diff --git "a/dev.jsonl" "b/dev.jsonl"
--- "a/dev.jsonl"
+++ "b/dev.jsonl"
@@ -1,1034 +1,1034 @@
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many singers do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM singer"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the total number of singers?\n[SQL]:\n", "output": "SELECT count(*) FROM singer"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show name, country, age for all singers ordered by age from the oldest to the youngest.\n[SQL]:\n", "output": "SELECT name , country , age FROM singer ORDER BY age DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names, countries, and ages for every singer in descending order of age?\n[SQL]:\n", "output": "SELECT name , country , age FROM singer ORDER BY age DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the average, minimum, and maximum age of all singers from France?\n[SQL]:\n", "output": "SELECT avg(age) , min(age) , max(age) FROM singer WHERE country = 'France'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the average, minimum, and maximum age for all French singers?\n[SQL]:\n", "output": "SELECT avg(age) , min(age) , max(age) FROM singer WHERE country = 'France'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the name and the release year of the song by the youngest singer.\n[SQL]:\n", "output": "SELECT song_name , song_release_year FROM singer ORDER BY age LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names and release years for all the songs of the youngest singer?\n[SQL]:\n", "output": "SELECT song_name , song_release_year FROM singer ORDER BY age LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are all distinct countries where singers above age 20 are from?\n[SQL]:\n", "output": "SELECT DISTINCT country FROM singer WHERE age > 20"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the different countries with singers above age 20?\n[SQL]:\n", "output": "SELECT DISTINCT country FROM singer WHERE age > 20"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show all countries and the number of singers in each country.\n[SQL]:\n", "output": "SELECT country , count(*) FROM singer GROUP BY country"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many singers are from each country?\n[SQL]:\n", "output": "SELECT country , count(*) FROM singer GROUP BY country"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:List all song names by singers above the average age.\n[SQL]:\n", "output": "SELECT song_name FROM singer WHERE age > (SELECT avg(age) FROM singer)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are all the song names by singers who are older than average?\n[SQL]:\n", "output": "SELECT song_name FROM singer WHERE age > (SELECT avg(age) FROM singer)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show location and name for all stadiums with a capacity between 5000 and 10000.\n[SQL]:\n", "output": "SELECT LOCATION , name FROM stadium WHERE capacity BETWEEN 5000 AND 10000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the locations and names of all stations with capacity between 5000 and 10000?\n[SQL]:\n", "output": "SELECT LOCATION , name FROM stadium WHERE capacity BETWEEN 5000 AND 10000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the maximum capacity and the average of all stadiums ?\n[SQL]:\n", "output": "select max(capacity), average from stadium"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the average and maximum capacities for all stadiums ?\n[SQL]:\n", "output": "select avg(capacity) , max(capacity) from stadium"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and capacity for the stadium with highest average attendance?\n[SQL]:\n", "output": "SELECT name , capacity FROM stadium ORDER BY average DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and capacity for the stadium with the highest average attendance?\n[SQL]:\n", "output": "SELECT name , capacity FROM stadium ORDER BY average DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many concerts are there in year 2014 or 2015?\n[SQL]:\n", "output": "SELECT count(*) FROM concert WHERE YEAR = 2014 OR YEAR = 2015"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many concerts occurred in 2014 or 2015?\n[SQL]:\n", "output": "SELECT count(*) FROM concert WHERE YEAR = 2014 OR YEAR = 2015"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the stadium name and the number of concerts in each stadium.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id GROUP BY T1.stadium_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:For each stadium, how many concerts play there?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id GROUP BY T1.stadium_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the stadium name and capacity with most number of concerts in year 2014 or after.\n[SQL]:\n", "output": "SELECT T2.name , T2.capacity FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year >= 2014 GROUP BY T2.stadium_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and capacity of the stadium with the most concerts after 2013 ?\n[SQL]:\n", "output": "select t2.name , t2.capacity from concert as t1 join stadium as t2 on t1.stadium_id = t2.stadium_id where t1.year > 2013 group by t2.stadium_id order by count(*) desc limit 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Which year has most number of concerts?\n[SQL]:\n", "output": "SELECT YEAR FROM concert GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the year that had the most concerts?\n[SQL]:\n", "output": "SELECT YEAR FROM concert GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the stadium names without any concert.\n[SQL]:\n", "output": "SELECT name FROM stadium WHERE stadium_id NOT IN (SELECT stadium_id FROM concert)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of the stadiums without any concerts?\n[SQL]:\n", "output": "SELECT name FROM stadium WHERE stadium_id NOT IN (SELECT stadium_id FROM concert)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show countries where a singer above age 40 and a singer below 30 are from.\n[SQL]:\n", "output": "SELECT country FROM singer WHERE age > 40 INTERSECT SELECT country FROM singer WHERE age < 30"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show names for all stadiums except for stadiums having a concert in year 2014.\n[SQL]:\n", "output": "SELECT name FROM stadium EXCEPT SELECT T2.name FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year = 2014"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of all stadiums that did not have a concert in 2014?\n[SQL]:\n", "output": "SELECT name FROM stadium EXCEPT SELECT T2.name FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year = 2014"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the name and theme for all concerts and the number of singers in each concert.\n[SQL]:\n", "output": "SELECT T2.concert_name , T2.theme , count(*) FROM singer_in_concert AS T1 JOIN concert AS T2 ON T1.concert_id = T2.concert_id GROUP BY T2.concert_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names , themes , and number of singers for every concert ?\n[SQL]:\n", "output": "select t2.concert_name , t2.theme , count(*) from singer_in_concert as t1 join concert as t2 on t1.concert_id = t2.concert_id group by t2.concert_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:List singer names and number of concerts for each singer.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id GROUP BY T2.singer_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers and number of concerts for each person?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id GROUP BY T2.singer_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:List all singer names in concerts in year 2014.\n[SQL]:\n", "output": "SELECT T2.name FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id JOIN concert AS T3 ON T1.concert_id = T3.concert_id WHERE T3.year = 2014"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers who performed in a concert in 2014?\n[SQL]:\n", "output": "SELECT T2.name FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id JOIN concert AS T3 ON T1.concert_id = T3.concert_id WHERE T3.year = 2014"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:what is the name and nation of the singer who have a song having 'Hey' in its name?\n[SQL]:\n", "output": "SELECT name , country FROM singer WHERE song_name LIKE '%Hey%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and country of origin of every singer who has a song with the word 'Hey' in its title?\n[SQL]:\n", "output": "SELECT name , country FROM singer WHERE song_name LIKE '%Hey%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Find the name and location of the stadiums which some concerts happened in the years of both 2014 and 2015.\n[SQL]:\n", "output": "SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2014 INTERSECT SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2015"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names and locations of the stadiums that had concerts that occurred in both 2014 and 2015?\n[SQL]:\n", "output": "SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2014 INTERSECT SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2015"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Find the number of concerts happened in the stadium with the highest capacity .\n[SQL]:\n", "output": "select count(*) from concert where stadium_id = (select stadium_id from stadium order by capacity desc limit 1)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the number of concerts that occurred in the stadium with the largest capacity ?\n[SQL]:\n", "output": "select count(*) from concert where stadium_id = (select stadium_id from stadium order by capacity desc limit 1)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of pets whose weight is heavier than 10.\n[SQL]:\n", "output": "SELECT count(*) FROM pets WHERE weight > 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many pets have a greater weight than 10?\n[SQL]:\n", "output": "SELECT count(*) FROM pets WHERE weight > 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the weight of the youngest dog.\n[SQL]:\n", "output": "SELECT weight FROM pets ORDER BY pet_age LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How much does the youngest dog weigh?\n[SQL]:\n", "output": "SELECT weight FROM pets ORDER BY pet_age LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the maximum weight for each type of pet. List the maximum weight and pet type.\n[SQL]:\n", "output": "SELECT max(weight) , petType FROM pets GROUP BY petType"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:List the maximum weight and type for each type of pet.\n[SQL]:\n", "output": "SELECT max(weight) , petType FROM pets GROUP BY petType"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find number of pets owned by students who are older than 20.\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.age > 20"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many pets are owned by students that have an age greater than 20?\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.age > 20"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of dog pets that are raised by female students (with sex F).\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T2.petid = T3.petid WHERE T1.sex = 'F' AND T3.pettype = 'dog'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many dog pets are raised by female students?\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T2.petid = T3.petid WHERE T1.sex = 'F' AND T3.pettype = 'dog'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of distinct type of pets.\n[SQL]:\n", "output": "SELECT count(DISTINCT pettype) FROM pets"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many different types of pet are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT pettype) FROM pets"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name of students who have cat or dog pet.\n[SQL]:\n", "output": "SELECT DISTINCT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' OR T3.pettype = 'dog'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the first names of every student who has a cat or dog as a pet?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' OR T3.pettype = 'dog'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name of students who have both cat and dog pets .\n[SQL]:\n", "output": "select t1.fname from student as t1 join has_pet as t2 on t1.stuid = t2.stuid join pets as t3 on t3.petid = t2.petid where t3.pettype = 'cat' intersect select t1.fname from student as t1 join has_pet as t2 on t1.stuid = t2.stuid join pets as t3 on t3.petid = t2.petid where t3.pettype = 'dog'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the students' first names who have both cats and dogs as pets?\n[SQL]:\n", "output": "SELECT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' INTERSECT SELECT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the major and age of students who do not have a cat pet.\n[SQL]:\n", "output": "SELECT major , age FROM student WHERE stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What major is every student who does not own a cat as a pet, and also how old are they?\n[SQL]:\n", "output": "SELECT major , age FROM student WHERE stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the id of students who do not have a cat pet.\n[SQL]:\n", "output": "SELECT stuid FROM student EXCEPT SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the ids of the students who do not own cats as pets?\n[SQL]:\n", "output": "SELECT stuid FROM student EXCEPT SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name and age of students who have a dog but do not have a cat as a pet.\n[SQL]:\n", "output": "SELECT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog' AND T1.stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the first name of every student who has a dog but does not have a cat?\n[SQL]:\n", "output": "SELECT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog' AND T1.stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the type and weight of the youngest pet.\n[SQL]:\n", "output": "SELECT pettype , weight FROM pets ORDER BY pet_age LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What type of pet is the youngest animal, and how much does it weigh?\n[SQL]:\n", "output": "SELECT pettype , weight FROM pets ORDER BY pet_age LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the id and weight of all pets whose age is older than 1.\n[SQL]:\n", "output": "SELECT petid , weight FROM pets WHERE pet_age > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the id and weight of every pet who is older than 1?\n[SQL]:\n", "output": "SELECT petid , weight FROM pets WHERE pet_age > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the average and maximum age for each type of pet.\n[SQL]:\n", "output": "SELECT avg(pet_age) , max(pet_age) , pettype FROM pets GROUP BY pettype"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the average and maximum age for each pet type?\n[SQL]:\n", "output": "SELECT avg(pet_age) , max(pet_age) , pettype FROM pets GROUP BY pettype"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the average weight for each pet type.\n[SQL]:\n", "output": "SELECT avg(weight) , pettype FROM pets GROUP BY pettype"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the average weight for each type of pet?\n[SQL]:\n", "output": "SELECT avg(weight) , pettype FROM pets GROUP BY pettype"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name and age of students who have a pet.\n[SQL]:\n", "output": "SELECT DISTINCT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the different first names and ages of the students who do have pets?\n[SQL]:\n", "output": "SELECT DISTINCT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the id of the pet owned by student whose last name is \u2018Smith\u2019.\n[SQL]:\n", "output": "SELECT T2.petid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.Lname = 'Smith'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the id of the pet owned by the student whose last name is 'Smith'?\n[SQL]:\n", "output": "SELECT T2.petid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.Lname = 'Smith'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of pets for each student who has any pet and student id.\n[SQL]:\n", "output": "SELECT count(*) , T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:For students who have pets , how many pets does each student have ? list their ids instead of names .\n[SQL]:\n", "output": "select count(*) , t1.stuid from student as t1 join has_pet as t2 on t1.stuid = t2.stuid group by t1.stuid"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name and gender of student who have more than one pet.\n[SQL]:\n", "output": "SELECT T1.fname , T1.sex FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid HAVING count(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the first name and gender of the all the students who have more than one pet?\n[SQL]:\n", "output": "SELECT T1.fname , T1.sex FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid HAVING count(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the last name of the student who has a cat that is age 3.\n[SQL]:\n", "output": "SELECT T1.lname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pet_age = 3 AND T3.pettype = 'cat'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the last name of the student who has a cat that is 3 years old?\n[SQL]:\n", "output": "SELECT T1.lname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pet_age = 3 AND T3.pettype = 'cat'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the average age of students who do not have any pet .\n[SQL]:\n", "output": "select avg(age) from student where stuid not in (select stuid from has_pet)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the average age for all students who do not own any pets ?\n[SQL]:\n", "output": "select avg(age) from student where stuid not in (select stuid from has_pet)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many continents are there?\n[SQL]:\n", "output": "SELECT count(*) FROM CONTINENTS;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of continents?\n[SQL]:\n", "output": "SELECT count(*) FROM CONTINENTS;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries does each continent have? List the continent id, continent name and the number of countries.\n[SQL]:\n", "output": "SELECT T1.ContId , T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.Continent GROUP BY T1.ContId;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For each continent, list its id, name, and how many countries it has?\n[SQL]:\n", "output": "SELECT T1.ContId , T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.Continent GROUP BY T1.ContId;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries are listed?\n[SQL]:\n", "output": "SELECT count(*) FROM COUNTRIES;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries exist?\n[SQL]:\n", "output": "SELECT count(*) FROM COUNTRIES;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many models does each car maker produce? List maker full name, id and the number.\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id , count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the full name of each car maker, along with its id and how many models it produces?\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id , count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which model of the car has the minimum horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.horsepower ASC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the model of the car with the smallest amount of horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.horsepower ASC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Find the model of the car whose weight is below the average weight.\n[SQL]:\n", "output": "SELECT T1.model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Weight < (SELECT avg(Weight) FROM CARS_DATA)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the model for the car with a weight smaller than the average?\n[SQL]:\n", "output": "SELECT T1.model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Weight < (SELECT avg(Weight) FROM CARS_DATA)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Find the name of the makers that produced some cars in the year of 1970?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model JOIN CARS_DATA AS T4 ON T3.MakeId = T4.id WHERE T4.year = '1970';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the name of the different car makers who produced a car in 1970?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model JOIN CARS_DATA AS T4 ON T3.MakeId = T4.id WHERE T4.year = '1970';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Find the make and production time of the cars that were produced in the earliest year?\n[SQL]:\n", "output": "SELECT T2.Make , T1.Year FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Year = (SELECT min(YEAR) FROM CARS_DATA);"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maker of the carr produced in the earliest year and what year was it?\n[SQL]:\n", "output": "SELECT T2.Make , T1.Year FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Year = (SELECT min(YEAR) FROM CARS_DATA);"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which distinct car models are the produced after 1980?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.model = T2.model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.id WHERE T3.year > 1980;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different models for the cards produced after 1980?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.model = T2.model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.id WHERE T3.year > 1980;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car makers are there in each continents? List the continent name and the count.\n[SQL]:\n", "output": "SELECT T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.continent JOIN car_makers AS T3 ON T2.CountryId = T3.Country GROUP BY T1.Continent;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the name of each continent and how many car makers are there in each one?\n[SQL]:\n", "output": "SELECT T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.continent JOIN car_makers AS T3 ON T2.CountryId = T3.Country GROUP BY T1.Continent;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which of the countries has the most car makers? List the country name.\n[SQL]:\n", "output": "SELECT T2.CountryName FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId GROUP BY T1.Country ORDER BY Count(*) DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the name of the country with the most car makers?\n[SQL]:\n", "output": "SELECT T2.CountryName FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId GROUP BY T1.Country ORDER BY Count(*) DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car models are produced by each maker ? Only list the count and the maker full name .\n[SQL]:\n", "output": "select count(*) , t2.fullname from model_list as t1 join car_makers as t2 on t1.maker = t2.id group by t2.id;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of car models that are produced by each maker and what is the id and full name of each maker?\n[SQL]:\n", "output": "SELECT Count(*) , T2.FullName , T2.id FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id GROUP BY T2.id;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the accelerate of the car make amc hornet sportabout (sw)?\n[SQL]:\n", "output": "SELECT T1.Accelerate FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Make = 'amc hornet sportabout (sw)';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How much does the car accelerate that makes amc hornet sportabout (sw)?\n[SQL]:\n", "output": "SELECT T1.Accelerate FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Make = 'amc hornet sportabout (sw)';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car makers are there in france?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId WHERE T2.CountryName = 'france';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of makers of care in France?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId WHERE T2.CountryName = 'france';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car models are produced in the usa?\n[SQL]:\n", "output": "SELECT count(*) FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id JOIN COUNTRIES AS T3 ON T2.Country = T3.CountryId WHERE T3.CountryName = 'usa';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the count of the car models produced in the United States?\n[SQL]:\n", "output": "SELECT count(*) FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id JOIN COUNTRIES AS T3 ON T2.Country = T3.CountryId WHERE T3.CountryName = 'usa';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average miles per gallon(mpg) of the cars with 4 cylinders?\n[SQL]:\n", "output": "SELECT avg(mpg) FROM CARS_DATA WHERE Cylinders = 4;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average miles per gallon of all the cards with 4 cylinders?\n[SQL]:\n", "output": "SELECT avg(mpg) FROM CARS_DATA WHERE Cylinders = 4;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the smallest weight of the car produced with 8 cylinders on 1974 ?\n[SQL]:\n", "output": "select min(weight) from cars_data where cylinders = 8 and year = 1974"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the minimum weight of the car with 8 cylinders produced in 1974 ?\n[SQL]:\n", "output": "select min(weight) from cars_data where cylinders = 8 and year = 1974"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are all the makers and models?\n[SQL]:\n", "output": "SELECT Maker , Model FROM MODEL_LIST;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the makers and models?\n[SQL]:\n", "output": "SELECT Maker , Model FROM MODEL_LIST;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the countries having at least one car maker? List name and id.\n[SQL]:\n", "output": "SELECT T1.CountryName , T1.CountryId FROM COUNTRIES AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.CountryId HAVING count(*) >= 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names and ids of all countries with at least one car maker?\n[SQL]:\n", "output": "SELECT T1.CountryName , T1.CountryId FROM COUNTRIES AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.CountryId HAVING count(*) >= 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of the cars with horsepower more than 150?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE horsepower > 150;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of cars with a horsepower greater than 150?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE horsepower > 150;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average weight of cars each year?\n[SQL]:\n", "output": "SELECT avg(Weight) , YEAR FROM CARS_DATA GROUP BY YEAR;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average weight and year for each year?\n[SQL]:\n", "output": "SELECT avg(Weight) , YEAR FROM CARS_DATA GROUP BY YEAR;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which countries in europe have at least 3 car manufacturers?\n[SQL]:\n", "output": "SELECT T1.CountryName FROM COUNTRIES AS T1 JOIN CONTINENTS AS T2 ON T1.Continent = T2.ContId JOIN CAR_MAKERS AS T3 ON T1.CountryId = T3.Country WHERE T2.Continent = 'europe' GROUP BY T1.CountryName HAVING count(*) >= 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names of all European countries with at least 3 manufacturers?\n[SQL]:\n", "output": "SELECT T1.CountryName FROM COUNTRIES AS T1 JOIN CONTINENTS AS T2 ON T1.Continent = T2.ContId JOIN CAR_MAKERS AS T3 ON T1.CountryId = T3.Country WHERE T2.Continent = 'europe' GROUP BY T1.CountryName HAVING count(*) >= 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum horsepower and the make of the car models with 3 cylinders?\n[SQL]:\n", "output": "SELECT T2.horsepower , T1.Make FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.cylinders = 3 ORDER BY T2.horsepower DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the largest amount of horsepower for the models with 3 cylinders and what make is it?\n[SQL]:\n", "output": "SELECT T2.horsepower , T1.Make FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.cylinders = 3 ORDER BY T2.horsepower DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which model saves the most gasoline? That is to say, have the maximum miles per gallon.\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.mpg DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the car model with the highest mpg ?\n[SQL]:\n", "output": "select t1.model from car_names as t1 join cars_data as t2 on t1.makeid = t2.id order by t2.mpg desc limit 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average horsepower of the cars before 1980?\n[SQL]:\n", "output": "SELECT avg(horsepower) FROM CARS_DATA WHERE YEAR < 1980;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average horsepower for all cars produced before 1980 ?\n[SQL]:\n", "output": "select avg(horsepower) from cars_data where year < 1980;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average edispl of the cars of model volvo?\n[SQL]:\n", "output": "SELECT avg(T2.edispl) FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T1.Model = 'volvo';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average edispl for all volvos?\n[SQL]:\n", "output": "SELECT avg(T2.edispl) FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T1.Model = 'volvo';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum accelerate for different number of cylinders?\n[SQL]:\n", "output": "SELECT max(Accelerate) , Cylinders FROM CARS_DATA GROUP BY Cylinders;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum accelerate for all the different cylinders?\n[SQL]:\n", "output": "SELECT max(Accelerate) , Cylinders FROM CARS_DATA GROUP BY Cylinders;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which model has the most version(make) of cars?\n[SQL]:\n", "output": "SELECT Model FROM CAR_NAMES GROUP BY Model ORDER BY count(*) DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What model has the most different versions?\n[SQL]:\n", "output": "SELECT Model FROM CAR_NAMES GROUP BY Model ORDER BY count(*) DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many cars have more than 4 cylinders?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE Cylinders > 4;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of cars with more than 4 cylinders?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE Cylinders > 4;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:how many cars were produced in 1980?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE YEAR = 1980;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:In 1980, how many cars were made?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE YEAR = 1980;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car models were produced by the maker with full name American Motor Company?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker WHERE T1.FullName = 'American Motor Company';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of car models created by the car maker American Motor Company?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker WHERE T1.FullName = 'American Motor Company';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which makers designed more than 3 car models? List full name and the id.\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) > 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names and ids of all makers with more than 3 models?\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) > 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which distinctive models are produced by maker with the full name General Motors or weighing more than 3500?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Model FROM CAR_NAMES AS T1 JOIN MODEL_LIST AS T2 ON T1.Model = T2.Model JOIN CAR_MAKERS AS T3 ON T2.Maker = T3.Id JOIN CARS_DATA AS T4 ON T1.MakeId = T4.Id WHERE T3.FullName = 'General Motors' OR T4.weight > 3500;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different models created by either the car maker General Motors or weighed more than 3500?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Model FROM CAR_NAMES AS T1 JOIN MODEL_LIST AS T2 ON T1.Model = T2.Model JOIN CAR_MAKERS AS T3 ON T2.Maker = T3.Id JOIN CARS_DATA AS T4 ON T1.MakeId = T4.Id WHERE T3.FullName = 'General Motors' OR T4.weight > 3500;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:In which years cars were produced weighing no less than 3000 and no more than 4000 ?\n[SQL]:\n", "output": "select distinct year from cars_data where weight between 3000 and 4000;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different years in which there were cars produced that weighed less than 4000 and also cars that weighted more than 3000 ?\n[SQL]:\n", "output": "select distinct year from cars_data where weight between 3000 and 4000;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the horsepower of the car with the largest accelerate?\n[SQL]:\n", "output": "SELECT T1.horsepower FROM CARS_DATA AS T1 ORDER BY T1.accelerate DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the horsepower of the car with the greatest accelerate?\n[SQL]:\n", "output": "SELECT T1.horsepower FROM CARS_DATA AS T1 ORDER BY T1.accelerate DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For model volvo, how many cylinders does the car with the least accelerate have?\n[SQL]:\n", "output": "SELECT T1.cylinders FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Model = 'volvo' ORDER BY T1.accelerate ASC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For a volvo model, how many cylinders does the version with least accelerate have?\n[SQL]:\n", "output": "SELECT T1.cylinders FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Model = 'volvo' ORDER BY T1.accelerate ASC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many cars have a larger accelerate than the car with the largest horsepower?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Accelerate > ( SELECT Accelerate FROM CARS_DATA ORDER BY Horsepower DESC LIMIT 1 );"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of cars with a greater accelerate than the one with the most horsepower?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Accelerate > ( SELECT Accelerate FROM CARS_DATA ORDER BY Horsepower DESC LIMIT 1 );"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries has more than 2 car makers ?\n[SQL]:\n", "output": "select count(*) from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of countries with more than 2 car makers ?\n[SQL]:\n", "output": "select count(*) from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many cars has over 6 cylinders?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Cylinders > 6;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of carsw ith over 6 cylinders?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Cylinders > 6;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For the cars with 4 cylinders, which model has the largest horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Cylinders = 4 ORDER BY T2.horsepower DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For all of the 4 cylinder cars, which model has the most horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Cylinders = 4 ORDER BY T2.horsepower DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Among the cars with more than lowest horsepower, which ones do not have more than 3 cylinders? List the car makeid and make name.\n[SQL]:\n", "output": "SELECT T2.MakeId , T2.Make FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Horsepower > (SELECT min(Horsepower) FROM CARS_DATA) AND T1.Cylinders <= 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Among the cars that do not have the minimum horsepower , what are the make ids and names of all those with less than 4 cylinders ?\n[SQL]:\n", "output": "select t2.makeid , t2.make from cars_data as t1 join car_names as t2 on t1.id = t2.makeid where t1.horsepower > (select min(horsepower) from cars_data) and t1.cylinders < 4;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum miles per gallon of the car with 8 cylinders or produced before 1980 ?\n[SQL]:\n", "output": "select max(mpg) from cars_data where cylinders = 8 or year < 1980"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum mpg of the cars that had 8 cylinders or that were produced before 1980 ?\n[SQL]:\n", "output": "select max(mpg) from cars_data where cylinders = 8 or year < 1980"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which models are lighter than 3500 but not built by the 'Ford Motor Company'?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.Model = T2.Model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.Id JOIN CAR_MAKERS AS T4 ON T1.Maker = T4.Id WHERE T3.weight < 3500 AND T4.FullName != 'Ford Motor Company';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different models wthat are lighter than 3500 but were not built by the Ford Motor Company?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.Model = T2.Model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.Id JOIN CAR_MAKERS AS T4 ON T1.Maker = T4.Id WHERE T3.weight < 3500 AND T4.FullName != 'Ford Motor Company';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the name of the countries where there is not a single car maker?\n[SQL]:\n", "output": "SELECT CountryName FROM countries EXCEPT SELECT T1.CountryName FROM countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.countryId = T2.Country;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names of the countries with no car makers?\n[SQL]:\n", "output": "SELECT CountryName FROM countries EXCEPT SELECT T1.CountryName FROM countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.countryId = T2.Country;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which are the car makers which produce at least 2 models and more than 3 car makers ? List the id and the maker .\n[SQL]:\n", "output": "select t1.id , t1.maker from car_makers as t1 join model_list as t2 on t1.id = t2.maker group by t1.id having count(*) >= 2 intersect select t1.id , t1.maker from car_makers as t1 join model_list as t2 on t1.id = t2.maker join car_names as t3 on t2.model = t3.model group by t1.id having count(*) > 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the ids and makers of all car makers that produce at least 2 models and make more than 3 cars?\n[SQL]:\n", "output": "SELECT T1.Id , T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) >= 2 INTERSECT SELECT T1.Id , T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model GROUP BY T1.Id HAVING count(*) > 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the id and names of the countries which have more than 3 car makers or produce the 'fiat' model?\n[SQL]:\n", "output": "SELECT T1.countryId , T1.CountryName FROM Countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.countryId HAVING count(*) > 3 UNION SELECT T1.countryId , T1.CountryName FROM Countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country JOIN MODEL_LIST AS T3 ON T2.Id = T3.Maker WHERE T3.Model = 'fiat';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the ids and names of all countries that either have more than 3 car makers or produce fiat model ?\n[SQL]:\n", "output": "select t1.countryid , t1.countryname from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 3 union select t1.countryid , t1.countryname from countries as t1 join car_makers as t2 on t1.countryid = t2.country join model_list as t3 on t2.id = t3.maker where t3.model = 'fiat';"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which country does Airline \"JetBlue Airways\" belong to?\n[SQL]:\n", "output": "SELECT Country FROM AIRLINES WHERE Airline = \"JetBlue Airways\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What country is Jetblue Airways affiliated with?\n[SQL]:\n", "output": "SELECT Country FROM AIRLINES WHERE Airline = \"JetBlue Airways\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the abbreviation of Airline \"JetBlue Airways\"?\n[SQL]:\n", "output": "SELECT Abbreviation FROM AIRLINES WHERE Airline = \"JetBlue Airways\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which abbreviation corresponds to Jetblue Airways?\n[SQL]:\n", "output": "SELECT Abbreviation FROM AIRLINES WHERE Airline = \"JetBlue Airways\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:List all airline names and their abbreviations in \"USA\".\n[SQL]:\n", "output": "SELECT Airline , Abbreviation FROM AIRLINES WHERE Country = \"USA\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are the airline names and abbreviations for airlines in the USA?\n[SQL]:\n", "output": "SELECT Airline , Abbreviation FROM AIRLINES WHERE Country = \"USA\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:List the airport code and name in the city of Anthony.\n[SQL]:\n", "output": "SELECT AirportCode , AirportName FROM AIRPORTS WHERE city = \"Anthony\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the airport code and airport name corresonding to the city Anthony.\n[SQL]:\n", "output": "SELECT AirportCode , AirportName FROM AIRPORTS WHERE city = \"Anthony\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many airlines do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the total number of airlines?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many airports do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRPORTS"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of airports.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRPORTS"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of flights.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airline has abbreviation 'UAL'?\n[SQL]:\n", "output": "SELECT Airline FROM AIRLINES WHERE Abbreviation = \"UAL\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the airline with abbreviation 'UAL'.\n[SQL]:\n", "output": "SELECT Airline FROM AIRLINES WHERE Abbreviation = \"UAL\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many airlines are from USA?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES WHERE Country = \"USA\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of airlines in the USA.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES WHERE Country = \"USA\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city and country is the Alton airport at?\n[SQL]:\n", "output": "SELECT City , Country FROM AIRPORTS WHERE AirportName = \"Alton\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the city and country for the Alton airport.\n[SQL]:\n", "output": "SELECT City , Country FROM AIRPORTS WHERE AirportName = \"Alton\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the airport name for airport 'AKO'?\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE AirportCode = \"AKO\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the name of the airport with code 'AKO'.\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE AirportCode = \"AKO\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are airport names at City 'Aberdeen'?\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are the names of airports in Aberdeen?\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights depart from 'APG'?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE SourceAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of flights departing from 'APG'.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE SourceAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights have destination ATO?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE DestAirport = \"ATO\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of flights into ATO.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE DestAirport = \"ATO\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights depart from City Aberdeen?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of flights departing from Aberdeen.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights arriving in Aberdeen city?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of flights arriving in Aberdeen.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights depart from City 'Aberdeen' and have destination City 'Ashley'?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRPORTS AS T3 ON T1.SourceAirport = T3.AirportCode WHERE T2.City = \"Ashley\" AND T3.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights fly from Aberdeen to Ashley?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRPORTS AS T3 ON T1.SourceAirport = T3.AirportCode WHERE T2.City = \"Ashley\" AND T3.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights does airline 'JetBlue Airways' have?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T1.Airline = T2.uid WHERE T2.Airline = \"JetBlue Airways\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the number of Jetblue Airways flights.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T1.Airline = T2.uid WHERE T2.Airline = \"JetBlue Airways\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many 'United Airlines' flights go to Airport 'ASY'?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.DestAirport = \"ASY\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of United Airlines flights arriving in ASY Airport.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.DestAirport = \"ASY\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many 'United Airlines' flights depart from Airport 'AHD'?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.SourceAirport = \"AHD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of United Airlines flights leaving from AHD Airport.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.SourceAirport = \"AHD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many United Airlines flights go to City 'Aberdeen'?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRLINES AS T3 ON T3.uid = T1.Airline WHERE T2.City = \"Aberdeen\" AND T3.Airline = \"United Airlines\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of United Airlines flights that arrive in Aberdeen.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRLINES AS T3 ON T3.uid = T1.Airline WHERE T2.City = \"Aberdeen\" AND T3.Airline = \"United Airlines\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city has most number of arriving flights?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city has the most frequent destination airport?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city has most number of departing flights?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.SourceAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city is the most frequent source airport?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.SourceAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the code of airport that has the highest number of flights?\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the airport code of the airport with the most flights?\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the code of airport that has fewest number of flights?\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the code of the airport with the least flights.\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airline has most number of flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What airline serves the most flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find the abbreviation and country of the airline that has fewest number of flights?\n[SQL]:\n", "output": "SELECT T1.Abbreviation , T1.Country FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the abbreviation of the airilne has the fewest flights and what country is it in?\n[SQL]:\n", "output": "SELECT T1.Abbreviation , T1.Country FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are airlines that have some flight departing from airport 'AHD'?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"AHD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have a flight with source airport AHD?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"AHD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are airlines that have flights arriving at airport 'AHD'?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.DestAirport = \"AHD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have a flight with destination airport AHD?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.DestAirport = \"AHD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have flights from both airports 'APG' and 'CVO'.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\" INTERSECT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have departing flights from both APG and CVO airports?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\" INTERSECT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have flights from airport 'CVO' but not from 'APG'.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\" EXCEPT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have departures from CVO but not from APG airports?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\" EXCEPT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have at least 10 flights.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) > 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have at least 10 flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) > 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have fewer than 200 flights.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) < 200"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have less than 200 flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) < 200"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of Airline \"United Airlines\"?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T2.uid = T1.Airline WHERE T2.Airline = \"United Airlines\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which flight numbers correspond to United Airlines flights?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T2.uid = T1.Airline WHERE T2.Airline = \"United Airlines\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights departing from Airport \"APG\"?\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE SourceAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights leaving from APG.\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE SourceAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights arriving at Airport \"APG\"?\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE DestAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights landing at APG.\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE DestAirport = \"APG\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights departing from City \"Aberdeen \"?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights leaving from Aberdeen.\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights arriving at City \"Aberdeen\"?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights arriving in Aberdeen.\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find the number of flights landing in the city of Aberdeen or Abilene.\n[SQL]:\n", "output": "SELECT count(*) FROM Flights AS T1 JOIN Airports AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.city = \"Aberdeen\" OR T2.city = \"Abilene\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights land in Aberdeen or Abilene?\n[SQL]:\n", "output": "SELECT count(*) FROM Flights AS T1 JOIN Airports AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.city = \"Aberdeen\" OR T2.city = \"Abilene\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find the name of airports which do not have any flight in and out.\n[SQL]:\n", "output": "SELECT AirportName FROM Airports WHERE AirportCode NOT IN (SELECT SourceAirport FROM Flights UNION SELECT DestAirport FROM Flights)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airports do not have departing or arriving flights?\n[SQL]:\n", "output": "SELECT AirportName FROM Airports WHERE AirportCode NOT IN (SELECT SourceAirport FROM Flights UNION SELECT DestAirport FROM Flights)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:How many employees are there?\n[SQL]:\n", "output": "SELECT count(*) FROM employee"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Count the number of employees\n[SQL]:\n", "output": "SELECT count(*) FROM employee"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Sort employee names by their age in ascending order.\n[SQL]:\n", "output": "SELECT name FROM employee ORDER BY age"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:List the names of employees and sort in ascending order of age.\n[SQL]:\n", "output": "SELECT name FROM employee ORDER BY age"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is the number of employees from each city?\n[SQL]:\n", "output": "SELECT count(*) , city FROM employee GROUP BY city"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Count the number of employees for each city.\n[SQL]:\n", "output": "SELECT count(*) , city FROM employee GROUP BY city"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which cities do more than one employee under age 30 come from?\n[SQL]:\n", "output": "SELECT city FROM employee WHERE age < 30 GROUP BY city HAVING count(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the cities that have more than one employee under age 30.\n[SQL]:\n", "output": "SELECT city FROM employee WHERE age < 30 GROUP BY city HAVING count(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the number of shops in each location.\n[SQL]:\n", "output": "SELECT count(*) , LOCATION FROM shop GROUP BY LOCATION"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:How many shops are there in each location?\n[SQL]:\n", "output": "SELECT count(*) , LOCATION FROM shop GROUP BY LOCATION"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the manager name and district of the shop whose number of products is the largest.\n[SQL]:\n", "output": "SELECT manager_name , district FROM shop ORDER BY number_products DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What are the manager name and district of the shop that sells the largest number of products?\n[SQL]:\n", "output": "SELECT manager_name , district FROM shop ORDER BY number_products DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:find the minimum and maximum number of products of all stores.\n[SQL]:\n", "output": "SELECT min(Number_products) , max(Number_products) FROM shop"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What are the minimum and maximum number of products across all the shops?\n[SQL]:\n", "output": "SELECT min(Number_products) , max(Number_products) FROM shop"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Return the name, location and district of all shops in descending order of number of products.\n[SQL]:\n", "output": "SELECT name , LOCATION , district FROM shop ORDER BY number_products DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Sort all the shops by number products in descending order, and return the name, location and district of each shop.\n[SQL]:\n", "output": "SELECT name , LOCATION , district FROM shop ORDER BY number_products DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the names of stores whose number products is more than the average number of products.\n[SQL]:\n", "output": "SELECT name FROM shop WHERE number_products > (SELECT avg(number_products) FROM shop)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which shops' number products is above the average? Give me the shop names.\n[SQL]:\n", "output": "SELECT name FROM shop WHERE number_products > (SELECT avg(number_products) FROM shop)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:find the name of employee who was awarded the most times in the evaluation.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID GROUP BY t2.Employee_ID ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which employee received the most awards in evaluations? Give me the employee name.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID GROUP BY t2.Employee_ID ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the name of the employee who got the highest one time bonus.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID ORDER BY t2.bonus DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which employee received the biggest bonus? Give me the employee name.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID ORDER BY t2.bonus DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the names of employees who never won any award in the evaluation.\n[SQL]:\n", "output": "SELECT name FROM employee WHERE Employee_ID NOT IN (SELECT Employee_ID FROM evaluation)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What are the names of the employees who never received any evaluation?\n[SQL]:\n", "output": "SELECT name FROM employee WHERE Employee_ID NOT IN (SELECT Employee_ID FROM evaluation)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is the name of the shop that is hiring the largest number of employees?\n[SQL]:\n", "output": "SELECT t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t1.shop_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which shop has the most employees? Give me the shop name.\n[SQL]:\n", "output": "SELECT t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t1.shop_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the name of the shops that do not hire any employee.\n[SQL]:\n", "output": "SELECT name FROM shop WHERE shop_id NOT IN (SELECT shop_id FROM hiring)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which shops run with no employees? Find the shop names\n[SQL]:\n", "output": "SELECT name FROM shop WHERE shop_id NOT IN (SELECT shop_id FROM hiring)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the number of employees hired in each shop; show the shop name as well.\n[SQL]:\n", "output": "SELECT count(*) , t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t2.name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:For each shop, return the number of employees working there and the name of the shop.\n[SQL]:\n", "output": "SELECT count(*) , t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t2.name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is total bonus given in all evaluations?\n[SQL]:\n", "output": "SELECT sum(bonus) FROM evaluation"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the total amount of bonus given in all the evaluations.\n[SQL]:\n", "output": "SELECT sum(bonus) FROM evaluation"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Give me all the information about hiring.\n[SQL]:\n", "output": "SELECT * FROM hiring"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is all the information about hiring?\n[SQL]:\n", "output": "SELECT * FROM hiring"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which district has both stores with less than 3000 products and stores with more than 10000 products?\n[SQL]:\n", "output": "SELECT district FROM shop WHERE Number_products < 3000 INTERSECT SELECT district FROM shop WHERE Number_products > 10000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the districts in which there are both shops selling less than 3000 products and shops selling more than 10000 products.\n[SQL]:\n", "output": "SELECT district FROM shop WHERE Number_products < 3000 INTERSECT SELECT district FROM shop WHERE Number_products > 10000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:How many different store locations are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT LOCATION) FROM shop"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Count the number of distinct store locations.\n[SQL]:\n", "output": "SELECT count(DISTINCT LOCATION) FROM shop"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many documents do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of documents.\n[SQL]:\n", "output": "SELECT count(*) FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:List document IDs, document names, and document descriptions for all documents.\n[SQL]:\n", "output": "SELECT document_id , document_name , document_description FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids, names, and descriptions for all documents?\n[SQL]:\n", "output": "SELECT document_id , document_name , document_description FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document name and template id for document with description with the letter 'w' in it?\n[SQL]:\n", "output": "SELECT document_name , template_id FROM Documents WHERE Document_Description LIKE \"%w%\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the names and template ids for documents that contain the letter w in their description.\n[SQL]:\n", "output": "SELECT document_name , template_id FROM Documents WHERE Document_Description LIKE \"%w%\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id, template id and description for document named \"Robbin CV\"?\n[SQL]:\n", "output": "SELECT document_id , template_id , Document_Description FROM Documents WHERE document_name = \"Robbin CV\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the document id, template id, and description for the document with the name Robbin CV.\n[SQL]:\n", "output": "SELECT document_id , template_id , Document_Description FROM Documents WHERE document_name = \"Robbin CV\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many different templates do all document use?\n[SQL]:\n", "output": "SELECT count(DISTINCT template_id) FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of different templates used for documents.\n[SQL]:\n", "output": "SELECT count(DISTINCT template_id) FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many documents are using the template with type code 'PPT'?\n[SQL]:\n", "output": "SELECT count(*) FROM Documents AS T1 JOIN Templates AS T2 ON T1.Template_ID = T2.Template_ID WHERE T2.Template_Type_Code = 'PPT'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of documents that use the PPT template type.\n[SQL]:\n", "output": "SELECT count(*) FROM Documents AS T1 JOIN Templates AS T2 ON T1.Template_ID = T2.Template_ID WHERE T2.Template_Type_Code = 'PPT'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template ids and number of documents using each template.\n[SQL]:\n", "output": "SELECT template_id , count(*) FROM Documents GROUP BY template_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are all different template ids used for documents, and how many times were each of them used?\n[SQL]:\n", "output": "SELECT template_id , count(*) FROM Documents GROUP BY template_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the id and type code for the template used by the most documents?\n[SQL]:\n", "output": "SELECT T1.template_id , T2.Template_Type_Code FROM Documents AS T1 JOIN Templates AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the id and type code of the template that is used for the greatest number of documents.\n[SQL]:\n", "output": "SELECT T1.template_id , T2.Template_Type_Code FROM Documents AS T1 JOIN Templates AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show ids for all templates that are used by more than one document.\n[SQL]:\n", "output": "SELECT template_id FROM Documents GROUP BY template_id HAVING count(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the template ids of any templates used in more than a single document?\n[SQL]:\n", "output": "SELECT template_id FROM Documents GROUP BY template_id HAVING count(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show ids for all templates not used by any document.\n[SQL]:\n", "output": "SELECT template_id FROM Templates EXCEPT SELECT template_id FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids for templates that are not used in any documents?\n[SQL]:\n", "output": "SELECT template_id FROM Templates EXCEPT SELECT template_id FROM Documents"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many templates do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of templates.\n[SQL]:\n", "output": "SELECT count(*) FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show template ids, version numbers, and template type codes for all templates.\n[SQL]:\n", "output": "SELECT template_id , version_number , template_type_code FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids, version numbers, and type codes for each template?\n[SQL]:\n", "output": "SELECT template_id , version_number , template_type_code FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all distinct template type codes for all templates.\n[SQL]:\n", "output": "SELECT DISTINCT template_type_code FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the different template type codes?\n[SQL]:\n", "output": "SELECT DISTINCT template_type_code FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids of templates with template type code PP or PPT?\n[SQL]:\n", "output": "SELECT template_id FROM Templates WHERE template_type_code = \"PP\" OR template_type_code = \"PPT\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the ids of templates that have the code PP or PPT.\n[SQL]:\n", "output": "SELECT template_id FROM Templates WHERE template_type_code = \"PP\" OR template_type_code = \"PPT\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many templates have template type code CV?\n[SQL]:\n", "output": "SELECT count(*) FROM Templates WHERE template_type_code = \"CV\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of templates of the type CV.\n[SQL]:\n", "output": "SELECT count(*) FROM Templates WHERE template_type_code = \"CV\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the version number and template type code for the template with version number later than 5?\n[SQL]:\n", "output": "SELECT version_number , template_type_code FROM Templates WHERE version_number > 5"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the version numbers and template type codes of templates with a version number greater than 5.\n[SQL]:\n", "output": "SELECT version_number , template_type_code FROM Templates WHERE version_number > 5"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes and number of templates for each.\n[SQL]:\n", "output": "SELECT template_type_code , count(*) FROM Templates GROUP BY template_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the different template type codes, and how many templates correspond to each?\n[SQL]:\n", "output": "SELECT template_type_code , count(*) FROM Templates GROUP BY template_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Which template type code has most number of templates?\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the type code of the template type that the most templates belong to.\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes with less than three templates.\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code HAVING count(*) < 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the codes of template types that have fewer than 3 templates?\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code HAVING count(*) < 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What the smallest version number and its template type code?\n[SQL]:\n", "output": "SELECT min(Version_Number) , template_type_code FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the lowest version number, along with its corresponding template type code.\n[SQL]:\n", "output": "SELECT min(Version_Number) , template_type_code FROM Templates"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the template type code of the template used by document with the name \"Data base\"?\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T2.document_name = \"Data base\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the template type code of the template that is used by a document named Data base.\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T2.document_name = \"Data base\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all document names using templates with template type code BK.\n[SQL]:\n", "output": "SELECT T2.document_name FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T1.template_type_code = \"BK\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the names of documents that use templates with the code BK?\n[SQL]:\n", "output": "SELECT T2.document_name FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T1.template_type_code = \"BK\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes and the number of documents using each type.\n[SQL]:\n", "output": "SELECT T1.template_type_code , count(*) FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the different template type codes, and how many documents use each type?\n[SQL]:\n", "output": "SELECT T1.template_type_code , count(*) FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Which template type code is used by most number of documents?\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the code of the template type that is most commonly used in documents.\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes that are not used by any document.\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates EXCEPT SELECT template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the codes of template types that are not used for any document?\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates EXCEPT SELECT template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes and descriptions.\n[SQL]:\n", "output": "SELECT template_type_code , template_type_description FROM Ref_template_types"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the type codes and descriptions for all template types?\n[SQL]:\n", "output": "SELECT template_type_code , template_type_description FROM Ref_template_types"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the template type descriptions for template type code \"AD\".\n[SQL]:\n", "output": "SELECT template_type_description FROM Ref_template_types WHERE template_type_code = \"AD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the template type description of the template type with the code AD.\n[SQL]:\n", "output": "SELECT template_type_description FROM Ref_template_types WHERE template_type_code = \"AD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the template type code for template type description \"Book\".\n[SQL]:\n", "output": "SELECT template_type_code FROM Ref_template_types WHERE template_type_description = \"Book\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the type code of the template type with the description \"Book\".\n[SQL]:\n", "output": "SELECT template_type_code FROM Ref_template_types WHERE template_type_description = \"Book\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the distinct template type descriptions for the templates ever used by any document?\n[SQL]:\n", "output": "SELECT DISTINCT T1.template_type_description FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code JOIN Documents AS T3 ON T2.Template_ID = T3.template_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the different descriptions for templates that have been used in a document.\n[SQL]:\n", "output": "SELECT DISTINCT T1.template_type_description FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code JOIN Documents AS T3 ON T2.Template_ID = T3.template_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the template ids with template type description \"Presentation\".\n[SQL]:\n", "output": "SELECT T2.template_id FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code WHERE T1.template_type_description = \"Presentation\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the ids corresponding to templates with the description 'Presentation'.\n[SQL]:\n", "output": "SELECT T2.template_id FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code WHERE T1.template_type_description = \"Presentation\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many paragraphs in total?\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of paragraphs.\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many paragraphs for the document with name 'Summer Show'?\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_ID = T2.document_ID WHERE T2.document_name = 'Summer Show'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of paragraphs in the document named 'Summer Show'.\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_ID = T2.document_ID WHERE T2.document_name = 'Summer Show'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show paragraph details for paragraph with text 'Korea ' .\n[SQL]:\n", "output": "select other_details from paragraphs where paragraph_text like 'korea'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the details for the paragraph that includes the text 'Korea ' ?\n[SQL]:\n", "output": "select other_details from paragraphs where paragraph_text like 'korea'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all paragraph ids and texts for the document with name 'Welcome to NY'.\n[SQL]:\n", "output": "SELECT T1.paragraph_id , T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.Document_Name = 'Welcome to NY'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids and texts of paragraphs in the document titled 'Welcome to NY'?\n[SQL]:\n", "output": "SELECT T1.paragraph_id , T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.Document_Name = 'Welcome to NY'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all paragraph texts for the document \"Customer reviews\".\n[SQL]:\n", "output": "SELECT T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.document_name = \"Customer reviews\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the paragraph texts for the document with the name 'Customer reviews'?\n[SQL]:\n", "output": "SELECT T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.document_name = \"Customer reviews\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all document ids and the number of paragraphs in each document. Order by document id.\n[SQL]:\n", "output": "SELECT document_id , count(*) FROM Paragraphs GROUP BY document_id ORDER BY document_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the different document ids along with the number of paragraphs corresponding to each, ordered by id.\n[SQL]:\n", "output": "SELECT document_id , count(*) FROM Paragraphs GROUP BY document_id ORDER BY document_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all document ids, names and the number of paragraphs in each document.\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name , count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids and names of each document, as well as the number of paragraphs in each?\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name , count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:List all document ids with at least two paragraphs.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids of documents that have 2 or more paragraphs?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id and name with greatest number of paragraphs?\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the id and name of the document with the most paragraphs.\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id with least number of paragraphs?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id ORDER BY count(*) ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the id of the document with the fewest paragraphs.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id ORDER BY count(*) ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id with 1 to 2 paragraphs?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) BETWEEN 1 AND 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Give the ids of documents that have between one and two paragraphs.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) BETWEEN 1 AND 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show the document id with paragraph text 'Brazil' and 'Ireland'.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Brazil' INTERSECT SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Ireland'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids of documents that contain the paragraph text 'Brazil' and 'Ireland'?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Brazil' INTERSECT SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Ireland'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:How many teachers are there?\n[SQL]:\n", "output": "SELECT count(*) FROM teacher"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the total count of teachers?\n[SQL]:\n", "output": "SELECT count(*) FROM teacher"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the names of teachers in ascending order of age.\n[SQL]:\n", "output": "SELECT Name FROM teacher ORDER BY Age ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers ordered by ascending age?\n[SQL]:\n", "output": "SELECT Name FROM teacher ORDER BY Age ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the age and hometown of teachers?\n[SQL]:\n", "output": "SELECT Age , Hometown FROM teacher"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the age and hometown of every teacher?\n[SQL]:\n", "output": "SELECT Age , Hometown FROM teacher"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the name of teachers whose hometown is not `` Little Lever Urban District '' .\n[SQL]:\n", "output": "select name from teacher where hometown != \"little lever urban district\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers whose hometown is not `` Little Lever Urban District '' ?\n[SQL]:\n", "output": "select name from teacher where hometown != \"little lever urban district\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show the name of teachers aged either 32 or 33?\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Age = 32 OR Age = 33"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers who are aged either 32 or 33?\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Age = 32 OR Age = 33"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the hometown of the youngest teacher?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher ORDER BY Age ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Where is the youngest teacher from?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher ORDER BY Age ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show different hometown of teachers and the number of teachers from each hometown.\n[SQL]:\n", "output": "SELECT Hometown , COUNT(*) FROM teacher GROUP BY Hometown"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:For each hometown, how many teachers are there?\n[SQL]:\n", "output": "SELECT Hometown , COUNT(*) FROM teacher GROUP BY Hometown"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the most common hometown of teachers.\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the most commmon hometowns for teachers?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show the hometowns shared by at least two teachers.\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown HAVING COUNT(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the towns from which at least two teachers come from?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown HAVING COUNT(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers and the courses they are arranged to teach.\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the name of each teacher and what course they teach?\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers and the courses they are arranged to teach in ascending alphabetical order of the teacher's name.\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID ORDER BY T3.Name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers and the courses they teach in ascending alphabetical order by the name of the teacher?\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID ORDER BY T3.Name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show the name of the teacher for the math course.\n[SQL]:\n", "output": "SELECT T3.Name FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID WHERE T2.Course = \"Math\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the people who teach math courses?\n[SQL]:\n", "output": "SELECT T3.Name FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID WHERE T2.Course = \"Math\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers and the number of courses they teach.\n[SQL]:\n", "output": "SELECT T2.Name , COUNT(*) FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers and how many courses do they teach?\n[SQL]:\n", "output": "SELECT T2.Name , COUNT(*) FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers that teach at least two courses.\n[SQL]:\n", "output": "SELECT T2.Name FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name HAVING COUNT(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers who teach at least two courses?\n[SQL]:\n", "output": "SELECT T2.Name FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name HAVING COUNT(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the names of teachers who have not been arranged to teach courses.\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Teacher_id NOT IN (SELECT Teacher_id FROM course_arrange)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers whose courses have not been arranged?\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Teacher_id NOT IN (SELECT Teacher_id FROM course_arrange)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:How many visitors below age 30 are there?\n[SQL]:\n", "output": "SELECT count(*) FROM visitor WHERE age < 30"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the names of the visitors whose membership level is higher than 4, and order the results by the level from high to low.\n[SQL]:\n", "output": "SELECT name FROM visitor WHERE Level_of_membership > 4 ORDER BY Level_of_membership DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the average age of the visitors whose membership level is not higher than 4?\n[SQL]:\n", "output": "SELECT avg(age) FROM visitor WHERE Level_of_membership <= 4"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the name and membership level of the visitors whose membership level is higher than 4, and sort by their age from old to young.\n[SQL]:\n", "output": "SELECT name , Level_of_membership FROM visitor WHERE Level_of_membership > 4 ORDER BY age DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the id and name of the museum that has the most staff members?\n[SQL]:\n", "output": "SELECT museum_id , name FROM museum ORDER BY num_of_staff DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the average number of staff working for the museums that were open before 2009.\n[SQL]:\n", "output": "SELECT avg(num_of_staff) FROM museum WHERE open_year < 2009"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the opening year and staff number of the museum named Plaza Museum?\n[SQL]:\n", "output": "SELECT Num_of_Staff , Open_Year FROM museum WHERE name = 'Plaza Museum'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:find the names of museums which have more staff than the minimum staff number of all museums opened after 2010.\n[SQL]:\n", "output": "SELECT name FROM museum WHERE num_of_staff > (SELECT min(num_of_staff) FROM museum WHERE open_year > 2010)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:find the id, name and age for visitors who visited some museums more than once.\n[SQL]:\n", "output": "SELECT t1.id , t1.name , t1.age FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id GROUP BY t1.id HAVING count(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the id, name and membership level of visitors who have spent the largest amount of money in total in all museum tickets?\n[SQL]:\n", "output": "SELECT t2.visitor_id , t1.name , t1.Level_of_membership FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id GROUP BY t2.visitor_id ORDER BY sum(t2.Total_spent) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the id and name of the museum visited most times?\n[SQL]:\n", "output": "SELECT t2.Museum_ID , t1.name FROM museum AS t1 JOIN visit AS t2 ON t1.Museum_ID = t2.Museum_ID GROUP BY t2.Museum_ID ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the name of the museum that had no visitor yet?\n[SQL]:\n", "output": "SELECT name FROM museum WHERE Museum_ID NOT IN (SELECT museum_id FROM visit)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the name and age of the visitor who bought the most tickets at once.\n[SQL]:\n", "output": "SELECT t1.name , t1.age FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id ORDER BY t2.num_of_ticket DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the average and maximum number of tickets bought in all visits?\n[SQL]:\n", "output": "SELECT avg(num_of_ticket) , max(num_of_ticket) FROM visit"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the total ticket expense of the visitors whose membership level is 1?\n[SQL]:\n", "output": "SELECT sum(t2.Total_spent) FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id WHERE t1.Level_of_membership = 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the name of the visitor who visited both a museum opened before 2009 and a museum opened after 2011?\n[SQL]:\n", "output": "SELECT t1.name FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id JOIN museum AS t3 ON t3.Museum_ID = t2.Museum_ID WHERE t3.open_year < 2009 INTERSECT SELECT t1.name FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id JOIN museum AS t3 ON t3.Museum_ID = t2.Museum_ID WHERE t3.open_year > 2011"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the number of visitors who did not visit any museum opened after 2010.\n[SQL]:\n", "output": "SELECT count(*) FROM visitor WHERE id NOT IN (SELECT t2.visitor_id FROM museum AS t1 JOIN visit AS t2 ON t1.Museum_ID = t2.Museum_ID WHERE t1.open_year > 2010)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:How many museums were opened after 2013 or before 2008?\n[SQL]:\n", "output": "SELECT count(*) FROM museum WHERE open_year > 2013 OR open_year < 2008"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total number of players.\n[SQL]:\n", "output": "SELECT count(*) FROM players"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many players are there?\n[SQL]:\n", "output": "SELECT count(*) FROM players"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total number of matches.\n[SQL]:\n", "output": "SELECT count(*) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Count the number of matches.\n[SQL]:\n", "output": "SELECT count(*) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the first name and birth date of all players from the country with code USA.\n[SQL]:\n", "output": "SELECT first_name , birth_date FROM players WHERE country_code = 'USA'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names and birth dates of players from the USA?\n[SQL]:\n", "output": "SELECT first_name , birth_date FROM players WHERE country_code = 'USA'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the average age of losers and winners of all matches.\n[SQL]:\n", "output": "SELECT avg(loser_age) , avg(winner_age) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the average ages of losers and winners across matches?\n[SQL]:\n", "output": "SELECT avg(loser_age) , avg(winner_age) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the average rank of winners in all matches.\n[SQL]:\n", "output": "SELECT avg(winner_rank) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the average rank for winners in all matches?\n[SQL]:\n", "output": "SELECT avg(winner_rank) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the highest rank of losers in all matches.\n[SQL]:\n", "output": "SELECT min(loser_rank) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the best rank of losers across all matches?\n[SQL]:\n", "output": "SELECT min(loser_rank) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the number of distinct country codes of all players.\n[SQL]:\n", "output": "SELECT count(DISTINCT country_code) FROM players"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many distinct countries do players come from?\n[SQL]:\n", "output": "SELECT count(DISTINCT country_code) FROM players"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of distinct name of losers.\n[SQL]:\n", "output": "SELECT count(DISTINCT loser_name) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many different loser names are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT loser_name) FROM matches"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name of tourney that has more than 10 matches.\n[SQL]:\n", "output": "SELECT tourney_name FROM matches GROUP BY tourney_name HAVING count(*) > 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names of tournaments that have more than 10 matches?\n[SQL]:\n", "output": "SELECT tourney_name FROM matches GROUP BY tourney_name HAVING count(*) > 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the names of all winners who played in both 2013 and 2016.\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE YEAR = 2013 INTERSECT SELECT winner_name FROM matches WHERE YEAR = 2016"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names of players who won in both 2013 and 2016?\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE YEAR = 2013 INTERSECT SELECT winner_name FROM matches WHERE YEAR = 2016"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the number of all matches who played in years of 2013 or 2016.\n[SQL]:\n", "output": "SELECT count(*) FROM matches WHERE YEAR = 2013 OR YEAR = 2016"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many matches were played in 2013 or 2016?\n[SQL]:\n", "output": "SELECT count(*) FROM matches WHERE YEAR = 2013 OR YEAR = 2016"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the country code and first name of the players who won in both tourney WTA Championships and Australian Open?\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'WTA Championships' INTERSECT SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'Australian Open'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names and country codes for players who won both the WTA Championships and the Australian Open?\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'WTA Championships' INTERSECT SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'Australian Open'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the first name and country code of the oldest player.\n[SQL]:\n", "output": "SELECT first_name , country_code FROM players ORDER BY birth_date LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the first name and country code of the oldest player?\n[SQL]:\n", "output": "SELECT first_name , country_code FROM players ORDER BY birth_date LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the first and last name of all players in the order of birth date.\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players ORDER BY birth_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the full names of all players, sorted by birth date?\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players ORDER BY birth_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the first and last name of all players who are left / L hand in the order of birth date.\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players WHERE hand = 'L' ORDER BY birth_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the full names of all left handed players, in order of birth date?\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players WHERE hand = 'L' ORDER BY birth_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the first name and country code of the player who did the most number of tours.\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id ORDER BY T2.tours DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the first name and country code of the player with the most tours?\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id ORDER BY T2.tours DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the year that has the most number of matches.\n[SQL]:\n", "output": "SELECT YEAR FROM matches GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Which year had the most matches?\n[SQL]:\n", "output": "SELECT YEAR FROM matches GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name and rank points of the winner who won the most times.\n[SQL]:\n", "output": "SELECT winner_name , winner_rank_points FROM matches GROUP BY winner_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the name of the winner who has won the most matches, and how many rank points does this player have?\n[SQL]:\n", "output": "SELECT winner_name , winner_rank_points FROM matches GROUP BY winner_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name of the winner who has the highest rank points and participated in the Australian Open tourney.\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE tourney_name = 'Australian Open' ORDER BY winner_rank_points DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the name of the winner with the most rank points who participated in the Australian Open tournament?\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE tourney_name = 'Australian Open' ORDER BY winner_rank_points DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the names of loser and winner who played in the match with greatest number of minutes.\n[SQL]:\n", "output": "SELECT winner_name , loser_name FROM matches ORDER BY minutes DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names of the winner and loser who played in the longest match?\n[SQL]:\n", "output": "SELECT winner_name , loser_name FROM matches ORDER BY minutes DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the average ranking for each player and their first name.\n[SQL]:\n", "output": "SELECT avg(ranking) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names of all players, and their average rankings?\n[SQL]:\n", "output": "SELECT avg(ranking) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total ranking points for each player and their first name.\n[SQL]:\n", "output": "SELECT sum(ranking_points) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names of all players, and their total ranking points?\n[SQL]:\n", "output": "SELECT sum(ranking_points) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the number of players for each country.\n[SQL]:\n", "output": "SELECT count(*) , country_code FROM players GROUP BY country_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many players are from each country?\n[SQL]:\n", "output": "SELECT count(*) , country_code FROM players GROUP BY country_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the code of the country where has the greatest number of players.\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the code of the country with the most players?\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the codes of countries that have more than 50 players.\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code HAVING count(*) > 50"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the codes of countries with more than 50 players?\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code HAVING count(*) > 50"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total number of tours for each ranking date.\n[SQL]:\n", "output": "SELECT sum(tours) , ranking_date FROM rankings GROUP BY ranking_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many total tours were there for each ranking date?\n[SQL]:\n", "output": "SELECT sum(tours) , ranking_date FROM rankings GROUP BY ranking_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of matches happened in each year.\n[SQL]:\n", "output": "SELECT count(*) , YEAR FROM matches GROUP BY YEAR"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many matches were played in each year?\n[SQL]:\n", "output": "SELECT count(*) , YEAR FROM matches GROUP BY YEAR"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name and rank of the 3 youngest winners across all matches.\n[SQL]:\n", "output": "SELECT DISTINCT winner_name , winner_rank FROM matches ORDER BY winner_age LIMIT 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names and ranks of the three youngest winners across all matches?\n[SQL]:\n", "output": "SELECT DISTINCT winner_name , winner_rank FROM matches ORDER BY winner_age LIMIT 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many different winners both participated in the WTA Championships and were left handed?\n[SQL]:\n", "output": "SELECT count(DISTINCT winner_name) FROM matches WHERE tourney_name = 'WTA Championships' AND winner_hand = 'L'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of left handed winners who participated in the WTA Championships.\n[SQL]:\n", "output": "SELECT count(DISTINCT winner_name) FROM matches WHERE tourney_name = 'WTA Championships' AND winner_hand = 'L'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the first name, country code and birth date of the winner who has the highest rank points in all matches.\n[SQL]:\n", "output": "SELECT T1.first_name , T1.country_code , T1.birth_date FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id ORDER BY T2.winner_rank_points DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the first name, country code, and birth date of the player with the most winner rank points across all matches?\n[SQL]:\n", "output": "SELECT T1.first_name , T1.country_code , T1.birth_date FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id ORDER BY T2.winner_rank_points DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of players for each hand type.\n[SQL]:\n", "output": "SELECT count(*) , hand FROM players GROUP BY hand"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many players are there for each hand type?\n[SQL]:\n", "output": "SELECT count(*) , hand FROM players GROUP BY hand"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:How many ships ended up being 'Captured'?\n[SQL]:\n", "output": "SELECT count(*) FROM ship WHERE disposition_of_ship = 'Captured'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:List the name and tonnage ordered by in descending alphaetical order for the names.\n[SQL]:\n", "output": "SELECT name , tonnage FROM ship ORDER BY name DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:List the name, date and result of each battle.\n[SQL]:\n", "output": "SELECT name , date FROM battle"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What is maximum and minimum death toll caused each time?\n[SQL]:\n", "output": "SELECT max(killed) , min(killed) FROM death"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What is the average number of injuries caused each time?\n[SQL]:\n", "output": "SELECT avg(injured) FROM death"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the death and injury situations caused by the ship with tonnage 't'?\n[SQL]:\n", "output": "SELECT T1.killed , T1.injured FROM death AS T1 JOIN ship AS t2 ON T1.caused_by_ship_id = T2.id WHERE T2.tonnage = 't'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the name and results of the battles when the bulgarian commander is not 'Boril'\n[SQL]:\n", "output": "SELECT name , RESULT FROM battle WHERE bulgarian_commander != 'Boril'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the different ids and names of the battles that lost any 'Brig' type shipes?\n[SQL]:\n", "output": "SELECT DISTINCT T1.id , T1.name FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.ship_type = 'Brig'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the ids and names of the battles that led to more than 10 people killed in total.\n[SQL]:\n", "output": "SELECT T1.id , T1.name FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle JOIN death AS T3 ON T2.id = T3.caused_by_ship_id GROUP BY T1.id HAVING sum(T3.killed) > 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What is the ship id and name that caused most total injuries?\n[SQL]:\n", "output": "SELECT T2.id , T2.name FROM death AS T1 JOIN ship AS t2 ON T1.caused_by_ship_id = T2.id GROUP BY T2.id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the distinct battle names which are between bulgarian commander 'Kaloyan' and latin commander 'Baldwin I'?\n[SQL]:\n", "output": "SELECT name FROM battle WHERE bulgarian_commander = 'Kaloyan' AND latin_commander = 'Baldwin I'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:How many different results are there for the battles?\n[SQL]:\n", "output": "SELECT count(DISTINCT RESULT) FROM battle"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:How many battles did not lose any ship with tonnage '225'?\n[SQL]:\n", "output": "SELECT count(*) FROM battle WHERE id NOT IN ( SELECT lost_in_battle FROM ship WHERE tonnage = '225' );"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:List the name and date the battle that has lost the ship named 'Lettice' and the ship named 'HMS Atalanta'\n[SQL]:\n", "output": "SELECT T1.name , T1.date FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.name = 'Lettice' INTERSECT SELECT T1.name , T1.date FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.name = 'HMS Atalanta'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:Show names, results and bulgarian commanders of the battles with no ships lost in the 'English Channel'.\n[SQL]:\n", "output": "SELECT name , RESULT , bulgarian_commander FROM battle EXCEPT SELECT T1.name , T1.result , T1.bulgarian_commander FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.location = 'English Channel'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the notes of the death events which has substring 'East'?\n[SQL]:\n", "output": "SELECT note FROM death WHERE note LIKE '%East%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:what are all the addresses including line 1 and line 2?\n[SQL]:\n", "output": "SELECT line_1 , line_2 FROM addresses"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first and second line for all addresses?\n[SQL]:\n", "output": "SELECT line_1 , line_2 FROM addresses"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many courses in total are listed?\n[SQL]:\n", "output": "SELECT count(*) FROM Courses"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many courses are there?\n[SQL]:\n", "output": "SELECT count(*) FROM Courses"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How is the math course described?\n[SQL]:\n", "output": "SELECT course_description FROM Courses WHERE course_name = 'math'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the descriptions for all the math courses?\n[SQL]:\n", "output": "SELECT course_description FROM Courses WHERE course_name = 'math'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the zip code of the address in the city Port Chelsea?\n[SQL]:\n", "output": "SELECT zip_postcode FROM Addresses WHERE city = 'Port Chelsea'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the zip code for Port Chelsea?\n[SQL]:\n", "output": "SELECT zip_postcode FROM Addresses WHERE city = 'Port Chelsea'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which department offers the most number of degrees? List department name and id.\n[SQL]:\n", "output": "SELECT T2.department_name , T1.department_id FROM Degree_Programs AS T1 JOIN Departments AS T2 ON T1.department_id = T2.department_id GROUP BY T1.department_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the name and id of the department with the most number of degrees ?\n[SQL]:\n", "output": "select t2.department_name , t1.department_id from degree_programs as t1 join departments as t2 on t1.department_id = t2.department_id group by t1.department_id order by count(*) desc limit 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many departments offer any degree?\n[SQL]:\n", "output": "SELECT count(DISTINCT department_id) FROM Degree_Programs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different departments offer degrees?\n[SQL]:\n", "output": "SELECT count(DISTINCT department_id) FROM Degree_Programs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different degree names are offered?\n[SQL]:\n", "output": "SELECT count(DISTINCT degree_summary_name) FROM Degree_Programs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different degrees are offered?\n[SQL]:\n", "output": "SELECT count(DISTINCT degree_summary_name) FROM Degree_Programs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many degrees does the engineering department offer?\n[SQL]:\n", "output": "SELECT count(*) FROM Departments AS T1 JOIN Degree_Programs AS T2 ON T1.department_id = T2.department_id WHERE T1.department_name = 'engineer'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many degrees does the engineering department have?\n[SQL]:\n", "output": "SELECT count(*) FROM Departments AS T1 JOIN Degree_Programs AS T2 ON T1.department_id = T2.department_id WHERE T1.department_name = 'engineer'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and descriptions of all the sections?\n[SQL]:\n", "output": "SELECT section_name , section_description FROM Sections"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and descriptions for all the sections?\n[SQL]:\n", "output": "SELECT section_name , section_description FROM Sections"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and id of courses having at most 2 sections?\n[SQL]:\n", "output": "SELECT T1.course_name , T1.course_id FROM Courses AS T1 JOIN Sections AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_id HAVING count(*) <= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and ids of every course with less than 2 sections?\n[SQL]:\n", "output": "SELECT T1.course_name , T1.course_id FROM Courses AS T1 JOIN Sections AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_id HAVING count(*) <= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:List the section_name in reversed lexicographical order.\n[SQL]:\n", "output": "SELECT section_name FROM Sections ORDER BY section_name DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names of the sections in reverse alphabetical order?\n[SQL]:\n", "output": "SELECT section_name FROM Sections ORDER BY section_name DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the semester which most student registered in? Show both the name and the id.\n[SQL]:\n", "output": "SELECT T1.semester_name , T1.semester_id FROM Semesters AS T1 JOIN Student_Enrolment AS T2 ON T1.semester_id = T2.semester_id GROUP BY T1.semester_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:For each semester, what is the name and id of the one with the most students registered?\n[SQL]:\n", "output": "SELECT T1.semester_name , T1.semester_id FROM Semesters AS T1 JOIN Student_Enrolment AS T2 ON T1.semester_id = T2.semester_id GROUP BY T1.semester_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the description of the department whose name has the substring the computer?\n[SQL]:\n", "output": "SELECT department_description FROM Departments WHERE department_name LIKE '%computer%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the department description for the one whose name has the word computer?\n[SQL]:\n", "output": "SELECT department_description FROM Departments WHERE department_name LIKE '%computer%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who are enrolled in 2 degree programs in one semester? List the first name, middle name and last name and the id.\n[SQL]:\n", "output": "SELECT T1.first_name , T1.middle_name , T1.last_name , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id HAVING count(*) = 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the first, middle, and last names, along with the ids, of all students who enrolled in 2 degree programs in one semester?\n[SQL]:\n", "output": "SELECT T1.first_name , T1.middle_name , T1.last_name , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id HAVING count(*) = 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who is enrolled in a Bachelor degree program? List the first name, middle name, last name.\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.middle_name , T1.last_name FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id JOIN Degree_Programs AS T3 ON T2.degree_program_id = T3.degree_program_id WHERE T3.degree_summary_name = 'Bachelor'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the first, middle, and last names for everybody enrolled in a Bachelors program?\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.middle_name , T1.last_name FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id JOIN Degree_Programs AS T3 ON T2.degree_program_id = T3.degree_program_id WHERE T3.degree_summary_name = 'Bachelor'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the kind of program which most number of students are enrolled in?\n[SQL]:\n", "output": "SELECT T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_summary_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the degree summary name that has the most number of students enrolled?\n[SQL]:\n", "output": "SELECT T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_summary_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the program which most number of students are enrolled in. List both the id and the summary.\n[SQL]:\n", "output": "SELECT T1.degree_program_id , T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_program_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the program id and the summary of the degree that has the most students enrolled?\n[SQL]:\n", "output": "SELECT T1.degree_program_id , T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_program_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which student has enrolled for the most times in any program? List the id, first name, middle name, last name, the number of enrollments and student id.\n[SQL]:\n", "output": "SELECT T1.student_id , T1.first_name , T1.middle_name , T1.last_name , count(*) , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first, middle, and last name, along with the id and number of enrollments, for the student who enrolled the most in any program?\n[SQL]:\n", "output": "SELECT T1.student_id , T1.first_name , T1.middle_name , T1.last_name , count(*) , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which semesters do not have any student enrolled? List the semester name.\n[SQL]:\n", "output": "SELECT semester_name FROM Semesters WHERE semester_id NOT IN( SELECT semester_id FROM Student_Enrolment )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the name of the semester with no students enrolled?\n[SQL]:\n", "output": "SELECT semester_name FROM Semesters WHERE semester_id NOT IN( SELECT semester_id FROM Student_Enrolment )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are all the course names of the courses which ever have students enrolled in?\n[SQL]:\n", "output": "SELECT DISTINCT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names of all courses that have some students enrolled?\n[SQL]:\n", "output": "SELECT DISTINCT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What's the name of the course with most number of enrollments?\n[SQL]:\n", "output": "SELECT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the name of the course with the most students enrolled?\n[SQL]:\n", "output": "SELECT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the last name of the students who currently live in the state of North Carolina but have not registered in any degree program.\n[SQL]:\n", "output": "SELECT T1.last_name FROM Students AS T1 JOIN Addresses AS T2 ON T1.current_address_id = T2.address_id WHERE T2.state_province_county = 'NorthCarolina' EXCEPT SELECT DISTINCT T3.last_name FROM Students AS T3 JOIN Student_Enrolment AS T4 ON T3.student_id = T4.student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the last name of the students who live in North Carolina but have not registered in any degree programs?\n[SQL]:\n", "output": "SELECT T1.last_name FROM Students AS T1 JOIN Addresses AS T2 ON T1.current_address_id = T2.address_id WHERE T2.state_province_county = 'NorthCarolina' EXCEPT SELECT DISTINCT T3.last_name FROM Students AS T3 JOIN Student_Enrolment AS T4 ON T3.student_id = T4.student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Show the date and id of the transcript with at least 2 course results.\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the date and id of the transcript with at least 2 courses listed?\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the phone number of the man with the first name Timmothy and the last name Ward?\n[SQL]:\n", "output": "SELECT cell_mobile_number FROM Students WHERE first_name = 'Timmothy' AND last_name = 'Ward'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the mobile phone number of the student named Timmothy Ward ?\n[SQL]:\n", "output": "select cell_mobile_number from students where first_name = 'timmothy' and last_name = 'ward'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who is the first student to register? List the first name, middle name and last name.\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_first_registered ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first, middle, and last name of the first student to register?\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_first_registered ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who is the earliest graduate of the school? List the first name, middle name and last name.\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_left ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first, middle, and last name of the earliest school graduate?\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_left ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Whose permanent address is different from his or her current address? List his or her first name.\n[SQL]:\n", "output": "SELECT first_name FROM Students WHERE current_address_id != permanent_address_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first name of the student whose permanent address is different from his or her current one?\n[SQL]:\n", "output": "SELECT first_name FROM Students WHERE current_address_id != permanent_address_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which address holds the most number of students currently? List the address id and all lines.\n[SQL]:\n", "output": "SELECT T1.address_id , T1.line_1 , T1.line_2 FROM Addresses AS T1 JOIN Students AS T2 ON T1.address_id = T2.current_address_id GROUP BY T1.address_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the id, line 1, and line 2 of the address with the most students?\n[SQL]:\n", "output": "SELECT T1.address_id , T1.line_1 , T1.line_2 FROM Addresses AS T1 JOIN Students AS T2 ON T1.address_id = T2.current_address_id GROUP BY T1.address_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:On average, when were the transcripts printed?\n[SQL]:\n", "output": "SELECT avg(transcript_date) FROM Transcripts"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the average transcript date?\n[SQL]:\n", "output": "SELECT avg(transcript_date) FROM Transcripts"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:When is the first transcript released? List the date and details.\n[SQL]:\n", "output": "SELECT transcript_date , other_details FROM Transcripts ORDER BY transcript_date ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the earliest date of a transcript release, and what details can you tell me?\n[SQL]:\n", "output": "SELECT transcript_date , other_details FROM Transcripts ORDER BY transcript_date ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many transcripts are released?\n[SQL]:\n", "output": "SELECT count(*) FROM Transcripts"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many transcripts are listed?\n[SQL]:\n", "output": "SELECT count(*) FROM Transcripts"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the last transcript release date?\n[SQL]:\n", "output": "SELECT transcript_date FROM Transcripts ORDER BY transcript_date DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:When was the last transcript released?\n[SQL]:\n", "output": "SELECT transcript_date FROM Transcripts ORDER BY transcript_date DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many times at most can a course enrollment result show in different transcripts? Also show the course enrollment id.\n[SQL]:\n", "output": "SELECT count(*) , student_course_id FROM Transcript_Contents GROUP BY student_course_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the maximum number of times that a course shows up in different transcripts and what is that course's enrollment id?\n[SQL]:\n", "output": "SELECT count(*) , student_course_id FROM Transcript_Contents GROUP BY student_course_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Show the date of the transcript which shows the least number of results, also list the id.\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id ORDER BY count(*) ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the date and id of the transcript with the least number of results?\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id ORDER BY count(*) ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the semester when both Master students and Bachelor students got enrolled in.\n[SQL]:\n", "output": "SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Master' INTERSECT SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Bachelor'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the id of the semester that had both Masters and Bachelors students enrolled?\n[SQL]:\n", "output": "SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Master' INTERSECT SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Bachelor'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different addresses do the students currently live?\n[SQL]:\n", "output": "SELECT count(DISTINCT current_address_id) FROM Students"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the different addresses that have students living there?\n[SQL]:\n", "output": "SELECT count(DISTINCT current_address_id) FROM Students"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:List all the student details in reversed lexicographical order.\n[SQL]:\n", "output": "SELECT other_student_details FROM Students ORDER BY other_student_details DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What other details can you tell me about students in reverse alphabetical order?\n[SQL]:\n", "output": "SELECT other_student_details FROM Students ORDER BY other_student_details DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Describe the section h.\n[SQL]:\n", "output": "SELECT section_description FROM Sections WHERE section_name = 'h'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the description for the section named h?\n[SQL]:\n", "output": "SELECT section_description FROM Sections WHERE section_name = 'h'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the first name of the students who permanently live in the country Haiti or have the cell phone number 09700166582 .\n[SQL]:\n", "output": "select t1.first_name from students as t1 join addresses as t2 on t1.permanent_address_id = t2.address_id where t2.country = 'haiti' or t1.cell_mobile_number = '09700166582'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the first names of the students who live in Haiti permanently or have the cell phone number 09700166582 ?\n[SQL]:\n", "output": "select t1.first_name from students as t1 join addresses as t2 on t1.permanent_address_id = t2.address_id where t2.country = 'haiti' or t1.cell_mobile_number = '09700166582'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the title of all cartoons in alphabetical order.\n[SQL]:\n", "output": "SELECT Title FROM Cartoon ORDER BY title"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the titles of the cartoons sorted alphabetically?\n[SQL]:\n", "output": "SELECT Title FROM Cartoon ORDER BY title"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List all cartoon directed by \"Ben Jones\".\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the names of all cartoons directed by Ben Jones?\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many cartoons were written by \"Joseph Kuhr\"?\n[SQL]:\n", "output": "SELECT count(*) FROM Cartoon WHERE Written_by = \"Joseph Kuhr\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the number of cartoones written by Joseph Kuhr?\n[SQL]:\n", "output": "SELECT count(*) FROM Cartoon WHERE Written_by = \"Joseph Kuhr\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:list all cartoon titles and their directors ordered by their air date\n[SQL]:\n", "output": "SELECT title , Directed_by FROM Cartoon ORDER BY Original_air_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the name and directors of all the cartoons that are ordered by air date?\n[SQL]:\n", "output": "SELECT title , Directed_by FROM Cartoon ORDER BY Original_air_date"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the title of all cartoon directed by \"Ben Jones\" or \"Brandon Vietti\".\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\" OR Directed_by = \"Brandon Vietti\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the titles of all cartoons directed by Ben Jones or Brandon Vietti?\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\" OR Directed_by = \"Brandon Vietti\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Which country has the most of TV Channels? List the country and number of TV Channels it has.\n[SQL]:\n", "output": "SELECT Country , count(*) FROM TV_Channel GROUP BY Country ORDER BY count(*) DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the country with the most number of TV Channels and how many does it have?\n[SQL]:\n", "output": "SELECT Country , count(*) FROM TV_Channel GROUP BY Country ORDER BY count(*) DESC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the number of different series names and contents in the TV Channel table.\n[SQL]:\n", "output": "SELECT count(DISTINCT series_name) , count(DISTINCT content) FROM TV_Channel;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many different series and contents are listed in the TV Channel table?\n[SQL]:\n", "output": "SELECT count(DISTINCT series_name) , count(DISTINCT content) FROM TV_Channel;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the content of TV Channel with serial name \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT Content FROM TV_Channel WHERE series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the content of the series Sky Radio?\n[SQL]:\n", "output": "SELECT Content FROM TV_Channel WHERE series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the Package Option of TV Channel with serial name \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT Package_Option FROM TV_Channel WHERE series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the Package Options of the TV Channels whose series names are Sky Radio?\n[SQL]:\n", "output": "SELECT Package_Option FROM TV_Channel WHERE series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many TV Channel using language English?\n[SQL]:\n", "output": "SELECT count(*) FROM TV_Channel WHERE LANGUAGE = \"English\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many TV Channels use the English language?\n[SQL]:\n", "output": "SELECT count(*) FROM TV_Channel WHERE LANGUAGE = \"English\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the language used least number of TV Channel. List language and number of TV Channel.\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE ORDER BY count(*) ASC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the languages used by the least number of TV Channels and how many channels use it?\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE ORDER BY count(*) ASC LIMIT 1;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List each language and the number of TV Channels using it.\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:For each language, list the number of TV Channels that use it.\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the TV Channel that shows the cartoon \"The Rise of the Blue Beetle!\"? List the TV Channel's series name.\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T2.Title = \"The Rise of the Blue Beetle!\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the series name of the TV Channel that shows the cartoon \"The Rise of the Blue Beetle\"?\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T2.Title = \"The Rise of the Blue Beetle!\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the title of all Cartoons showed on TV Channel with series name \"Sky Radio\".\n[SQL]:\n", "output": "SELECT T2.Title FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the title of all the cartools that are on the TV Channel with the series name \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT T2.Title FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the Episode of all TV series sorted by rating.\n[SQL]:\n", "output": "SELECT Episode FROM TV_series ORDER BY rating"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are all of the episodes ordered by ratings?\n[SQL]:\n", "output": "SELECT Episode FROM TV_series ORDER BY rating"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List top 3 highest Rating TV series. List the TV series's Episode and Rating.\n[SQL]:\n", "output": "SELECT Episode , Rating FROM TV_series ORDER BY Rating DESC LIMIT 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are 3 most highly rated episodes in the TV series table and what were those ratings?\n[SQL]:\n", "output": "SELECT Episode , Rating FROM TV_series ORDER BY Rating DESC LIMIT 3;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is minimum and maximum share of TV series?\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM TV_series;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the maximum and minimum share for the TV series?\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM TV_series;"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the air date of TV series with Episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT Air_Date FROM TV_series WHERE Episode = \"A Love of a Lifetime\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:When did the episode \"A Love of a Lifetime\" air?\n[SQL]:\n", "output": "SELECT Air_Date FROM TV_series WHERE Episode = \"A Love of a Lifetime\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is Weekly Rank of TV series with Episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT Weekly_Rank FROM TV_series WHERE Episode = \"A Love of a Lifetime\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the weekly rank for the episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT Weekly_Rank FROM TV_series WHERE Episode = \"A Love of a Lifetime\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the TV Channel of TV series with Episode \"A Love of a Lifetime\"? List the TV Channel's series name.\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T2.Episode = \"A Love of a Lifetime\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the name of the series that has the episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T2.Episode = \"A Love of a Lifetime\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the Episode of all TV series showed on TV Channel with series name \"Sky Radio\".\n[SQL]:\n", "output": "SELECT T2.Episode FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the episode for the TV series named \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT T2.Episode FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the number of cartoons directed by each of the listed directors.\n[SQL]:\n", "output": "SELECT count(*) , Directed_by FROM cartoon GROUP BY Directed_by"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many cartoons did each director create?\n[SQL]:\n", "output": "SELECT count(*) , Directed_by FROM cartoon GROUP BY Directed_by"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the production code and channel of the most recently aired cartoon .\n[SQL]:\n", "output": "select production_code , channel from cartoon order by original_air_date desc limit 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the produdction code and channel of the most recent cartoon ?\n[SQL]:\n", "output": "select production_code , channel from cartoon order by original_air_date desc limit 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the package choice and series name of the TV channel that has high definition TV.\n[SQL]:\n", "output": "SELECT package_option , series_name FROM TV_Channel WHERE hight_definition_TV = \"yes\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the package options and the name of the series for the TV Channel that supports high definition TV?\n[SQL]:\n", "output": "SELECT package_option , series_name FROM TV_Channel WHERE hight_definition_TV = \"yes\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:which countries' tv channels are playing some cartoon written by Todd Casey?\n[SQL]:\n", "output": "SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the countries that have cartoons on TV that were written by Todd Casey?\n[SQL]:\n", "output": "SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:which countries' tv channels are not playing any cartoon written by Todd Casey?\n[SQL]:\n", "output": "SELECT country FROM TV_Channel EXCEPT SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the countries that are not playing cartoons written by Todd Casey?\n[SQL]:\n", "output": "SELECT country FROM TV_Channel EXCEPT SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the series name and country of the tv channel that is playing some cartoons directed by Ben Jones and Michael Chang?\n[SQL]:\n", "output": "SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Michael Chang' INTERSECT SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Ben Jones'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the series name and country of all TV channels that are playing cartoons directed by Ben Jones and cartoons directed by Michael Chang?\n[SQL]:\n", "output": "SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Michael Chang' INTERSECT SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Ben Jones'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find the pixel aspect ratio and nation of the tv channels that do not use English.\n[SQL]:\n", "output": "SELECT Pixel_aspect_ratio_PAR , country FROM tv_channel WHERE LANGUAGE != 'English'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the pixel aspect ratio and country of origin for all TV channels that do not use English?\n[SQL]:\n", "output": "SELECT Pixel_aspect_ratio_PAR , country FROM tv_channel WHERE LANGUAGE != 'English'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find id of the tv channels that from the countries where have more than two tv channels.\n[SQL]:\n", "output": "SELECT id FROM tv_channel GROUP BY country HAVING count(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the ids of all tv channels that have more than 2 TV channels?\n[SQL]:\n", "output": "SELECT id FROM tv_channel GROUP BY country HAVING count(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find the id of tv channels that do not play any cartoon directed by Ben Jones.\n[SQL]:\n", "output": "SELECT id FROM TV_Channel EXCEPT SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the ids of the TV channels that do not have any cartoons directed by Ben Jones?\n[SQL]:\n", "output": "SELECT id FROM TV_Channel EXCEPT SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find the package option of the tv channel that do not have any cartoon directed by Ben Jones.\n[SQL]:\n", "output": "SELECT package_option FROM TV_Channel WHERE id NOT IN (SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the package options of all tv channels that are not playing any cartoons directed by Ben Jones?\n[SQL]:\n", "output": "SELECT package_option FROM TV_Channel WHERE id NOT IN (SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:How many poker players are there?\n[SQL]:\n", "output": "SELECT count(*) FROM poker_player"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Count the number of poker players.\n[SQL]:\n", "output": "SELECT count(*) FROM poker_player"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the earnings of poker players in descending order.\n[SQL]:\n", "output": "SELECT Earnings FROM poker_player ORDER BY Earnings DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the earnings of poker players, ordered descending by value?\n[SQL]:\n", "output": "SELECT Earnings FROM poker_player ORDER BY Earnings DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the final tables made and the best finishes of poker players.\n[SQL]:\n", "output": "SELECT Final_Table_Made , Best_Finish FROM poker_player"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the final tables made and best finishes for all poker players?\n[SQL]:\n", "output": "SELECT Final_Table_Made , Best_Finish FROM poker_player"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the average earnings of poker players?\n[SQL]:\n", "output": "SELECT avg(Earnings) FROM poker_player"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the average earnings across all poker players.\n[SQL]:\n", "output": "SELECT avg(Earnings) FROM poker_player"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the money rank of the poker player with the highest earnings?\n[SQL]:\n", "output": "SELECT Money_Rank FROM poker_player ORDER BY Earnings DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the money rank of the player with the greatest earnings.\n[SQL]:\n", "output": "SELECT Money_Rank FROM poker_player ORDER BY Earnings DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the maximum number of final tables made among poker players with earnings less than 200000?\n[SQL]:\n", "output": "SELECT max(Final_Table_Made) FROM poker_player WHERE Earnings < 200000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the maximum final tables made across all poker players who have earnings below 200000.\n[SQL]:\n", "output": "SELECT max(Final_Table_Made) FROM poker_player WHERE Earnings < 200000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the names of all the poker players.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players whose earnings is higher than 300000?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T2.Earnings > 300000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Give the names of poker players who have earnings above 300000.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T2.Earnings > 300000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the names of poker players ordered by the final tables made in ascending order.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Final_Table_Made"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players, ordered ascending by the number of final tables they have made?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Final_Table_Made"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the birth date of the poker player with the lowest earnings?\n[SQL]:\n", "output": "SELECT T1.Birth_Date FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the birth date of the poker player with the lowest earnings.\n[SQL]:\n", "output": "SELECT T1.Birth_Date FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the money rank of the tallest poker player?\n[SQL]:\n", "output": "SELECT T2.Money_Rank FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Height DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the money rank of the poker player with the greatest height.\n[SQL]:\n", "output": "SELECT T2.Money_Rank FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Height DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the average earnings of poker players with height higher than 200?\n[SQL]:\n", "output": "SELECT avg(T2.Earnings) FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T1.Height > 200"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Give average earnings of poker players who are taller than 200.\n[SQL]:\n", "output": "SELECT avg(T2.Earnings) FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T1.Height > 200"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players in descending order of earnings?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the names of poker players sorted by their earnings descending.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are different nationalities of people and the corresponding number of people from each nation?\n[SQL]:\n", "output": "SELECT Nationality , COUNT(*) FROM people GROUP BY Nationality"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:How many people are there of each nationality?\n[SQL]:\n", "output": "SELECT Nationality , COUNT(*) FROM people GROUP BY Nationality"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the most common nationality of people?\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Give the nationality that is most common across all people.\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the nationalities that are shared by at least two people?\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality HAVING COUNT(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the nationalities for which there are two or more people.\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality HAVING COUNT(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the names and birth dates of people in ascending alphabetical order of name.\n[SQL]:\n", "output": "SELECT Name , Birth_Date FROM people ORDER BY Name ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names and birth dates of people, ordered by their names in alphabetical order?\n[SQL]:\n", "output": "SELECT Name , Birth_Date FROM people ORDER BY Name ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Show names of people whose nationality is not \"Russia\".\n[SQL]:\n", "output": "SELECT Name FROM people WHERE Nationality != \"Russia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of people who are not from Russia?\n[SQL]:\n", "output": "SELECT Name FROM people WHERE Nationality != \"Russia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the names of people that are not poker players.\n[SQL]:\n", "output": "SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM poker_player)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of people who do not play poker?\n[SQL]:\n", "output": "SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM poker_player)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:How many distinct nationalities are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM people"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Count the number of different nationalities.\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM people"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:How many states are there?\n[SQL]:\n", "output": "SELECT count(*) FROM area_code_state"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:List the contestant numbers and names, ordered by contestant name descending.\n[SQL]:\n", "output": "SELECT contestant_number , contestant_name FROM contestants ORDER BY contestant_name DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:List the vote ids, phone numbers and states of all votes.\n[SQL]:\n", "output": "SELECT vote_id , phone_number , state FROM votes"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the maximum and minimum values of area codes?\n[SQL]:\n", "output": "SELECT max(area_code) , min(area_code) FROM area_code_state"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What is last date created of votes from the state 'CA'?\n[SQL]:\n", "output": "SELECT max(created) FROM votes WHERE state = 'CA'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the names of the contestants whose names are not 'Jessie Alloway'\n[SQL]:\n", "output": "SELECT contestant_name FROM contestants WHERE contestant_name != 'Jessie Alloway'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the distinct states and create time of all votes?\n[SQL]:\n", "output": "SELECT DISTINCT state , created FROM votes"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the contestant numbers and names of the contestants who had at least two votes?\n[SQL]:\n", "output": "SELECT T1.contestant_number , T1.contestant_name FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number GROUP BY T1.contestant_number HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:Of all the contestants who got voted, what is the contestant number and name of the contestant who got least votes?\n[SQL]:\n", "output": "SELECT T1.contestant_number , T1.contestant_name FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number GROUP BY T1.contestant_number ORDER BY count(*) ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the number of votes from state 'NY' or 'CA'?\n[SQL]:\n", "output": "SELECT count(*) FROM votes WHERE state = 'NY' OR state = 'CA'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:How many contestants did not get voted?\n[SQL]:\n", "output": "SELECT count(*) FROM contestants WHERE contestant_number NOT IN ( SELECT contestant_number FROM votes )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What is the area code in which the most voters voted?\n[SQL]:\n", "output": "SELECT T1.area_code FROM area_code_state AS T1 JOIN votes AS T2 ON T1.state = T2.state GROUP BY T1.area_code ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the create dates, states, and phone numbers of the votes that were for the contestant named 'Tabatha Gehling'?\n[SQL]:\n", "output": "SELECT T2.created , T2.state , T2.phone_number FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number WHERE T1.contestant_name = 'Tabatha Gehling'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:List the area codes in which voters voted both for the contestant 'Tabatha Gehling' and the contestant 'Kelly Clauss'.\n[SQL]:\n", "output": "SELECT T3.area_code FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number JOIN area_code_state AS T3 ON T2.state = T3.state WHERE T1.contestant_name = 'Tabatha Gehling' INTERSECT SELECT T3.area_code FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number JOIN area_code_state AS T3 ON T2.state = T3.state WHERE T1.contestant_name = 'Kelly Clauss'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:Return the names of the contestants whose names contain the substring 'Al' .\n[SQL]:\n", "output": "select contestant_name from contestants where contestant_name like \"%al%\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of all the countries that became independent after 1950?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE IndepYear > 1950"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of the nations that were founded after 1950.\n[SQL]:\n", "output": "SELECT Name FROM country WHERE IndepYear > 1950"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many countries have a republic as their form of government?\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE GovernmentForm = \"Republic\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many countries have governments that are republics?\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE GovernmentForm = \"Republic\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total surface area of the countries in the Caribbean region?\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Region = \"Caribbean\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How much surface area do the countires in the Carribean cover together?\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Region = \"Caribbean\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which continent is Anguilla in?\n[SQL]:\n", "output": "SELECT Continent FROM country WHERE Name = \"Anguilla\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the continent name which Anguilla belongs to?\n[SQL]:\n", "output": "SELECT Continent FROM country WHERE Name = \"Anguilla\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which region is the city Kabul located in?\n[SQL]:\n", "output": "SELECT Region FROM country AS T1 JOIN city AS T2 ON T1.Code = T2.CountryCode WHERE T2.Name = \"Kabul\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What region is Kabul in?\n[SQL]:\n", "output": "SELECT Region FROM country AS T1 JOIN city AS T2 ON T1.Code = T2.CountryCode WHERE T2.Name = \"Kabul\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which language is the most popular in Aruba?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\" ORDER BY Percentage DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What language is predominantly spoken in Aruba?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\" ORDER BY Percentage DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the population and life expectancies in Brazil?\n[SQL]:\n", "output": "SELECT Population , LifeExpectancy FROM country WHERE Name = \"Brazil\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give me Brazil\u2019s population and life expectancies.\n[SQL]:\n", "output": "SELECT Population , LifeExpectancy FROM country WHERE Name = \"Brazil\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the region and population of Angola?\n[SQL]:\n", "output": "SELECT Population , Region FROM country WHERE Name = \"Angola\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What region does Angola belong to and what is its population?\n[SQL]:\n", "output": "SELECT Population , Region FROM country WHERE Name = \"Angola\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the average expected life expectancy for countries in the region of Central Africa?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Region = \"Central Africa\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How long is the people\u2019s average life expectancy in Central Africa?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Region = \"Central Africa\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the name of country that has the shortest life expectancy in Asia?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" ORDER BY LifeExpectancy LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name of the country in Asia with the lowest life expectancy.\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" ORDER BY LifeExpectancy LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total population and maximum GNP in Asia?\n[SQL]:\n", "output": "SELECT sum(Population) , max(GNP) FROM country WHERE Continent = \"Asia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many people live in Asia, and what is the largest GNP among them?\n[SQL]:\n", "output": "SELECT sum(Population) , max(GNP) FROM country WHERE Continent = \"Asia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the average life expectancy in African countries that are republics?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Continent = \"Africa\" AND GovernmentForm = \"Republic\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the average life expectancy for countries in Africa which are republics?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Continent = \"Africa\" AND GovernmentForm = \"Republic\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total surface area of the continents Asia and Europe?\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Continent = \"Asia\" OR Continent = \"Europe\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the total surface area covered by countries in Asia or Europe.\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Continent = \"Asia\" OR Continent = \"Europe\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many people live in Gelderland district?\n[SQL]:\n", "output": "SELECT sum(Population) FROM city WHERE District = \"Gelderland\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total population of Gelderland district?\n[SQL]:\n", "output": "SELECT sum(Population) FROM city WHERE District = \"Gelderland\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the average GNP and total population in all nations whose government is US territory?\n[SQL]:\n", "output": "SELECT avg(GNP) , sum(population) FROM country WHERE GovernmentForm = \"US Territory\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the mean GNP and total population of nations which are considered US territory.\n[SQL]:\n", "output": "SELECT avg(GNP) , sum(population) FROM country WHERE GovernmentForm = \"US Territory\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many unique languages are spoken in the world?\n[SQL]:\n", "output": "SELECT count(DISTINCT LANGUAGE) FROM countrylanguage"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the number of distinct languages used around the world?\n[SQL]:\n", "output": "SELECT count(DISTINCT LANGUAGE) FROM countrylanguage"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many type of governments are in Africa?\n[SQL]:\n", "output": "SELECT count(DISTINCT GovernmentForm) FROM country WHERE Continent = \"Africa\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many different forms of governments are there in Africa?\n[SQL]:\n", "output": "SELECT count(DISTINCT GovernmentForm) FROM country WHERE Continent = \"Africa\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of languages used in Aruba?\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many languages are spoken in Aruba?\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many official languages does Afghanistan have?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Afghanistan\" AND IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many official languages are spoken in Afghanistan?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Afghanistan\" AND IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is name of the country that speaks the largest number of languages?\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name of the nation that uses the greatest amount of languages.\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which continent has the most diverse languages?\n[SQL]:\n", "output": "SELECT T1.Continent FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Continent ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which continent speaks the most languages?\n[SQL]:\n", "output": "SELECT T1.Continent FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Continent ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many countries speak both English and Dutch?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the number of nations that use English and Dutch?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of nations speak both English and French?\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of nations that speak both English and French.\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of nations where both English and French are official languages?\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\" AND T2.IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of countries with English and French as official languages.\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\" AND T2.IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the number of distinct continents where Chinese is spoken?\n[SQL]:\n", "output": "SELECT COUNT( DISTINCT Continent) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Chinese\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many continents speak Chinese?\n[SQL]:\n", "output": "SELECT COUNT( DISTINCT Continent) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Chinese\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the regions that use English or Dutch?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Region FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" OR T2.Language = \"Dutch\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which regions speak Dutch or English?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Region FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" OR T2.Language = \"Dutch\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the countries where either English or Dutch is the official language ?\n[SQL]:\n", "output": "select t1.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode where t2.language = \"english\" and isofficial = \"t\" union select t1.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode where t2.language = \"dutch\" and isofficial = \"t\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which countries have either English or Dutch as an official language?\n[SQL]:\n", "output": "SELECT * FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND IsOfficial = \"T\" UNION SELECT * FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\" AND IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which language is the most popular on the Asian continent?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = \"Asia\" GROUP BY T2.Language ORDER BY COUNT (*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the language that is used by the largest number of Asian nations?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = \"Asia\" GROUP BY T2.Language ORDER BY COUNT (*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which languages are spoken by only one country in republic governments?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.GovernmentForm = \"Republic\" GROUP BY T2.Language HAVING COUNT(*) = 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What languages are only used by a single country with a republic government?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.GovernmentForm = \"Republic\" GROUP BY T2.Language HAVING COUNT(*) = 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the city with the largest population that uses English.\n[SQL]:\n", "output": "SELECT T1.Name , T1.Population FROM city AS T1 JOIN countrylanguage AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Language = \"English\" ORDER BY T1.Population DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the most populace city that speaks English?\n[SQL]:\n", "output": "SELECT T1.Name , T1.Population FROM city AS T1 JOIN countrylanguage AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Language = \"English\" ORDER BY T1.Population DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the name, population and expected life length of asian country with the largest area?\n[SQL]:\n", "output": "SELECT Name , Population , LifeExpectancy FROM country WHERE Continent = \"Asia\" ORDER BY SurfaceArea DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the name, population, and life expectancy of the largest Asian country by land?\n[SQL]:\n", "output": "SELECT Name , Population , LifeExpectancy FROM country WHERE Continent = \"Asia\" ORDER BY SurfaceArea DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is average life expectancy in the countries where English is not the official language?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the mean life expectancy of countries in which English is not the official language.\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of people living in the nations that do not use English?\n[SQL]:\n", "output": "SELECT sum(Population) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many people live in countries that do not speak English?\n[SQL]:\n", "output": "SELECT sum(Population) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the official language spoken in the country whose head of state is Beatrix?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.HeadOfState = \"Beatrix\" AND T2.IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the official language used in the country the name of whose head of state is Beatrix.\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.HeadOfState = \"Beatrix\" AND T2.IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of unique official languages spoken in the countries that are founded before 1930?\n[SQL]:\n", "output": "SELECT count(DISTINCT T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE IndepYear < 1930 AND T2.IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:For the countries founded before 1930, what is the total number of distinct official languages?\n[SQL]:\n", "output": "SELECT count(DISTINCT T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE IndepYear < 1930 AND T2.IsOfficial = \"T\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the countries that have greater surface area than any country in Europe?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE SurfaceArea > (SELECT min(SurfaceArea) FROM country WHERE Continent = \"Europe\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which countries have greater area than that of any country in Europe?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE SurfaceArea > (SELECT min(SurfaceArea) FROM country WHERE Continent = \"Europe\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the African countries that have a population less than any country in Asia?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Africa\" AND population < (SELECT max(population) FROM country WHERE Continent = \"Asia\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which African countries have a smaller population than that of any country in Asia?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Africa\" AND population < (SELECT min(population) FROM country WHERE Continent = \"Asia\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which Asian countries have a population that is larger than any country in Africa?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" AND population > (SELECT max(population) FROM country WHERE Continent = \"Africa\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the Asian countries which have a population larger than that of any country in Africa?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" AND population > (SELECT min(population) FROM country WHERE Continent = \"Africa\")"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the country codes for countries that do not speak English?\n[SQL]:\n", "output": "SELECT CountryCode FROM countrylanguage EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the country codes for countries that do not speak English.\n[SQL]:\n", "output": "SELECT CountryCode FROM countrylanguage EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the country codes of countries where people use languages other than English?\n[SQL]:\n", "output": "SELECT DISTINCT CountryCode FROM countrylanguage WHERE LANGUAGE != \"English\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the country codes for countries in which people speak langauges that are not English.\n[SQL]:\n", "output": "SELECT DISTINCT CountryCode FROM countrylanguage WHERE LANGUAGE != \"English\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the codes of the countries that do not speak English and whose government forms are not Republic?\n[SQL]:\n", "output": "SELECT Code FROM country WHERE GovernmentForm != \"Republic\" EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the codes of countries that do not speak English and do not have Republics for governments.\n[SQL]:\n", "output": "SELECT Code FROM country WHERE GovernmentForm != \"Republic\" EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which cities are in European countries where English is not the official language?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Name FROM country AS T1 JOIN city AS T2 ON T2.CountryCode = T1.Code WHERE T1.Continent = 'Europe' AND T1.Name NOT IN (SELECT T3.Name FROM country AS T3 JOIN countrylanguage AS T4 ON T3.Code = T4.CountryCode WHERE T4.IsOfficial = 'T' AND T4.Language = 'English')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of cities in Europe for which English is not the official language?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Name FROM country AS T1 JOIN city AS T2 ON T2.CountryCode = T1.Code WHERE T1.Continent = 'Europe' AND T1.Name NOT IN (SELECT T3.Name FROM country AS T3 JOIN countrylanguage AS T4 ON T3.Code = T4.CountryCode WHERE T4.IsOfficial = 'T' AND T4.Language = 'English')"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which unique cities are in Asian countries where Chinese is the official language ?\n[SQL]:\n", "output": "select distinct t3.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode join city as t3 on t1.code = t3.countrycode where t2.isofficial = 't' and t2.language = 'chinese' and t1.continent = \"asia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the different names of cities that are in Asia and for which Chinese is the official language.\n[SQL]:\n", "output": "SELECT DISTINCT T3.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode JOIN city AS T3 ON T1.Code = T3.CountryCode WHERE T2.IsOfficial = 'T' AND T2.Language = 'Chinese' AND T1.Continent = \"Asia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the name, independence year, and surface area of the country with the smallest population?\n[SQL]:\n", "output": "SELECT Name , SurfaceArea , IndepYear FROM country ORDER BY Population LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name, year of independence, and surface area of the country that has the lowest population.\n[SQL]:\n", "output": "SELECT Name , SurfaceArea , IndepYear FROM country ORDER BY Population LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the population, name and leader of the country with the largest area?\n[SQL]:\n", "output": "SELECT Name , population , HeadOfState FROM country ORDER BY SurfaceArea DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name, population, and head of state for the country that has the largest area.\n[SQL]:\n", "output": "SELECT Name , population , HeadOfState FROM country ORDER BY SurfaceArea DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the country name and the numbers of languages spoken for each country that speaks at least 3 languages.\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) , T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name HAVING COUNT(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of countries that speak more than 2 languages, as well as how many languages they speak?\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) , T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name HAVING COUNT(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the number of cities in each district whose population is greater than the average population of cities?\n[SQL]:\n", "output": "SELECT count(*) , District FROM city WHERE Population > (SELECT avg(Population) FROM city) GROUP BY District"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many cities in each district have a population that is above the average population across all cities?\n[SQL]:\n", "output": "SELECT count(*) , District FROM city WHERE Population > (SELECT avg(Population) FROM city) GROUP BY District"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the government form name and total population for each government form whose average life expectancy is longer than 72.\n[SQL]:\n", "output": "SELECT sum(Population) , GovernmentForm FROM country GROUP BY GovernmentForm HAVING avg(LifeExpectancy) > 72"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the different government forms and what is the total population of each for government forms that have an average life expectancy greater than 72?\n[SQL]:\n", "output": "SELECT sum(Population) , GovernmentForm FROM country GROUP BY GovernmentForm HAVING avg(LifeExpectancy) > 72"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the average life expectancy and total population for each continent where the average life expectancy is shorter than 72?\n[SQL]:\n", "output": "SELECT sum(Population) , avg(LifeExpectancy) , Continent FROM country GROUP BY Continent HAVING avg(LifeExpectancy) < 72"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the different continents and the total popuation and average life expectancy corresponding to each, for continents that have an average life expectancy less than 72?\n[SQL]:\n", "output": "SELECT sum(Population) , avg(LifeExpectancy) , Continent FROM country GROUP BY Continent HAVING avg(LifeExpectancy) < 72"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names and areas of countries with the top 5 largest area?\n[SQL]:\n", "output": "SELECT Name , SurfaceArea FROM country ORDER BY SurfaceArea DESC LIMIT 5"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names and surface areas of the 5 largest countries.\n[SQL]:\n", "output": "SELECT Name , SurfaceArea FROM country ORDER BY SurfaceArea DESC LIMIT 5"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are names of countries with the top 3 largest population?\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population DESC LIMIT 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names of the 3 most populated countries.\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population DESC LIMIT 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of the nations with the 3 lowest populations?\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population ASC LIMIT 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names of the 3 countries with the fewest people.\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population ASC LIMIT 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:how many countries are in Asia?\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE continent = \"Asia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Count the number of countries in Asia.\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE continent = \"Asia\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of the countries that are in the continent of Europe and have a population of 80000?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE continent = \"Europe\" AND Population = \"80000\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of countries that are in Europe and have a population equal to 80000.\n[SQL]:\n", "output": "SELECT Name FROM country WHERE continent = \"Europe\" AND Population = \"80000\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total population and average area of countries in the continent of North America whose area is bigger than 3000 ?\n[SQL]:\n", "output": "select sum(population) , avg(surfacearea) from country where continent = \"north america\" and surfacearea > 3000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the total population and average surface area corresponding to countries in North America that have a surface area greater than 3000 .\n[SQL]:\n", "output": "select sum(population) , avg(surfacearea) from country where continent = \"north america\" and surfacearea > 3000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the cities whose population is between 160000 and 900000?\n[SQL]:\n", "output": "SELECT name FROM city WHERE Population BETWEEN 160000 AND 900000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names of cities that have a population between 160000 and 900000 .\n[SQL]:\n", "output": "select name from city where population between 160000 and 900000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which language is spoken by the largest number of countries?\n[SQL]:\n", "output": "SELECT LANGUAGE FROM countrylanguage GROUP BY LANGUAGE ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the language that is spoken in the most countries.\n[SQL]:\n", "output": "SELECT LANGUAGE FROM countrylanguage GROUP BY LANGUAGE ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the language spoken by the largest percentage of people in each country?\n[SQL]:\n", "output": "SELECT LANGUAGE , CountryCode , max(Percentage) FROM countrylanguage GROUP BY CountryCode"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the country codes of the different countries, and what are the languages spoken by the greatest percentage of people for each?\n[SQL]:\n", "output": "SELECT LANGUAGE , CountryCode , max(Percentage) FROM countrylanguage GROUP BY CountryCode"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of countries where Spanish is spoken by the largest percentage of people?\n[SQL]:\n", "output": "SELECT count(*) , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Count the number of countries for which Spanish is the predominantly spoken language.\n[SQL]:\n", "output": "SELECT count(*) , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the codes of countries where Spanish is spoken by the largest percentage of people?\n[SQL]:\n", "output": "SELECT CountryCode , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the codes of countries for which Spanish is the predominantly spoken language.\n[SQL]:\n", "output": "SELECT CountryCode , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:How many conductors are there?\n[SQL]:\n", "output": "SELECT count(*) FROM conductor"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Count the number of conductors.\n[SQL]:\n", "output": "SELECT count(*) FROM conductor"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the names of conductors in ascending order of age.\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Age ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors, ordered by age?\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Age ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors whose nationalities are not \"USA\"?\n[SQL]:\n", "output": "SELECT Name FROM conductor WHERE Nationality != 'USA'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the names of conductors that do not have the nationality \"USA\".\n[SQL]:\n", "output": "SELECT Name FROM conductor WHERE Nationality != 'USA'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the record companies of orchestras in descending order of years in which they were founded?\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra ORDER BY Year_of_Founded DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the record companies of orchestras, sorted descending by the years in which they were founded.\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra ORDER BY Year_of_Founded DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the average attendance of shows?\n[SQL]:\n", "output": "SELECT avg(Attendance) FROM SHOW"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the average attendance across all shows.\n[SQL]:\n", "output": "SELECT avg(Attendance) FROM SHOW"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the maximum and minimum share of performances whose type is not \"Live final\".\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM performance WHERE TYPE != \"Live final\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the maximum and minimum shares for performances that do not have the type \"Live final\".\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM performance WHERE TYPE != \"Live final\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:How many different nationalities do conductors have?\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM conductor"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Count the number of different nationalities of conductors.\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM conductor"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List names of conductors in descending order of years of work.\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors, sorted descending by the number of years they have worked?\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the name of the conductor with the most years of work.\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the name of the conductor who has worked the greatest number of years?\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the names of conductors and the orchestras they have conducted.\n[SQL]:\n", "output": "SELECT T1.Name , T2.Orchestra FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors as well as the corresonding orchestras that they have conducted?\n[SQL]:\n", "output": "SELECT T1.Name , T2.Orchestra FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the names of conductors that have conducted more than one orchestras.\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID HAVING COUNT(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors who have conducted at more than one orchestra?\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID HAVING COUNT(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the name of the conductor that has conducted the most number of orchestras.\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the name of the conductor who has conducted the most orchestras?\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Please show the name of the conductor that has conducted orchestras founded after 2008.\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID WHERE Year_of_Founded > 2008"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors who have conducted orchestras founded after the year 2008?\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID WHERE Year_of_Founded > 2008"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Please show the different record companies and the corresponding number of orchestras.\n[SQL]:\n", "output": "SELECT Record_Company , COUNT(*) FROM orchestra GROUP BY Record_Company"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:How many orchestras does each record company manage?\n[SQL]:\n", "output": "SELECT Record_Company , COUNT(*) FROM orchestra GROUP BY Record_Company"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Please show the record formats of orchestras in ascending order of count.\n[SQL]:\n", "output": "SELECT Major_Record_Format FROM orchestra GROUP BY Major_Record_Format ORDER BY COUNT(*) ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the major record formats of orchestras, sorted by their frequency?\n[SQL]:\n", "output": "SELECT Major_Record_Format FROM orchestra GROUP BY Major_Record_Format ORDER BY COUNT(*) ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the record company shared by the most number of orchestras.\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra GROUP BY Record_Company ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the record company used by the greatest number of orchestras?\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra GROUP BY Record_Company ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the names of orchestras that have no performance.\n[SQL]:\n", "output": "SELECT Orchestra FROM orchestra WHERE Orchestra_ID NOT IN (SELECT Orchestra_ID FROM performance)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the orchestras that do not have any performances?\n[SQL]:\n", "output": "SELECT Orchestra FROM orchestra WHERE Orchestra_ID NOT IN (SELECT Orchestra_ID FROM performance)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the record companies shared by orchestras founded before 2003 and after 2003.\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra WHERE Year_of_Founded < 2003 INTERSECT SELECT Record_Company FROM orchestra WHERE Year_of_Founded > 2003"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the record companies that are used by both orchestras founded before 2003 and those founded after 2003?\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra WHERE Year_of_Founded < 2003 INTERSECT SELECT Record_Company FROM orchestra WHERE Year_of_Founded > 2003"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Find the number of orchestras whose record format is \"CD\" or \"DVD\".\n[SQL]:\n", "output": "SELECT COUNT(*) FROM orchestra WHERE Major_Record_Format = \"CD\" OR Major_Record_Format = \"DVD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Count the number of orchestras that have CD or DVD as their record format.\n[SQL]:\n", "output": "SELECT COUNT(*) FROM orchestra WHERE Major_Record_Format = \"CD\" OR Major_Record_Format = \"DVD\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the years in which orchestras that have given more than one performance are founded.\n[SQL]:\n", "output": "SELECT Year_of_Founded FROM orchestra AS T1 JOIN performance AS T2 ON T1.Orchestra_ID = T2.Orchestra_ID GROUP BY T2.Orchestra_ID HAVING COUNT(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are years of founding for orchestras that have had more than a single performance?\n[SQL]:\n", "output": "SELECT Year_of_Founded FROM orchestra AS T1 JOIN performance AS T2 ON T1.Orchestra_ID = T2.Orchestra_ID GROUP BY T2.Orchestra_ID HAVING COUNT(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many high schoolers are there?\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of high schoolers.\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names and grades of each high schooler.\n[SQL]:\n", "output": "SELECT name , grade FROM Highschooler"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names and grades for each high schooler?\n[SQL]:\n", "output": "SELECT name , grade FROM Highschooler"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show all the grades of the high schoolers.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the grade of each high schooler?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What grade is Kyle in?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler WHERE name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the grade for the high schooler named Kyle.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler WHERE name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of all high schoolers in grade 10.\n[SQL]:\n", "output": "SELECT name FROM Highschooler WHERE grade = 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of all high schoolers in grade 10?\n[SQL]:\n", "output": "SELECT name FROM Highschooler WHERE grade = 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the ID of the high schooler named Kyle.\n[SQL]:\n", "output": "SELECT ID FROM Highschooler WHERE name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is Kyle's id?\n[SQL]:\n", "output": "SELECT ID FROM Highschooler WHERE name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many high schoolers are there in grade 9 or 10?\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler WHERE grade = 9 OR grade = 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of high schoolers in grades 9 or 10.\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler WHERE grade = 9 OR grade = 10"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the number of high schoolers for each grade.\n[SQL]:\n", "output": "SELECT grade , count(*) FROM Highschooler GROUP BY grade"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many high schoolers are in each grade?\n[SQL]:\n", "output": "SELECT grade , count(*) FROM Highschooler GROUP BY grade"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Which grade has the most high schoolers?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the grade that has the greatest number of high schoolers.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show me all grades that have at least 4 students.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade HAVING count(*) >= 4"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Which grades have 4 or more high schoolers?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade HAVING count(*) >= 4"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the student IDs and numbers of friends corresponding to each.\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Friend GROUP BY student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many friends does each student have?\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Friend GROUP BY student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of high school students and their corresponding number of friends.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of the high schoolers and how many friends does each have?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the name of the high schooler who has the greatest number of friends?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the name of the high school student with the most friends.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of high schoolers who have at least 3 friends.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who have 3 or more friends?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 3"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of all of the high schooler Kyle's friends.\n[SQL]:\n", "output": "SELECT T3.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id JOIN Highschooler AS T3 ON T1.friend_id = T3.id WHERE T2.name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the names of friends of the high school student Kyle.\n[SQL]:\n", "output": "SELECT T3.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id JOIN Highschooler AS T3 ON T1.friend_id = T3.id WHERE T2.name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many friends does the high school student Kyle have?\n[SQL]:\n", "output": "SELECT count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of friends Kyle has.\n[SQL]:\n", "output": "SELECT count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show ids of all students who do not have any friends.\n[SQL]:\n", "output": "SELECT id FROM Highschooler EXCEPT SELECT student_id FROM Friend"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the ids of high school students who do not have friends?\n[SQL]:\n", "output": "SELECT id FROM Highschooler EXCEPT SELECT student_id FROM Friend"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show names of all high school students who do not have any friends.\n[SQL]:\n", "output": "SELECT name FROM Highschooler EXCEPT SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of students who have no friends?\n[SQL]:\n", "output": "SELECT name FROM Highschooler EXCEPT SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the ids of high schoolers who have friends and are also liked by someone else.\n[SQL]:\n", "output": "SELECT student_id FROM Friend INTERSECT SELECT liked_id FROM Likes"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the ids of students who both have friends and are liked?\n[SQL]:\n", "output": "SELECT student_id FROM Friend INTERSECT SELECT liked_id FROM Likes"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show name of all students who have some friends and also are liked by someone else.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id INTERSECT SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.liked_id = T2.id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who both have friends and are liked?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id INTERSECT SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.liked_id = T2.id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of likes for each student id.\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Likes GROUP BY student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many likes correspond to each student id?\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Likes GROUP BY student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of high schoolers who have likes, and numbers of likes for each.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who have likes, and how many likes does each have?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the name of the high schooler who has the greatest number of likes?\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Give the name of the student with the most likes.\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of students who have at least 2 likes.\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of students who have 2 or more likes?\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of students who have a grade higher than 5 and have at least 2 friends.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.grade > 5 GROUP BY T1.student_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who have a grade of over 5 and have 2 or more friends?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.grade > 5 GROUP BY T1.student_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many likes does Kyle have?\n[SQL]:\n", "output": "SELECT count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the number of likes that the high schooler named Kyle has.\n[SQL]:\n", "output": "SELECT count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Find the average grade of all students who have some friends.\n[SQL]:\n", "output": "SELECT avg(grade) FROM Highschooler WHERE id IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the average grade of students who have friends?\n[SQL]:\n", "output": "SELECT avg(grade) FROM Highschooler WHERE id IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Find the minimum grade of students who have no friends.\n[SQL]:\n", "output": "SELECT min(grade) FROM Highschooler WHERE id NOT IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the lowest grade of students who do not have any friends?\n[SQL]:\n", "output": "SELECT min(grade) FROM Highschooler WHERE id NOT IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which states have both owners and professionals living there?\n[SQL]:\n", "output": "SELECT state FROM Owners INTERSECT SELECT state FROM Professionals"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the states where both owners and professionals live.\n[SQL]:\n", "output": "SELECT state FROM Owners INTERSECT SELECT state FROM Professionals"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the average age of the dogs who have gone through any treatments?\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs WHERE dog_id IN ( SELECT dog_id FROM Treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the average age of the dogs who went through treatments.\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs WHERE dog_id IN ( SELECT dog_id FROM Treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals live in the state of Indiana or have done treatment on more than 2 treatments? List his or her id, last name and cell phone.\n[SQL]:\n", "output": "SELECT professional_id , last_name , cell_number FROM Professionals WHERE state = 'Indiana' UNION SELECT T1.professional_id , T1.last_name , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the id, last name and cell phone of the professionals who live in the state of Indiana or have performed more than two treatments.\n[SQL]:\n", "output": "SELECT professional_id , last_name , cell_number FROM Professionals WHERE state = 'Indiana' UNION SELECT T1.professional_id , T1.last_name , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) > 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which dogs have not cost their owner more than 1000 for treatment ? List the dog names .\n[SQL]:\n", "output": "select name from dogs where dog_id not in ( select dog_id from treatments group by dog_id having sum(cost_of_treatment) > 1000 )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the names of the dogs for which the owner has not spend more than 1000 for treatment ?\n[SQL]:\n", "output": "select name from dogs where dog_id not in ( select dog_id from treatments group by dog_id having sum(cost_of_treatment) > 1000 )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which first names are used for professionals or owners but are not used as dog names?\n[SQL]:\n", "output": "SELECT first_name FROM Professionals UNION SELECT first_name FROM Owners EXCEPT SELECT name FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the first names that are used for professionals or owners but are not used as dog names.\n[SQL]:\n", "output": "SELECT first_name FROM Professionals UNION SELECT first_name FROM Owners EXCEPT SELECT name FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professional did not operate any treatment on dogs? List the professional's id, role and email.\n[SQL]:\n", "output": "SELECT professional_id , role_code , email_address FROM Professionals EXCEPT SELECT T1.professional_id , T1.role_code , T1.email_address FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Give me the id, role and email of the professionals who did not perform any treatment on dogs.\n[SQL]:\n", "output": "SELECT professional_id , role_code , email_address FROM Professionals EXCEPT SELECT T1.professional_id , T1.role_code , T1.email_address FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owner owns the most dogs? List the owner id, first name and last name.\n[SQL]:\n", "output": "SELECT T1.owner_id , T2.first_name , T2.last_name FROM Dogs AS T1 JOIN Owners AS T2 ON T1.owner_id = T2.owner_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Return the owner id, first name and last name of the owner who has the most dogs.\n[SQL]:\n", "output": "SELECT T1.owner_id , T2.first_name , T2.last_name FROM Dogs AS T1 JOIN Owners AS T2 ON T1.owner_id = T2.owner_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals have done at least two treatments? List the professional's id, role, and first name.\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.role_code , T1.first_name FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the id, role, and first name of the professionals who have performed two or more treatments?\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.role_code , T1.first_name FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the name of the breed with the most dogs?\n[SQL]:\n", "output": "SELECT T1.breed_name FROM Breeds AS T1 JOIN Dogs AS T2 ON T1.breed_code = T2.breed_code GROUP BY T1.breed_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which breed do the most dogs have? Give me the breed name.\n[SQL]:\n", "output": "SELECT T1.breed_name FROM Breeds AS T1 JOIN Dogs AS T2 ON T1.breed_code = T2.breed_code GROUP BY T1.breed_name ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owner has paid for the most treatments on his or her dogs? List the owner id and last name.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Tell me the owner id and last name of the owner who spent the most on treatments of his or her dogs.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the description of the treatment type that costs the least money in total?\n[SQL]:\n", "output": "SELECT T1.treatment_type_description FROM Treatment_types AS T1 JOIN Treatments AS T2 ON T1.treatment_type_code = T2.treatment_type_code GROUP BY T1.treatment_type_code ORDER BY sum(cost_of_treatment) ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Give me the description of the treatment type whose total cost is the lowest.\n[SQL]:\n", "output": "SELECT T1.treatment_type_description FROM Treatment_types AS T1 JOIN Treatments AS T2 ON T1.treatment_type_code = T2.treatment_type_code GROUP BY T1.treatment_type_code ORDER BY sum(cost_of_treatment) ASC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owner has paid the largest amount of money in total for their dogs? Show the owner id and zip code.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.zip_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY sum(T3.cost_of_treatment) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the owner id and zip code of the owner who spent the most money in total for his or her dogs.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.zip_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY sum(T3.cost_of_treatment) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals have done at least two types of treatments? List the professional id and cell phone.\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the id and cell phone of the professionals who operate two or more types of treatments.\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the first name and last name of the professionals who have done treatment with cost below average?\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.last_name FROM Professionals AS T1 JOIN Treatments AS T2 WHERE cost_of_treatment < ( SELECT avg(cost_of_treatment) FROM Treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals have operated a treatment that costs less than the average? Give me theor first names and last names.\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.last_name FROM Professionals AS T1 JOIN Treatments AS T2 WHERE cost_of_treatment < ( SELECT avg(cost_of_treatment) FROM Treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the date of each treatment, together with the first name of the professional who operated it.\n[SQL]:\n", "output": "SELECT T1.date_of_treatment , T2.first_name FROM Treatments AS T1 JOIN Professionals AS T2 ON T1.professional_id = T2.professional_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the date and the operating professional's first name of each treatment?\n[SQL]:\n", "output": "SELECT T1.date_of_treatment , T2.first_name FROM Treatments AS T1 JOIN Professionals AS T2 ON T1.professional_id = T2.professional_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the cost of each treatment and the corresponding treatment type description.\n[SQL]:\n", "output": "SELECT T1.cost_of_treatment , T2.treatment_type_description FROM Treatments AS T1 JOIN treatment_types AS T2 ON T1.treatment_type_code = T2.treatment_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the cost and treatment type description of each treatment?\n[SQL]:\n", "output": "SELECT T1.cost_of_treatment , T2.treatment_type_description FROM Treatments AS T1 JOIN treatment_types AS T2 ON T1.treatment_type_code = T2.treatment_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List each owner's first name, last name, and the size of his for her dog.\n[SQL]:\n", "output": "SELECT T1.first_name , T1.last_name , T2.size_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are each owner's first name, last name, and the size of their dog?\n[SQL]:\n", "output": "SELECT T1.first_name , T1.last_name , T2.size_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List pairs of the owner's first name and the dogs's name.\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are each owner's first name and their dogs's name?\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the names of the dogs of the rarest breed and the treatment dates of them.\n[SQL]:\n", "output": "SELECT T1.name , T2.date_of_treatment FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id WHERE T1.breed_code = ( SELECT breed_code FROM Dogs GROUP BY breed_code ORDER BY count(*) ASC LIMIT 1 )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which dogs are of the rarest breed? Show their names and treatment dates.\n[SQL]:\n", "output": "SELECT T1.name , T2.date_of_treatment FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id WHERE T1.breed_code = ( SELECT breed_code FROM Dogs GROUP BY breed_code ORDER BY count(*) ASC LIMIT 1 )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which dogs are owned by someone who lives in Virginia? List the owner's first name and the dog's name.\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T1.state = 'Virginia'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the first names of owners living in Virginia and the names of dogs they own.\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T1.state = 'Virginia'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the arriving date and the departing date of the dogs who have gone through a treatment?\n[SQL]:\n", "output": "SELECT DISTINCT T1.date_arrived , T1.date_departed FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the arriving date and the departing date of the dogs that received a treatment.\n[SQL]:\n", "output": "SELECT DISTINCT T1.date_arrived , T1.date_departed FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the last name of the owner owning the youngest dog.\n[SQL]:\n", "output": "SELECT T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T2.age = ( SELECT max(age) FROM Dogs )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Who owns the youngest dog? Give me his or her last name.\n[SQL]:\n", "output": "SELECT T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T2.age = ( SELECT max(age) FROM Dogs )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the emails of the professionals who live in the state of Hawaii or the state of Wisconsin.\n[SQL]:\n", "output": "SELECT email_address FROM Professionals WHERE state = 'Hawaii' OR state = 'Wisconsin'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the emails of the professionals living in either the state of Hawaii or the state of Wisconsin?\n[SQL]:\n", "output": "SELECT email_address FROM Professionals WHERE state = 'Hawaii' OR state = 'Wisconsin'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the arriving date and the departing date of all the dogs?\n[SQL]:\n", "output": "SELECT date_arrived , date_departed FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the arrival date and the departure date for all the dogs.\n[SQL]:\n", "output": "SELECT date_arrived , date_departed FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many dogs went through any treatments?\n[SQL]:\n", "output": "SELECT count(DISTINCT dog_id) FROM Treatments"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Count the number of dogs that went through a treatment.\n[SQL]:\n", "output": "SELECT count(DISTINCT dog_id) FROM Treatments"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many professionals have performed any treatment to dogs?\n[SQL]:\n", "output": "SELECT count(DISTINCT professional_id) FROM Treatments"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the number of professionals who have ever treated dogs.\n[SQL]:\n", "output": "SELECT count(DISTINCT professional_id) FROM Treatments"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals live in a city containing the substring 'West'? List his or her role, street, city and state.\n[SQL]:\n", "output": "SELECT role_code , street , city , state FROM professionals WHERE city LIKE '%West%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the role, street, city and state of the professionals living in a city that contains the substring 'West'.\n[SQL]:\n", "output": "SELECT role_code , street , city , state FROM professionals WHERE city LIKE '%West%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owners live in the state whose name contains the substring 'North'? List his first name, last name and email.\n[SQL]:\n", "output": "SELECT first_name , last_name , email_address FROM Owners WHERE state LIKE '%North%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Return the first name, last name and email of the owners living in a state whose name contains the substring 'North'.\n[SQL]:\n", "output": "SELECT first_name , last_name , email_address FROM Owners WHERE state LIKE '%North%'"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many dogs have an age below the average?\n[SQL]:\n", "output": "SELECT count(*) FROM Dogs WHERE age < ( SELECT avg(age) FROM Dogs )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Count the number of dogs of an age below the average.\n[SQL]:\n", "output": "SELECT count(*) FROM Dogs WHERE age < ( SELECT avg(age) FROM Dogs )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How much does the most recent treatment cost?\n[SQL]:\n", "output": "SELECT cost_of_treatment FROM Treatments ORDER BY date_of_treatment DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Show me the cost of the most recently performed treatment.\n[SQL]:\n", "output": "SELECT cost_of_treatment FROM Treatments ORDER BY date_of_treatment DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many dogs have not gone through any treatment?\n[SQL]:\n", "output": "SELECT count(*) FROM Dogs WHERE dog_id NOT IN ( SELECT dog_id FROM Treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Tell me the number of dogs that have not received any treatment .\n[SQL]:\n", "output": "select count(*) from dogs where dog_id not in ( select dog_id from treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many owners temporarily do not have any dogs?\n[SQL]:\n", "output": "SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the number of owners who do not own any dogs at this moment.\n[SQL]:\n", "output": "SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many professionals did not operate any treatment on dogs?\n[SQL]:\n", "output": "SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the number of professionals who have not treated any dogs.\n[SQL]:\n", "output": "SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the dog name, age and weight of the dogs who have been abandoned? 1 stands for yes, and 0 stands for no.\n[SQL]:\n", "output": "SELECT name , age , weight FROM Dogs WHERE abandoned_yn = 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the dog name, age and weight of the dogs that were abandoned? Note that 1 stands for yes, and 0 stands for no in the tables.\n[SQL]:\n", "output": "SELECT name , age , weight FROM Dogs WHERE abandoned_yn = 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the average age of all the dogs?\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Compute the average age of all the dogs.\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the age of the oldest dog?\n[SQL]:\n", "output": "SELECT max(age) FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Tell me the age of the oldest dog.\n[SQL]:\n", "output": "SELECT max(age) FROM Dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How much does each charge type costs? List both charge type and amount.\n[SQL]:\n", "output": "SELECT charge_type , charge_amount FROM Charges"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List each charge type and its amount.\n[SQL]:\n", "output": "SELECT charge_type , charge_amount FROM Charges"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How much does the most expensive charge type costs?\n[SQL]:\n", "output": "SELECT max(charge_amount) FROM Charges"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the charge amount of the most expensive charge type?\n[SQL]:\n", "output": "SELECT max(charge_amount) FROM Charges"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the email, cell phone and home phone of all the professionals.\n[SQL]:\n", "output": "SELECT email_address , cell_number , home_phone FROM professionals"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the email, cell phone and home phone of each professional?\n[SQL]:\n", "output": "SELECT email_address , cell_number , home_phone FROM professionals"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are all the possible breed type and size type combinations?\n[SQL]:\n", "output": "SELECT DISTINCT breed_code , size_code FROM dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the distinct breed type and size type combinations for dogs.\n[SQL]:\n", "output": "SELECT DISTINCT breed_code , size_code FROM dogs"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the first name of all the professionals along with the description of the treatment they have done.\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T3.treatment_type_description FROM professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id JOIN Treatment_types AS T3 ON T2.treatment_type_code = T3.treatment_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are each professional's first name and description of the treatment they have performed?\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T3.treatment_type_description FROM professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id JOIN Treatment_types AS T3 ON T2.treatment_type_code = T3.treatment_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:How many singers are there?\n[SQL]:\n", "output": "SELECT count(*) FROM singer"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the count of singers?\n[SQL]:\n", "output": "SELECT count(*) FROM singer"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:List the name of singers in ascending order of net worth.\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of singers ordered by ascending net worth?\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the birth year and citizenship of singers?\n[SQL]:\n", "output": "SELECT Birth_Year , Citizenship FROM singer"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the birth years and citizenships of the singers?\n[SQL]:\n", "output": "SELECT Birth_Year , Citizenship FROM singer"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:List the name of singers whose citizenship is not \"France\".\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Citizenship != \"France\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers who are not French citizens?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Citizenship != \"France\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the name of singers whose birth year is either 1948 or 1949?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Birth_Year = 1948 OR Birth_Year = 1949"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers whose birth years are either 1948 or 1949?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Birth_Year = 1948 OR Birth_Year = 1949"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the name of the singer with the largest net worth?\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the name of the singer who is worth the most?\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show different citizenship of singers and the number of singers of each citizenship.\n[SQL]:\n", "output": "SELECT Citizenship , COUNT(*) FROM singer GROUP BY Citizenship"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:For each citizenship, how many singers are from that country?\n[SQL]:\n", "output": "SELECT Citizenship , COUNT(*) FROM singer GROUP BY Citizenship"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Please show the most common citizenship of singers.\n[SQL]:\n", "output": "SELECT Citizenship FROM singer GROUP BY Citizenship ORDER BY COUNT(*) DESC LIMIT 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the most common singer citizenship ?\n[SQL]:\n", "output": "select citizenship from singer group by citizenship order by count(*) desc limit 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show different citizenships and the maximum net worth of singers of each citizenship.\n[SQL]:\n", "output": "SELECT Citizenship , max(Net_Worth_Millions) FROM singer GROUP BY Citizenship"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:For each citizenship, what is the maximum net worth?\n[SQL]:\n", "output": "SELECT Citizenship , max(Net_Worth_Millions) FROM singer GROUP BY Citizenship"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show titles of songs and names of singers.\n[SQL]:\n", "output": "SELECT T2.Title , T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the song titles and singer names?\n[SQL]:\n", "output": "SELECT T2.Title , T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show distinct names of singers that have songs with sales more than 300000.\n[SQL]:\n", "output": "SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID WHERE T2.Sales > 300000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:what are the different names of the singers that have sales more than 300000?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID WHERE T2.Sales > 300000"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the names of singers that have more than one song.\n[SQL]:\n", "output": "SELECT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name HAVING COUNT(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers that have more than one songs?\n[SQL]:\n", "output": "SELECT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name HAVING COUNT(*) > 1"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the names of singers and the total sales of their songs.\n[SQL]:\n", "output": "SELECT T1.Name , sum(T2.Sales) FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:For each singer name, what is the total sales for their songs?\n[SQL]:\n", "output": "SELECT T1.Name , sum(T2.Sales) FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:List the name of singers that do not have any song.\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the sname of every sing that does not have any song?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the citizenship shared by singers with birth year before 1945 and after 1955.\n[SQL]:\n", "output": "SELECT Citizenship FROM singer WHERE Birth_Year < 1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year > 1955"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the citizenships that are shared by singers with a birth year before 1945 and after 1955?\n[SQL]:\n", "output": "SELECT Citizenship FROM singer WHERE Birth_Year < 1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year > 1955"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:How many available features are there in total?\n[SQL]:\n", "output": "SELECT count(*) FROM Other_Available_Features"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:What is the feature type name of feature AirCon?\n[SQL]:\n", "output": "SELECT T2.feature_type_name FROM Other_Available_Features AS T1 JOIN Ref_Feature_Types AS T2 ON T1.feature_type_code = T2.feature_type_code WHERE T1.feature_name = \"AirCon\""}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:Show the property type descriptions of properties belonging to that code.\n[SQL]:\n", "output": "SELECT T2.property_type_description FROM Properties AS T1 JOIN Ref_Property_Types AS T2 ON T1.property_type_code = T2.property_type_code GROUP BY T1.property_type_code"}
-{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:What are the names of properties that are either houses or apartments with more than 1 room?\n[SQL]:\n", "output": "SELECT property_name FROM Properties WHERE property_type_code = \"House\" UNION SELECT property_name FROM Properties WHERE property_type_code = \"Apartment\" AND room_count > 1"}
\ No newline at end of file
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many singers do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM singer", "db_id": "concert_singer", "query": "SELECT count(*) FROM singer", "question": "How many singers do we have?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the total number of singers?\n[SQL]:\n", "output": "SELECT count(*) FROM singer", "db_id": "concert_singer", "query": "SELECT count(*) FROM singer", "question": "What is the total number of singers?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show name, country, age for all singers ordered by age from the oldest to the youngest.\n[SQL]:\n", "output": "SELECT name , country , age FROM singer ORDER BY age DESC", "db_id": "concert_singer", "query": "SELECT name , country , age FROM singer ORDER BY age DESC", "question": "Show name, country, age for all singers ordered by age from the oldest to the youngest.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names, countries, and ages for every singer in descending order of age?\n[SQL]:\n", "output": "SELECT name , country , age FROM singer ORDER BY age DESC", "db_id": "concert_singer", "query": "SELECT name , country , age FROM singer ORDER BY age DESC", "question": "What are the names, countries, and ages for every singer in descending order of age?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the average, minimum, and maximum age of all singers from France?\n[SQL]:\n", "output": "SELECT avg(age) , min(age) , max(age) FROM singer WHERE country = 'France'", "db_id": "concert_singer", "query": "SELECT avg(age) , min(age) , max(age) FROM singer WHERE country = 'France'", "question": "What is the average, minimum, and maximum age of all singers from France?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the average, minimum, and maximum age for all French singers?\n[SQL]:\n", "output": "SELECT avg(age) , min(age) , max(age) FROM singer WHERE country = 'France'", "db_id": "concert_singer", "query": "SELECT avg(age) , min(age) , max(age) FROM singer WHERE country = 'France'", "question": "What is the average, minimum, and maximum age for all French singers?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the name and the release year of the song by the youngest singer.\n[SQL]:\n", "output": "SELECT song_name , song_release_year FROM singer ORDER BY age LIMIT 1", "db_id": "concert_singer", "query": "SELECT song_name , song_release_year FROM singer ORDER BY age LIMIT 1", "question": "Show the name and the release year of the song by the youngest singer.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names and release years for all the songs of the youngest singer?\n[SQL]:\n", "output": "SELECT song_name , song_release_year FROM singer ORDER BY age LIMIT 1", "db_id": "concert_singer", "query": "SELECT song_name , song_release_year FROM singer ORDER BY age LIMIT 1", "question": "What are the names and release years for all the songs of the youngest singer?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are all distinct countries where singers above age 20 are from?\n[SQL]:\n", "output": "SELECT DISTINCT country FROM singer WHERE age > 20", "db_id": "concert_singer", "query": "SELECT DISTINCT country FROM singer WHERE age > 20", "question": "What are all distinct countries where singers above age 20 are from?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the different countries with singers above age 20?\n[SQL]:\n", "output": "SELECT DISTINCT country FROM singer WHERE age > 20", "db_id": "concert_singer", "query": "SELECT DISTINCT country FROM singer WHERE age > 20", "question": "What are the different countries with singers above age 20?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show all countries and the number of singers in each country.\n[SQL]:\n", "output": "SELECT country , count(*) FROM singer GROUP BY country", "db_id": "concert_singer", "query": "SELECT country , count(*) FROM singer GROUP BY country", "question": "Show all countries and the number of singers in each country.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many singers are from each country?\n[SQL]:\n", "output": "SELECT country , count(*) FROM singer GROUP BY country", "db_id": "concert_singer", "query": "SELECT country , count(*) FROM singer GROUP BY country", "question": "How many singers are from each country?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:List all song names by singers above the average age.\n[SQL]:\n", "output": "SELECT song_name FROM singer WHERE age > (SELECT avg(age) FROM singer)", "db_id": "concert_singer", "query": "SELECT song_name FROM singer WHERE age > (SELECT avg(age) FROM singer)", "question": "List all song names by singers above the average age.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are all the song names by singers who are older than average?\n[SQL]:\n", "output": "SELECT song_name FROM singer WHERE age > (SELECT avg(age) FROM singer)", "db_id": "concert_singer", "query": "SELECT song_name FROM singer WHERE age > (SELECT avg(age) FROM singer)", "question": "What are all the song names by singers who are older than average?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show location and name for all stadiums with a capacity between 5000 and 10000.\n[SQL]:\n", "output": "SELECT LOCATION , name FROM stadium WHERE capacity BETWEEN 5000 AND 10000", "db_id": "concert_singer", "query": "SELECT LOCATION , name FROM stadium WHERE capacity BETWEEN 5000 AND 10000", "question": "Show location and name for all stadiums with a capacity between 5000 and 10000.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the locations and names of all stations with capacity between 5000 and 10000?\n[SQL]:\n", "output": "SELECT LOCATION , name FROM stadium WHERE capacity BETWEEN 5000 AND 10000", "db_id": "concert_singer", "query": "SELECT LOCATION , name FROM stadium WHERE capacity BETWEEN 5000 AND 10000", "question": "What are the locations and names of all stations with capacity between 5000 and 10000?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the maximum capacity and the average of all stadiums ?\n[SQL]:\n", "output": "select max(capacity), average from stadium", "db_id": "concert_singer", "query": "select max(capacity), average from stadium", "question": "What is the maximum capacity and the average of all stadiums ?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the average and maximum capacities for all stadiums ?\n[SQL]:\n", "output": "select avg(capacity) , max(capacity) from stadium", "db_id": "concert_singer", "query": "select avg(capacity) , max(capacity) from stadium", "question": "What is the average and maximum capacities for all stadiums ?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and capacity for the stadium with highest average attendance?\n[SQL]:\n", "output": "SELECT name , capacity FROM stadium ORDER BY average DESC LIMIT 1", "db_id": "concert_singer", "query": "SELECT name , capacity FROM stadium ORDER BY average DESC LIMIT 1", "question": "What is the name and capacity for the stadium with highest average attendance?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and capacity for the stadium with the highest average attendance?\n[SQL]:\n", "output": "SELECT name , capacity FROM stadium ORDER BY average DESC LIMIT 1", "db_id": "concert_singer", "query": "SELECT name , capacity FROM stadium ORDER BY average DESC LIMIT 1", "question": "What is the name and capacity for the stadium with the highest average attendance?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many concerts are there in year 2014 or 2015?\n[SQL]:\n", "output": "SELECT count(*) FROM concert WHERE YEAR = 2014 OR YEAR = 2015", "db_id": "concert_singer", "query": "SELECT count(*) FROM concert WHERE YEAR = 2014 OR YEAR = 2015", "question": "How many concerts are there in year 2014 or 2015?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:How many concerts occurred in 2014 or 2015?\n[SQL]:\n", "output": "SELECT count(*) FROM concert WHERE YEAR = 2014 OR YEAR = 2015", "db_id": "concert_singer", "query": "SELECT count(*) FROM concert WHERE YEAR = 2014 OR YEAR = 2015", "question": "How many concerts occurred in 2014 or 2015?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the stadium name and the number of concerts in each stadium.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id GROUP BY T1.stadium_id", "db_id": "concert_singer", "query": "SELECT T2.name , count(*) FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id GROUP BY T1.stadium_id", "question": "Show the stadium name and the number of concerts in each stadium.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:For each stadium, how many concerts play there?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id GROUP BY T1.stadium_id", "db_id": "concert_singer", "query": "SELECT T2.name , count(*) FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id GROUP BY T1.stadium_id", "question": "For each stadium, how many concerts play there?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the stadium name and capacity with most number of concerts in year 2014 or after.\n[SQL]:\n", "output": "SELECT T2.name , T2.capacity FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year >= 2014 GROUP BY T2.stadium_id ORDER BY count(*) DESC LIMIT 1", "db_id": "concert_singer", "query": "SELECT T2.name , T2.capacity FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year >= 2014 GROUP BY T2.stadium_id ORDER BY count(*) DESC LIMIT 1", "question": "Show the stadium name and capacity with most number of concerts in year 2014 or after.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and capacity of the stadium with the most concerts after 2013 ?\n[SQL]:\n", "output": "select t2.name , t2.capacity from concert as t1 join stadium as t2 on t1.stadium_id = t2.stadium_id where t1.year > 2013 group by t2.stadium_id order by count(*) desc limit 1", "db_id": "concert_singer", "query": "select t2.name , t2.capacity from concert as t1 join stadium as t2 on t1.stadium_id = t2.stadium_id where t1.year > 2013 group by t2.stadium_id order by count(*) desc limit 1", "question": "What is the name and capacity of the stadium with the most concerts after 2013 ?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Which year has most number of concerts?\n[SQL]:\n", "output": "SELECT YEAR FROM concert GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "db_id": "concert_singer", "query": "SELECT YEAR FROM concert GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "question": "Which year has most number of concerts?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the year that had the most concerts?\n[SQL]:\n", "output": "SELECT YEAR FROM concert GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "db_id": "concert_singer", "query": "SELECT YEAR FROM concert GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "question": "What is the year that had the most concerts?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the stadium names without any concert.\n[SQL]:\n", "output": "SELECT name FROM stadium WHERE stadium_id NOT IN (SELECT stadium_id FROM concert)", "db_id": "concert_singer", "query": "SELECT name FROM stadium WHERE stadium_id NOT IN (SELECT stadium_id FROM concert)", "question": "Show the stadium names without any concert.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of the stadiums without any concerts?\n[SQL]:\n", "output": "SELECT name FROM stadium WHERE stadium_id NOT IN (SELECT stadium_id FROM concert)", "db_id": "concert_singer", "query": "SELECT name FROM stadium WHERE stadium_id NOT IN (SELECT stadium_id FROM concert)", "question": "What are the names of the stadiums without any concerts?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show countries where a singer above age 40 and a singer below 30 are from.\n[SQL]:\n", "output": "SELECT country FROM singer WHERE age > 40 INTERSECT SELECT country FROM singer WHERE age < 30", "db_id": "concert_singer", "query": "SELECT country FROM singer WHERE age > 40 INTERSECT SELECT country FROM singer WHERE age < 30", "question": "Show countries where a singer above age 40 and a singer below 30 are from.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show names for all stadiums except for stadiums having a concert in year 2014.\n[SQL]:\n", "output": "SELECT name FROM stadium EXCEPT SELECT T2.name FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year = 2014", "db_id": "concert_singer", "query": "SELECT name FROM stadium EXCEPT SELECT T2.name FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year = 2014", "question": "Show names for all stadiums except for stadiums having a concert in year 2014.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of all stadiums that did not have a concert in 2014?\n[SQL]:\n", "output": "SELECT name FROM stadium EXCEPT SELECT T2.name FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year = 2014", "db_id": "concert_singer", "query": "SELECT name FROM stadium EXCEPT SELECT T2.name FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.year = 2014", "question": "What are the names of all stadiums that did not have a concert in 2014?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Show the name and theme for all concerts and the number of singers in each concert.\n[SQL]:\n", "output": "SELECT T2.concert_name , T2.theme , count(*) FROM singer_in_concert AS T1 JOIN concert AS T2 ON T1.concert_id = T2.concert_id GROUP BY T2.concert_id", "db_id": "concert_singer", "query": "SELECT T2.concert_name , T2.theme , count(*) FROM singer_in_concert AS T1 JOIN concert AS T2 ON T1.concert_id = T2.concert_id GROUP BY T2.concert_id", "question": "Show the name and theme for all concerts and the number of singers in each concert.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names , themes , and number of singers for every concert ?\n[SQL]:\n", "output": "select t2.concert_name , t2.theme , count(*) from singer_in_concert as t1 join concert as t2 on t1.concert_id = t2.concert_id group by t2.concert_id", "db_id": "concert_singer", "query": "select t2.concert_name , t2.theme , count(*) from singer_in_concert as t1 join concert as t2 on t1.concert_id = t2.concert_id group by t2.concert_id", "question": "What are the names , themes , and number of singers for every concert ?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:List singer names and number of concerts for each singer.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id GROUP BY T2.singer_id", "db_id": "concert_singer", "query": "SELECT T2.name , count(*) FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id GROUP BY T2.singer_id", "question": "List singer names and number of concerts for each singer.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers and number of concerts for each person?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id GROUP BY T2.singer_id", "db_id": "concert_singer", "query": "SELECT T2.name , count(*) FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id GROUP BY T2.singer_id", "question": "What are the names of the singers and number of concerts for each person?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:List all singer names in concerts in year 2014.\n[SQL]:\n", "output": "SELECT T2.name FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id JOIN concert AS T3 ON T1.concert_id = T3.concert_id WHERE T3.year = 2014", "db_id": "concert_singer", "query": "SELECT T2.name FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id JOIN concert AS T3 ON T1.concert_id = T3.concert_id WHERE T3.year = 2014", "question": "List all singer names in concerts in year 2014.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers who performed in a concert in 2014?\n[SQL]:\n", "output": "SELECT T2.name FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id JOIN concert AS T3 ON T1.concert_id = T3.concert_id WHERE T3.year = 2014", "db_id": "concert_singer", "query": "SELECT T2.name FROM singer_in_concert AS T1 JOIN singer AS T2 ON T1.singer_id = T2.singer_id JOIN concert AS T3 ON T1.concert_id = T3.concert_id WHERE T3.year = 2014", "question": "What are the names of the singers who performed in a concert in 2014?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:what is the name and nation of the singer who have a song having 'Hey' in its name?\n[SQL]:\n", "output": "SELECT name , country FROM singer WHERE song_name LIKE '%Hey%'", "db_id": "concert_singer", "query": "SELECT name , country FROM singer WHERE song_name LIKE '%Hey%'", "question": "what is the name and nation of the singer who have a song having 'Hey' in its name?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What is the name and country of origin of every singer who has a song with the word 'Hey' in its title?\n[SQL]:\n", "output": "SELECT name , country FROM singer WHERE song_name LIKE '%Hey%'", "db_id": "concert_singer", "query": "SELECT name , country FROM singer WHERE song_name LIKE '%Hey%'", "question": "What is the name and country of origin of every singer who has a song with the word 'Hey' in its title?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Find the name and location of the stadiums which some concerts happened in the years of both 2014 and 2015.\n[SQL]:\n", "output": "SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2014 INTERSECT SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2015", "db_id": "concert_singer", "query": "SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2014 INTERSECT SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2015", "question": "Find the name and location of the stadiums which some concerts happened in the years of both 2014 and 2015.", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the names and locations of the stadiums that had concerts that occurred in both 2014 and 2015?\n[SQL]:\n", "output": "SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2014 INTERSECT SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2015", "db_id": "concert_singer", "query": "SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2014 INTERSECT SELECT T2.name , T2.location FROM concert AS T1 JOIN stadium AS T2 ON T1.stadium_id = T2.stadium_id WHERE T1.Year = 2015", "question": "What are the names and locations of the stadiums that had concerts that occurred in both 2014 and 2015?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:Find the number of concerts happened in the stadium with the highest capacity .\n[SQL]:\n", "output": "select count(*) from concert where stadium_id = (select stadium_id from stadium order by capacity desc limit 1)", "db_id": "concert_singer", "query": "select count(*) from concert where stadium_id = (select stadium_id from stadium order by capacity desc limit 1)", "question": "Find the number of concerts happened in the stadium with the highest capacity .", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);\"\n[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id\"\n[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id\"\nAnswer the following question with a SQL Statement:What are the number of concerts that occurred in the stadium with the largest capacity ?\n[SQL]:\n", "output": "select count(*) from concert where stadium_id = (select stadium_id from stadium order by capacity desc limit 1)", "db_id": "concert_singer", "query": "select count(*) from concert where stadium_id = (select stadium_id from stadium order by capacity desc limit 1)", "question": "What are the number of concerts that occurred in the stadium with the largest capacity ?", "schema": "[Schema (values) (types)]: | concert_singer | stadium : stadium_id (text) , location (number) , name (text) , capacity (text) , highest (number) , lowest (number) , average (number) | singer : singer_id (text) , name (number) , country (text) , song_name (text) , song_release_year (number) , age (number) , is_male (number) | concert : concert_id (text) , concert_name (number) , theme (text) , stadium_id (text) , year (number) | singer_in_concert : concert_id (text) , singer_id (number);", "primary_keys": "[Primary Keys]: stadium : stadium_id, singer : singer_id, concert : concert_id, singer_in_concert : concert_id", "foreign_keys": "[Foreign Keys]: concert : stadium_id = stadium : stadium_id | singer_in_concert : singer_id = singer : singer_id | singer_in_concert : concert_id = concert : concert_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of pets whose weight is heavier than 10.\n[SQL]:\n", "output": "SELECT count(*) FROM pets WHERE weight > 10", "db_id": "pets_1", "query": "SELECT count(*) FROM pets WHERE weight > 10", "question": "Find the number of pets whose weight is heavier than 10.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many pets have a greater weight than 10?\n[SQL]:\n", "output": "SELECT count(*) FROM pets WHERE weight > 10", "db_id": "pets_1", "query": "SELECT count(*) FROM pets WHERE weight > 10", "question": "How many pets have a greater weight than 10?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the weight of the youngest dog.\n[SQL]:\n", "output": "SELECT weight FROM pets ORDER BY pet_age LIMIT 1", "db_id": "pets_1", "query": "SELECT weight FROM pets ORDER BY pet_age LIMIT 1", "question": "Find the weight of the youngest dog.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How much does the youngest dog weigh?\n[SQL]:\n", "output": "SELECT weight FROM pets ORDER BY pet_age LIMIT 1", "db_id": "pets_1", "query": "SELECT weight FROM pets ORDER BY pet_age LIMIT 1", "question": "How much does the youngest dog weigh?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the maximum weight for each type of pet. List the maximum weight and pet type.\n[SQL]:\n", "output": "SELECT max(weight) , petType FROM pets GROUP BY petType", "db_id": "pets_1", "query": "SELECT max(weight) , petType FROM pets GROUP BY petType", "question": "Find the maximum weight for each type of pet. List the maximum weight and pet type.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:List the maximum weight and type for each type of pet.\n[SQL]:\n", "output": "SELECT max(weight) , petType FROM pets GROUP BY petType", "db_id": "pets_1", "query": "SELECT max(weight) , petType FROM pets GROUP BY petType", "question": "List the maximum weight and type for each type of pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find number of pets owned by students who are older than 20.\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.age > 20", "db_id": "pets_1", "query": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.age > 20", "question": "Find number of pets owned by students who are older than 20.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many pets are owned by students that have an age greater than 20?\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.age > 20", "db_id": "pets_1", "query": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.age > 20", "question": "How many pets are owned by students that have an age greater than 20?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of dog pets that are raised by female students (with sex F).\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T2.petid = T3.petid WHERE T1.sex = 'F' AND T3.pettype = 'dog'", "db_id": "pets_1", "query": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T2.petid = T3.petid WHERE T1.sex = 'F' AND T3.pettype = 'dog'", "question": "Find the number of dog pets that are raised by female students (with sex F).", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many dog pets are raised by female students?\n[SQL]:\n", "output": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T2.petid = T3.petid WHERE T1.sex = 'F' AND T3.pettype = 'dog'", "db_id": "pets_1", "query": "SELECT count(*) FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T2.petid = T3.petid WHERE T1.sex = 'F' AND T3.pettype = 'dog'", "question": "How many dog pets are raised by female students?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of distinct type of pets.\n[SQL]:\n", "output": "SELECT count(DISTINCT pettype) FROM pets", "db_id": "pets_1", "query": "SELECT count(DISTINCT pettype) FROM pets", "question": "Find the number of distinct type of pets.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:How many different types of pet are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT pettype) FROM pets", "db_id": "pets_1", "query": "SELECT count(DISTINCT pettype) FROM pets", "question": "How many different types of pet are there?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name of students who have cat or dog pet.\n[SQL]:\n", "output": "SELECT DISTINCT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' OR T3.pettype = 'dog'", "db_id": "pets_1", "query": "SELECT DISTINCT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' OR T3.pettype = 'dog'", "question": "Find the first name of students who have cat or dog pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the first names of every student who has a cat or dog as a pet?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' OR T3.pettype = 'dog'", "db_id": "pets_1", "query": "SELECT DISTINCT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' OR T3.pettype = 'dog'", "question": "What are the first names of every student who has a cat or dog as a pet?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name of students who have both cat and dog pets .\n[SQL]:\n", "output": "select t1.fname from student as t1 join has_pet as t2 on t1.stuid = t2.stuid join pets as t3 on t3.petid = t2.petid where t3.pettype = 'cat' intersect select t1.fname from student as t1 join has_pet as t2 on t1.stuid = t2.stuid join pets as t3 on t3.petid = t2.petid where t3.pettype = 'dog'", "db_id": "pets_1", "query": "select t1.fname from student as t1 join has_pet as t2 on t1.stuid = t2.stuid join pets as t3 on t3.petid = t2.petid where t3.pettype = 'cat' intersect select t1.fname from student as t1 join has_pet as t2 on t1.stuid = t2.stuid join pets as t3 on t3.petid = t2.petid where t3.pettype = 'dog'", "question": "Find the first name of students who have both cat and dog pets .", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the students' first names who have both cats and dogs as pets?\n[SQL]:\n", "output": "SELECT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' INTERSECT SELECT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog'", "db_id": "pets_1", "query": "SELECT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat' INTERSECT SELECT T1.Fname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog'", "question": "What are the students' first names who have both cats and dogs as pets?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the major and age of students who do not have a cat pet.\n[SQL]:\n", "output": "SELECT major , age FROM student WHERE stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "db_id": "pets_1", "query": "SELECT major , age FROM student WHERE stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "question": "Find the major and age of students who do not have a cat pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What major is every student who does not own a cat as a pet, and also how old are they?\n[SQL]:\n", "output": "SELECT major , age FROM student WHERE stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "db_id": "pets_1", "query": "SELECT major , age FROM student WHERE stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "question": "What major is every student who does not own a cat as a pet, and also how old are they?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the id of students who do not have a cat pet.\n[SQL]:\n", "output": "SELECT stuid FROM student EXCEPT SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat'", "db_id": "pets_1", "query": "SELECT stuid FROM student EXCEPT SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat'", "question": "Find the id of students who do not have a cat pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the ids of the students who do not own cats as pets?\n[SQL]:\n", "output": "SELECT stuid FROM student EXCEPT SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat'", "db_id": "pets_1", "query": "SELECT stuid FROM student EXCEPT SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat'", "question": "What are the ids of the students who do not own cats as pets?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name and age of students who have a dog but do not have a cat as a pet.\n[SQL]:\n", "output": "SELECT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog' AND T1.stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "db_id": "pets_1", "query": "SELECT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog' AND T1.stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "question": "Find the first name and age of students who have a dog but do not have a cat as a pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the first name of every student who has a dog but does not have a cat?\n[SQL]:\n", "output": "SELECT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog' AND T1.stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "db_id": "pets_1", "query": "SELECT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'dog' AND T1.stuid NOT IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')", "question": "What is the first name of every student who has a dog but does not have a cat?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the type and weight of the youngest pet.\n[SQL]:\n", "output": "SELECT pettype , weight FROM pets ORDER BY pet_age LIMIT 1", "db_id": "pets_1", "query": "SELECT pettype , weight FROM pets ORDER BY pet_age LIMIT 1", "question": "Find the type and weight of the youngest pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What type of pet is the youngest animal, and how much does it weigh?\n[SQL]:\n", "output": "SELECT pettype , weight FROM pets ORDER BY pet_age LIMIT 1", "db_id": "pets_1", "query": "SELECT pettype , weight FROM pets ORDER BY pet_age LIMIT 1", "question": "What type of pet is the youngest animal, and how much does it weigh?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the id and weight of all pets whose age is older than 1.\n[SQL]:\n", "output": "SELECT petid , weight FROM pets WHERE pet_age > 1", "db_id": "pets_1", "query": "SELECT petid , weight FROM pets WHERE pet_age > 1", "question": "Find the id and weight of all pets whose age is older than 1.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the id and weight of every pet who is older than 1?\n[SQL]:\n", "output": "SELECT petid , weight FROM pets WHERE pet_age > 1", "db_id": "pets_1", "query": "SELECT petid , weight FROM pets WHERE pet_age > 1", "question": "What is the id and weight of every pet who is older than 1?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the average and maximum age for each type of pet.\n[SQL]:\n", "output": "SELECT avg(pet_age) , max(pet_age) , pettype FROM pets GROUP BY pettype", "db_id": "pets_1", "query": "SELECT avg(pet_age) , max(pet_age) , pettype FROM pets GROUP BY pettype", "question": "Find the average and maximum age for each type of pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the average and maximum age for each pet type?\n[SQL]:\n", "output": "SELECT avg(pet_age) , max(pet_age) , pettype FROM pets GROUP BY pettype", "db_id": "pets_1", "query": "SELECT avg(pet_age) , max(pet_age) , pettype FROM pets GROUP BY pettype", "question": "What is the average and maximum age for each pet type?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the average weight for each pet type.\n[SQL]:\n", "output": "SELECT avg(weight) , pettype FROM pets GROUP BY pettype", "db_id": "pets_1", "query": "SELECT avg(weight) , pettype FROM pets GROUP BY pettype", "question": "Find the average weight for each pet type.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the average weight for each type of pet?\n[SQL]:\n", "output": "SELECT avg(weight) , pettype FROM pets GROUP BY pettype", "db_id": "pets_1", "query": "SELECT avg(weight) , pettype FROM pets GROUP BY pettype", "question": "What is the average weight for each type of pet?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name and age of students who have a pet.\n[SQL]:\n", "output": "SELECT DISTINCT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid", "db_id": "pets_1", "query": "SELECT DISTINCT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid", "question": "Find the first name and age of students who have a pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What are the different first names and ages of the students who do have pets?\n[SQL]:\n", "output": "SELECT DISTINCT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid", "db_id": "pets_1", "query": "SELECT DISTINCT T1.fname , T1.age FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid", "question": "What are the different first names and ages of the students who do have pets?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the id of the pet owned by student whose last name is \u2018Smith\u2019.\n[SQL]:\n", "output": "SELECT T2.petid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.Lname = 'Smith'", "db_id": "pets_1", "query": "SELECT T2.petid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.Lname = 'Smith'", "question": "Find the id of the pet owned by student whose last name is \u2018Smith\u2019.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the id of the pet owned by the student whose last name is 'Smith'?\n[SQL]:\n", "output": "SELECT T2.petid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.Lname = 'Smith'", "db_id": "pets_1", "query": "SELECT T2.petid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid WHERE T1.Lname = 'Smith'", "question": "What is the id of the pet owned by the student whose last name is 'Smith'?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the number of pets for each student who has any pet and student id.\n[SQL]:\n", "output": "SELECT count(*) , T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid", "db_id": "pets_1", "query": "SELECT count(*) , T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid", "question": "Find the number of pets for each student who has any pet and student id.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:For students who have pets , how many pets does each student have ? list their ids instead of names .\n[SQL]:\n", "output": "select count(*) , t1.stuid from student as t1 join has_pet as t2 on t1.stuid = t2.stuid group by t1.stuid", "db_id": "pets_1", "query": "select count(*) , t1.stuid from student as t1 join has_pet as t2 on t1.stuid = t2.stuid group by t1.stuid", "question": "For students who have pets , how many pets does each student have ? list their ids instead of names .", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the first name and gender of student who have more than one pet.\n[SQL]:\n", "output": "SELECT T1.fname , T1.sex FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid HAVING count(*) > 1", "db_id": "pets_1", "query": "SELECT T1.fname , T1.sex FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid HAVING count(*) > 1", "question": "Find the first name and gender of student who have more than one pet.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the first name and gender of the all the students who have more than one pet?\n[SQL]:\n", "output": "SELECT T1.fname , T1.sex FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid HAVING count(*) > 1", "db_id": "pets_1", "query": "SELECT T1.fname , T1.sex FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid GROUP BY T1.stuid HAVING count(*) > 1", "question": "What is the first name and gender of the all the students who have more than one pet?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the last name of the student who has a cat that is age 3.\n[SQL]:\n", "output": "SELECT T1.lname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pet_age = 3 AND T3.pettype = 'cat'", "db_id": "pets_1", "query": "SELECT T1.lname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pet_age = 3 AND T3.pettype = 'cat'", "question": "Find the last name of the student who has a cat that is age 3.", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the last name of the student who has a cat that is 3 years old?\n[SQL]:\n", "output": "SELECT T1.lname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pet_age = 3 AND T3.pettype = 'cat'", "db_id": "pets_1", "query": "SELECT T1.lname FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pet_age = 3 AND T3.pettype = 'cat'", "question": "What is the last name of the student who has a cat that is 3 years old?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:Find the average age of students who do not have any pet .\n[SQL]:\n", "output": "select avg(age) from student where stuid not in (select stuid from has_pet)", "db_id": "pets_1", "query": "select avg(age) from student where stuid not in (select stuid from has_pet)", "question": "Find the average age of students who do not have any pet .", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);\"\n[Primary Keys]: student : stuid, has_pet : petid\"\n[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid\"\nAnswer the following question with a SQL Statement:What is the average age for all students who do not own any pets ?\n[SQL]:\n", "output": "select avg(age) from student where stuid not in (select stuid from has_pet)", "db_id": "pets_1", "query": "select avg(age) from student where stuid not in (select stuid from has_pet)", "question": "What is the average age for all students who do not own any pets ?", "schema": "[Schema (values) (types)]: | pets_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Has_Pet : stuid (text) , petid (number) | Pets : petid (text) , pettype (number) , pet_age (text) , weight (text);", "primary_keys": "[Primary Keys]: student : stuid, has_pet : petid", "foreign_keys": "[Foreign Keys]: has_pet : stuid = student : stuid | has_pet : petid = pets : petid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many continents are there?\n[SQL]:\n", "output": "SELECT count(*) FROM CONTINENTS;", "db_id": "car_1", "query": "SELECT count(*) FROM CONTINENTS;", "question": "How many continents are there?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of continents?\n[SQL]:\n", "output": "SELECT count(*) FROM CONTINENTS;", "db_id": "car_1", "query": "SELECT count(*) FROM CONTINENTS;", "question": "What is the number of continents?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries does each continent have? List the continent id, continent name and the number of countries.\n[SQL]:\n", "output": "SELECT T1.ContId , T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.Continent GROUP BY T1.ContId;", "db_id": "car_1", "query": "SELECT T1.ContId , T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.Continent GROUP BY T1.ContId;", "question": "How many countries does each continent have? List the continent id, continent name and the number of countries.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For each continent, list its id, name, and how many countries it has?\n[SQL]:\n", "output": "SELECT T1.ContId , T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.Continent GROUP BY T1.ContId;", "db_id": "car_1", "query": "SELECT T1.ContId , T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.Continent GROUP BY T1.ContId;", "question": "For each continent, list its id, name, and how many countries it has?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries are listed?\n[SQL]:\n", "output": "SELECT count(*) FROM COUNTRIES;", "db_id": "car_1", "query": "SELECT count(*) FROM COUNTRIES;", "question": "How many countries are listed?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries exist?\n[SQL]:\n", "output": "SELECT count(*) FROM COUNTRIES;", "db_id": "car_1", "query": "SELECT count(*) FROM COUNTRIES;", "question": "How many countries exist?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many models does each car maker produce? List maker full name, id and the number.\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id , count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id;", "db_id": "car_1", "query": "SELECT T1.FullName , T1.Id , count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id;", "question": "How many models does each car maker produce? List maker full name, id and the number.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the full name of each car maker, along with its id and how many models it produces?\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id , count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id;", "db_id": "car_1", "query": "SELECT T1.FullName , T1.Id , count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id;", "question": "What is the full name of each car maker, along with its id and how many models it produces?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which model of the car has the minimum horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.horsepower ASC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.horsepower ASC LIMIT 1;", "question": "Which model of the car has the minimum horsepower?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the model of the car with the smallest amount of horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.horsepower ASC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.horsepower ASC LIMIT 1;", "question": "What is the model of the car with the smallest amount of horsepower?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Find the model of the car whose weight is below the average weight.\n[SQL]:\n", "output": "SELECT T1.model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Weight < (SELECT avg(Weight) FROM CARS_DATA)", "db_id": "car_1", "query": "SELECT T1.model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Weight < (SELECT avg(Weight) FROM CARS_DATA)", "question": "Find the model of the car whose weight is below the average weight.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the model for the car with a weight smaller than the average?\n[SQL]:\n", "output": "SELECT T1.model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Weight < (SELECT avg(Weight) FROM CARS_DATA)", "db_id": "car_1", "query": "SELECT T1.model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Weight < (SELECT avg(Weight) FROM CARS_DATA)", "question": "What is the model for the car with a weight smaller than the average?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Find the name of the makers that produced some cars in the year of 1970?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model JOIN CARS_DATA AS T4 ON T3.MakeId = T4.id WHERE T4.year = '1970';", "db_id": "car_1", "query": "SELECT DISTINCT T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model JOIN CARS_DATA AS T4 ON T3.MakeId = T4.id WHERE T4.year = '1970';", "question": "Find the name of the makers that produced some cars in the year of 1970?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the name of the different car makers who produced a car in 1970?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model JOIN CARS_DATA AS T4 ON T3.MakeId = T4.id WHERE T4.year = '1970';", "db_id": "car_1", "query": "SELECT DISTINCT T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model JOIN CARS_DATA AS T4 ON T3.MakeId = T4.id WHERE T4.year = '1970';", "question": "What is the name of the different car makers who produced a car in 1970?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Find the make and production time of the cars that were produced in the earliest year?\n[SQL]:\n", "output": "SELECT T2.Make , T1.Year FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Year = (SELECT min(YEAR) FROM CARS_DATA);", "db_id": "car_1", "query": "SELECT T2.Make , T1.Year FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Year = (SELECT min(YEAR) FROM CARS_DATA);", "question": "Find the make and production time of the cars that were produced in the earliest year?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maker of the carr produced in the earliest year and what year was it?\n[SQL]:\n", "output": "SELECT T2.Make , T1.Year FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Year = (SELECT min(YEAR) FROM CARS_DATA);", "db_id": "car_1", "query": "SELECT T2.Make , T1.Year FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Year = (SELECT min(YEAR) FROM CARS_DATA);", "question": "What is the maker of the carr produced in the earliest year and what year was it?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which distinct car models are the produced after 1980?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.model = T2.model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.id WHERE T3.year > 1980;", "db_id": "car_1", "query": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.model = T2.model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.id WHERE T3.year > 1980;", "question": "Which distinct car models are the produced after 1980?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different models for the cards produced after 1980?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.model = T2.model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.id WHERE T3.year > 1980;", "db_id": "car_1", "query": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.model = T2.model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.id WHERE T3.year > 1980;", "question": "What are the different models for the cards produced after 1980?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car makers are there in each continents? List the continent name and the count.\n[SQL]:\n", "output": "SELECT T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.continent JOIN car_makers AS T3 ON T2.CountryId = T3.Country GROUP BY T1.Continent;", "db_id": "car_1", "query": "SELECT T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.continent JOIN car_makers AS T3 ON T2.CountryId = T3.Country GROUP BY T1.Continent;", "question": "How many car makers are there in each continents? List the continent name and the count.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the name of each continent and how many car makers are there in each one?\n[SQL]:\n", "output": "SELECT T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.continent JOIN car_makers AS T3 ON T2.CountryId = T3.Country GROUP BY T1.Continent;", "db_id": "car_1", "query": "SELECT T1.Continent , count(*) FROM CONTINENTS AS T1 JOIN COUNTRIES AS T2 ON T1.ContId = T2.continent JOIN car_makers AS T3 ON T2.CountryId = T3.Country GROUP BY T1.Continent;", "question": "What is the name of each continent and how many car makers are there in each one?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which of the countries has the most car makers? List the country name.\n[SQL]:\n", "output": "SELECT T2.CountryName FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId GROUP BY T1.Country ORDER BY Count(*) DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T2.CountryName FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId GROUP BY T1.Country ORDER BY Count(*) DESC LIMIT 1;", "question": "Which of the countries has the most car makers? List the country name.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the name of the country with the most car makers?\n[SQL]:\n", "output": "SELECT T2.CountryName FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId GROUP BY T1.Country ORDER BY Count(*) DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T2.CountryName FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId GROUP BY T1.Country ORDER BY Count(*) DESC LIMIT 1;", "question": "What is the name of the country with the most car makers?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car models are produced by each maker ? Only list the count and the maker full name .\n[SQL]:\n", "output": "select count(*) , t2.fullname from model_list as t1 join car_makers as t2 on t1.maker = t2.id group by t2.id;", "db_id": "car_1", "query": "select count(*) , t2.fullname from model_list as t1 join car_makers as t2 on t1.maker = t2.id group by t2.id;", "question": "How many car models are produced by each maker ? Only list the count and the maker full name .", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of car models that are produced by each maker and what is the id and full name of each maker?\n[SQL]:\n", "output": "SELECT Count(*) , T2.FullName , T2.id FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id GROUP BY T2.id;", "db_id": "car_1", "query": "SELECT Count(*) , T2.FullName , T2.id FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id GROUP BY T2.id;", "question": "What is the number of car models that are produced by each maker and what is the id and full name of each maker?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the accelerate of the car make amc hornet sportabout (sw)?\n[SQL]:\n", "output": "SELECT T1.Accelerate FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Make = 'amc hornet sportabout (sw)';", "db_id": "car_1", "query": "SELECT T1.Accelerate FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Make = 'amc hornet sportabout (sw)';", "question": "What is the accelerate of the car make amc hornet sportabout (sw)?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How much does the car accelerate that makes amc hornet sportabout (sw)?\n[SQL]:\n", "output": "SELECT T1.Accelerate FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Make = 'amc hornet sportabout (sw)';", "db_id": "car_1", "query": "SELECT T1.Accelerate FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Make = 'amc hornet sportabout (sw)';", "question": "How much does the car accelerate that makes amc hornet sportabout (sw)?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car makers are there in france?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId WHERE T2.CountryName = 'france';", "db_id": "car_1", "query": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId WHERE T2.CountryName = 'france';", "question": "How many car makers are there in france?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of makers of care in France?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId WHERE T2.CountryName = 'france';", "db_id": "car_1", "query": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN COUNTRIES AS T2 ON T1.Country = T2.CountryId WHERE T2.CountryName = 'france';", "question": "What is the number of makers of care in France?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car models are produced in the usa?\n[SQL]:\n", "output": "SELECT count(*) FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id JOIN COUNTRIES AS T3 ON T2.Country = T3.CountryId WHERE T3.CountryName = 'usa';", "db_id": "car_1", "query": "SELECT count(*) FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id JOIN COUNTRIES AS T3 ON T2.Country = T3.CountryId WHERE T3.CountryName = 'usa';", "question": "How many car models are produced in the usa?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the count of the car models produced in the United States?\n[SQL]:\n", "output": "SELECT count(*) FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id JOIN COUNTRIES AS T3 ON T2.Country = T3.CountryId WHERE T3.CountryName = 'usa';", "db_id": "car_1", "query": "SELECT count(*) FROM MODEL_LIST AS T1 JOIN CAR_MAKERS AS T2 ON T1.Maker = T2.Id JOIN COUNTRIES AS T3 ON T2.Country = T3.CountryId WHERE T3.CountryName = 'usa';", "question": "What is the count of the car models produced in the United States?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average miles per gallon(mpg) of the cars with 4 cylinders?\n[SQL]:\n", "output": "SELECT avg(mpg) FROM CARS_DATA WHERE Cylinders = 4;", "db_id": "car_1", "query": "SELECT avg(mpg) FROM CARS_DATA WHERE Cylinders = 4;", "question": "What is the average miles per gallon(mpg) of the cars with 4 cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average miles per gallon of all the cards with 4 cylinders?\n[SQL]:\n", "output": "SELECT avg(mpg) FROM CARS_DATA WHERE Cylinders = 4;", "db_id": "car_1", "query": "SELECT avg(mpg) FROM CARS_DATA WHERE Cylinders = 4;", "question": "What is the average miles per gallon of all the cards with 4 cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the smallest weight of the car produced with 8 cylinders on 1974 ?\n[SQL]:\n", "output": "select min(weight) from cars_data where cylinders = 8 and year = 1974", "db_id": "car_1", "query": "select min(weight) from cars_data where cylinders = 8 and year = 1974", "question": "What is the smallest weight of the car produced with 8 cylinders on 1974 ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the minimum weight of the car with 8 cylinders produced in 1974 ?\n[SQL]:\n", "output": "select min(weight) from cars_data where cylinders = 8 and year = 1974", "db_id": "car_1", "query": "select min(weight) from cars_data where cylinders = 8 and year = 1974", "question": "What is the minimum weight of the car with 8 cylinders produced in 1974 ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are all the makers and models?\n[SQL]:\n", "output": "SELECT Maker , Model FROM MODEL_LIST;", "db_id": "car_1", "query": "SELECT Maker , Model FROM MODEL_LIST;", "question": "What are all the makers and models?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the makers and models?\n[SQL]:\n", "output": "SELECT Maker , Model FROM MODEL_LIST;", "db_id": "car_1", "query": "SELECT Maker , Model FROM MODEL_LIST;", "question": "What are the makers and models?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the countries having at least one car maker? List name and id.\n[SQL]:\n", "output": "SELECT T1.CountryName , T1.CountryId FROM COUNTRIES AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.CountryId HAVING count(*) >= 1;", "db_id": "car_1", "query": "SELECT T1.CountryName , T1.CountryId FROM COUNTRIES AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.CountryId HAVING count(*) >= 1;", "question": "What are the countries having at least one car maker? List name and id.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names and ids of all countries with at least one car maker?\n[SQL]:\n", "output": "SELECT T1.CountryName , T1.CountryId FROM COUNTRIES AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.CountryId HAVING count(*) >= 1;", "db_id": "car_1", "query": "SELECT T1.CountryName , T1.CountryId FROM COUNTRIES AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.CountryId HAVING count(*) >= 1;", "question": "What are the names and ids of all countries with at least one car maker?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of the cars with horsepower more than 150?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE horsepower > 150;", "db_id": "car_1", "query": "SELECT count(*) FROM CARS_DATA WHERE horsepower > 150;", "question": "What is the number of the cars with horsepower more than 150?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of cars with a horsepower greater than 150?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE horsepower > 150;", "db_id": "car_1", "query": "SELECT count(*) FROM CARS_DATA WHERE horsepower > 150;", "question": "What is the number of cars with a horsepower greater than 150?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average weight of cars each year?\n[SQL]:\n", "output": "SELECT avg(Weight) , YEAR FROM CARS_DATA GROUP BY YEAR;", "db_id": "car_1", "query": "SELECT avg(Weight) , YEAR FROM CARS_DATA GROUP BY YEAR;", "question": "What is the average weight of cars each year?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average weight and year for each year?\n[SQL]:\n", "output": "SELECT avg(Weight) , YEAR FROM CARS_DATA GROUP BY YEAR;", "db_id": "car_1", "query": "SELECT avg(Weight) , YEAR FROM CARS_DATA GROUP BY YEAR;", "question": "What is the average weight and year for each year?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which countries in europe have at least 3 car manufacturers?\n[SQL]:\n", "output": "SELECT T1.CountryName FROM COUNTRIES AS T1 JOIN CONTINENTS AS T2 ON T1.Continent = T2.ContId JOIN CAR_MAKERS AS T3 ON T1.CountryId = T3.Country WHERE T2.Continent = 'europe' GROUP BY T1.CountryName HAVING count(*) >= 3;", "db_id": "car_1", "query": "SELECT T1.CountryName FROM COUNTRIES AS T1 JOIN CONTINENTS AS T2 ON T1.Continent = T2.ContId JOIN CAR_MAKERS AS T3 ON T1.CountryId = T3.Country WHERE T2.Continent = 'europe' GROUP BY T1.CountryName HAVING count(*) >= 3;", "question": "Which countries in europe have at least 3 car manufacturers?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names of all European countries with at least 3 manufacturers?\n[SQL]:\n", "output": "SELECT T1.CountryName FROM COUNTRIES AS T1 JOIN CONTINENTS AS T2 ON T1.Continent = T2.ContId JOIN CAR_MAKERS AS T3 ON T1.CountryId = T3.Country WHERE T2.Continent = 'europe' GROUP BY T1.CountryName HAVING count(*) >= 3;", "db_id": "car_1", "query": "SELECT T1.CountryName FROM COUNTRIES AS T1 JOIN CONTINENTS AS T2 ON T1.Continent = T2.ContId JOIN CAR_MAKERS AS T3 ON T1.CountryId = T3.Country WHERE T2.Continent = 'europe' GROUP BY T1.CountryName HAVING count(*) >= 3;", "question": "What are the names of all European countries with at least 3 manufacturers?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum horsepower and the make of the car models with 3 cylinders?\n[SQL]:\n", "output": "SELECT T2.horsepower , T1.Make FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.cylinders = 3 ORDER BY T2.horsepower DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T2.horsepower , T1.Make FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.cylinders = 3 ORDER BY T2.horsepower DESC LIMIT 1;", "question": "What is the maximum horsepower and the make of the car models with 3 cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the largest amount of horsepower for the models with 3 cylinders and what make is it?\n[SQL]:\n", "output": "SELECT T2.horsepower , T1.Make FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.cylinders = 3 ORDER BY T2.horsepower DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T2.horsepower , T1.Make FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.cylinders = 3 ORDER BY T2.horsepower DESC LIMIT 1;", "question": "What is the largest amount of horsepower for the models with 3 cylinders and what make is it?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which model saves the most gasoline? That is to say, have the maximum miles per gallon.\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.mpg DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id ORDER BY T2.mpg DESC LIMIT 1;", "question": "Which model saves the most gasoline? That is to say, have the maximum miles per gallon.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the car model with the highest mpg ?\n[SQL]:\n", "output": "select t1.model from car_names as t1 join cars_data as t2 on t1.makeid = t2.id order by t2.mpg desc limit 1;", "db_id": "car_1", "query": "select t1.model from car_names as t1 join cars_data as t2 on t1.makeid = t2.id order by t2.mpg desc limit 1;", "question": "What is the car model with the highest mpg ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average horsepower of the cars before 1980?\n[SQL]:\n", "output": "SELECT avg(horsepower) FROM CARS_DATA WHERE YEAR < 1980;", "db_id": "car_1", "query": "SELECT avg(horsepower) FROM CARS_DATA WHERE YEAR < 1980;", "question": "What is the average horsepower of the cars before 1980?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average horsepower for all cars produced before 1980 ?\n[SQL]:\n", "output": "select avg(horsepower) from cars_data where year < 1980;", "db_id": "car_1", "query": "select avg(horsepower) from cars_data where year < 1980;", "question": "What is the average horsepower for all cars produced before 1980 ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average edispl of the cars of model volvo?\n[SQL]:\n", "output": "SELECT avg(T2.edispl) FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T1.Model = 'volvo';", "db_id": "car_1", "query": "SELECT avg(T2.edispl) FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T1.Model = 'volvo';", "question": "What is the average edispl of the cars of model volvo?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the average edispl for all volvos?\n[SQL]:\n", "output": "SELECT avg(T2.edispl) FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T1.Model = 'volvo';", "db_id": "car_1", "query": "SELECT avg(T2.edispl) FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T1.Model = 'volvo';", "question": "What is the average edispl for all volvos?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum accelerate for different number of cylinders?\n[SQL]:\n", "output": "SELECT max(Accelerate) , Cylinders FROM CARS_DATA GROUP BY Cylinders;", "db_id": "car_1", "query": "SELECT max(Accelerate) , Cylinders FROM CARS_DATA GROUP BY Cylinders;", "question": "What is the maximum accelerate for different number of cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum accelerate for all the different cylinders?\n[SQL]:\n", "output": "SELECT max(Accelerate) , Cylinders FROM CARS_DATA GROUP BY Cylinders;", "db_id": "car_1", "query": "SELECT max(Accelerate) , Cylinders FROM CARS_DATA GROUP BY Cylinders;", "question": "What is the maximum accelerate for all the different cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which model has the most version(make) of cars?\n[SQL]:\n", "output": "SELECT Model FROM CAR_NAMES GROUP BY Model ORDER BY count(*) DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT Model FROM CAR_NAMES GROUP BY Model ORDER BY count(*) DESC LIMIT 1;", "question": "Which model has the most version(make) of cars?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What model has the most different versions?\n[SQL]:\n", "output": "SELECT Model FROM CAR_NAMES GROUP BY Model ORDER BY count(*) DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT Model FROM CAR_NAMES GROUP BY Model ORDER BY count(*) DESC LIMIT 1;", "question": "What model has the most different versions?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many cars have more than 4 cylinders?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE Cylinders > 4;", "db_id": "car_1", "query": "SELECT count(*) FROM CARS_DATA WHERE Cylinders > 4;", "question": "How many cars have more than 4 cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of cars with more than 4 cylinders?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE Cylinders > 4;", "db_id": "car_1", "query": "SELECT count(*) FROM CARS_DATA WHERE Cylinders > 4;", "question": "What is the number of cars with more than 4 cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:how many cars were produced in 1980?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE YEAR = 1980;", "db_id": "car_1", "query": "SELECT count(*) FROM CARS_DATA WHERE YEAR = 1980;", "question": "how many cars were produced in 1980?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:In 1980, how many cars were made?\n[SQL]:\n", "output": "SELECT count(*) FROM CARS_DATA WHERE YEAR = 1980;", "db_id": "car_1", "query": "SELECT count(*) FROM CARS_DATA WHERE YEAR = 1980;", "question": "In 1980, how many cars were made?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many car models were produced by the maker with full name American Motor Company?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker WHERE T1.FullName = 'American Motor Company';", "db_id": "car_1", "query": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker WHERE T1.FullName = 'American Motor Company';", "question": "How many car models were produced by the maker with full name American Motor Company?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of car models created by the car maker American Motor Company?\n[SQL]:\n", "output": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker WHERE T1.FullName = 'American Motor Company';", "db_id": "car_1", "query": "SELECT count(*) FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker WHERE T1.FullName = 'American Motor Company';", "question": "What is the number of car models created by the car maker American Motor Company?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which makers designed more than 3 car models? List full name and the id.\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) > 3;", "db_id": "car_1", "query": "SELECT T1.FullName , T1.Id FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) > 3;", "question": "Which makers designed more than 3 car models? List full name and the id.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names and ids of all makers with more than 3 models?\n[SQL]:\n", "output": "SELECT T1.FullName , T1.Id FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) > 3;", "db_id": "car_1", "query": "SELECT T1.FullName , T1.Id FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) > 3;", "question": "What are the names and ids of all makers with more than 3 models?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which distinctive models are produced by maker with the full name General Motors or weighing more than 3500?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Model FROM CAR_NAMES AS T1 JOIN MODEL_LIST AS T2 ON T1.Model = T2.Model JOIN CAR_MAKERS AS T3 ON T2.Maker = T3.Id JOIN CARS_DATA AS T4 ON T1.MakeId = T4.Id WHERE T3.FullName = 'General Motors' OR T4.weight > 3500;", "db_id": "car_1", "query": "SELECT DISTINCT T2.Model FROM CAR_NAMES AS T1 JOIN MODEL_LIST AS T2 ON T1.Model = T2.Model JOIN CAR_MAKERS AS T3 ON T2.Maker = T3.Id JOIN CARS_DATA AS T4 ON T1.MakeId = T4.Id WHERE T3.FullName = 'General Motors' OR T4.weight > 3500;", "question": "Which distinctive models are produced by maker with the full name General Motors or weighing more than 3500?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different models created by either the car maker General Motors or weighed more than 3500?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Model FROM CAR_NAMES AS T1 JOIN MODEL_LIST AS T2 ON T1.Model = T2.Model JOIN CAR_MAKERS AS T3 ON T2.Maker = T3.Id JOIN CARS_DATA AS T4 ON T1.MakeId = T4.Id WHERE T3.FullName = 'General Motors' OR T4.weight > 3500;", "db_id": "car_1", "query": "SELECT DISTINCT T2.Model FROM CAR_NAMES AS T1 JOIN MODEL_LIST AS T2 ON T1.Model = T2.Model JOIN CAR_MAKERS AS T3 ON T2.Maker = T3.Id JOIN CARS_DATA AS T4 ON T1.MakeId = T4.Id WHERE T3.FullName = 'General Motors' OR T4.weight > 3500;", "question": "What are the different models created by either the car maker General Motors or weighed more than 3500?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:In which years cars were produced weighing no less than 3000 and no more than 4000 ?\n[SQL]:\n", "output": "select distinct year from cars_data where weight between 3000 and 4000;", "db_id": "car_1", "query": "select distinct year from cars_data where weight between 3000 and 4000;", "question": "In which years cars were produced weighing no less than 3000 and no more than 4000 ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different years in which there were cars produced that weighed less than 4000 and also cars that weighted more than 3000 ?\n[SQL]:\n", "output": "select distinct year from cars_data where weight between 3000 and 4000;", "db_id": "car_1", "query": "select distinct year from cars_data where weight between 3000 and 4000;", "question": "What are the different years in which there were cars produced that weighed less than 4000 and also cars that weighted more than 3000 ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the horsepower of the car with the largest accelerate?\n[SQL]:\n", "output": "SELECT T1.horsepower FROM CARS_DATA AS T1 ORDER BY T1.accelerate DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.horsepower FROM CARS_DATA AS T1 ORDER BY T1.accelerate DESC LIMIT 1;", "question": "What is the horsepower of the car with the largest accelerate?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the horsepower of the car with the greatest accelerate?\n[SQL]:\n", "output": "SELECT T1.horsepower FROM CARS_DATA AS T1 ORDER BY T1.accelerate DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.horsepower FROM CARS_DATA AS T1 ORDER BY T1.accelerate DESC LIMIT 1;", "question": "What is the horsepower of the car with the greatest accelerate?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For model volvo, how many cylinders does the car with the least accelerate have?\n[SQL]:\n", "output": "SELECT T1.cylinders FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Model = 'volvo' ORDER BY T1.accelerate ASC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.cylinders FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Model = 'volvo' ORDER BY T1.accelerate ASC LIMIT 1;", "question": "For model volvo, how many cylinders does the car with the least accelerate have?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For a volvo model, how many cylinders does the version with least accelerate have?\n[SQL]:\n", "output": "SELECT T1.cylinders FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Model = 'volvo' ORDER BY T1.accelerate ASC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.cylinders FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T2.Model = 'volvo' ORDER BY T1.accelerate ASC LIMIT 1;", "question": "For a volvo model, how many cylinders does the version with least accelerate have?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many cars have a larger accelerate than the car with the largest horsepower?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Accelerate > ( SELECT Accelerate FROM CARS_DATA ORDER BY Horsepower DESC LIMIT 1 );", "db_id": "car_1", "query": "SELECT COUNT(*) FROM CARS_DATA WHERE Accelerate > ( SELECT Accelerate FROM CARS_DATA ORDER BY Horsepower DESC LIMIT 1 );", "question": "How many cars have a larger accelerate than the car with the largest horsepower?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of cars with a greater accelerate than the one with the most horsepower?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Accelerate > ( SELECT Accelerate FROM CARS_DATA ORDER BY Horsepower DESC LIMIT 1 );", "db_id": "car_1", "query": "SELECT COUNT(*) FROM CARS_DATA WHERE Accelerate > ( SELECT Accelerate FROM CARS_DATA ORDER BY Horsepower DESC LIMIT 1 );", "question": "What is the number of cars with a greater accelerate than the one with the most horsepower?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many countries has more than 2 car makers ?\n[SQL]:\n", "output": "select count(*) from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 2", "db_id": "car_1", "query": "select count(*) from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 2", "question": "How many countries has more than 2 car makers ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of countries with more than 2 car makers ?\n[SQL]:\n", "output": "select count(*) from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 2", "db_id": "car_1", "query": "select count(*) from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 2", "question": "What is the number of countries with more than 2 car makers ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:How many cars has over 6 cylinders?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Cylinders > 6;", "db_id": "car_1", "query": "SELECT COUNT(*) FROM CARS_DATA WHERE Cylinders > 6;", "question": "How many cars has over 6 cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the number of carsw ith over 6 cylinders?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM CARS_DATA WHERE Cylinders > 6;", "db_id": "car_1", "query": "SELECT COUNT(*) FROM CARS_DATA WHERE Cylinders > 6;", "question": "What is the number of carsw ith over 6 cylinders?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For the cars with 4 cylinders, which model has the largest horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Cylinders = 4 ORDER BY T2.horsepower DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Cylinders = 4 ORDER BY T2.horsepower DESC LIMIT 1;", "question": "For the cars with 4 cylinders, which model has the largest horsepower?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:For all of the 4 cylinder cars, which model has the most horsepower?\n[SQL]:\n", "output": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Cylinders = 4 ORDER BY T2.horsepower DESC LIMIT 1;", "db_id": "car_1", "query": "SELECT T1.Model FROM CAR_NAMES AS T1 JOIN CARS_DATA AS T2 ON T1.MakeId = T2.Id WHERE T2.Cylinders = 4 ORDER BY T2.horsepower DESC LIMIT 1;", "question": "For all of the 4 cylinder cars, which model has the most horsepower?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Among the cars with more than lowest horsepower, which ones do not have more than 3 cylinders? List the car makeid and make name.\n[SQL]:\n", "output": "SELECT T2.MakeId , T2.Make FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Horsepower > (SELECT min(Horsepower) FROM CARS_DATA) AND T1.Cylinders <= 3;", "db_id": "car_1", "query": "SELECT T2.MakeId , T2.Make FROM CARS_DATA AS T1 JOIN CAR_NAMES AS T2 ON T1.Id = T2.MakeId WHERE T1.Horsepower > (SELECT min(Horsepower) FROM CARS_DATA) AND T1.Cylinders <= 3;", "question": "Among the cars with more than lowest horsepower, which ones do not have more than 3 cylinders? List the car makeid and make name.", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Among the cars that do not have the minimum horsepower , what are the make ids and names of all those with less than 4 cylinders ?\n[SQL]:\n", "output": "select t2.makeid , t2.make from cars_data as t1 join car_names as t2 on t1.id = t2.makeid where t1.horsepower > (select min(horsepower) from cars_data) and t1.cylinders < 4;", "db_id": "car_1", "query": "select t2.makeid , t2.make from cars_data as t1 join car_names as t2 on t1.id = t2.makeid where t1.horsepower > (select min(horsepower) from cars_data) and t1.cylinders < 4;", "question": "Among the cars that do not have the minimum horsepower , what are the make ids and names of all those with less than 4 cylinders ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum miles per gallon of the car with 8 cylinders or produced before 1980 ?\n[SQL]:\n", "output": "select max(mpg) from cars_data where cylinders = 8 or year < 1980", "db_id": "car_1", "query": "select max(mpg) from cars_data where cylinders = 8 or year < 1980", "question": "What is the maximum miles per gallon of the car with 8 cylinders or produced before 1980 ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What is the maximum mpg of the cars that had 8 cylinders or that were produced before 1980 ?\n[SQL]:\n", "output": "select max(mpg) from cars_data where cylinders = 8 or year < 1980", "db_id": "car_1", "query": "select max(mpg) from cars_data where cylinders = 8 or year < 1980", "question": "What is the maximum mpg of the cars that had 8 cylinders or that were produced before 1980 ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which models are lighter than 3500 but not built by the 'Ford Motor Company'?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.Model = T2.Model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.Id JOIN CAR_MAKERS AS T4 ON T1.Maker = T4.Id WHERE T3.weight < 3500 AND T4.FullName != 'Ford Motor Company';", "db_id": "car_1", "query": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.Model = T2.Model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.Id JOIN CAR_MAKERS AS T4 ON T1.Maker = T4.Id WHERE T3.weight < 3500 AND T4.FullName != 'Ford Motor Company';", "question": "Which models are lighter than 3500 but not built by the 'Ford Motor Company'?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the different models wthat are lighter than 3500 but were not built by the Ford Motor Company?\n[SQL]:\n", "output": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.Model = T2.Model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.Id JOIN CAR_MAKERS AS T4 ON T1.Maker = T4.Id WHERE T3.weight < 3500 AND T4.FullName != 'Ford Motor Company';", "db_id": "car_1", "query": "SELECT DISTINCT T1.model FROM MODEL_LIST AS T1 JOIN CAR_NAMES AS T2 ON T1.Model = T2.Model JOIN CARS_DATA AS T3 ON T2.MakeId = T3.Id JOIN CAR_MAKERS AS T4 ON T1.Maker = T4.Id WHERE T3.weight < 3500 AND T4.FullName != 'Ford Motor Company';", "question": "What are the different models wthat are lighter than 3500 but were not built by the Ford Motor Company?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the name of the countries where there is not a single car maker?\n[SQL]:\n", "output": "SELECT CountryName FROM countries EXCEPT SELECT T1.CountryName FROM countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.countryId = T2.Country;", "db_id": "car_1", "query": "SELECT CountryName FROM countries EXCEPT SELECT T1.CountryName FROM countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.countryId = T2.Country;", "question": "What are the name of the countries where there is not a single car maker?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the names of the countries with no car makers?\n[SQL]:\n", "output": "SELECT CountryName FROM countries EXCEPT SELECT T1.CountryName FROM countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.countryId = T2.Country;", "db_id": "car_1", "query": "SELECT CountryName FROM countries EXCEPT SELECT T1.CountryName FROM countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.countryId = T2.Country;", "question": "What are the names of the countries with no car makers?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:Which are the car makers which produce at least 2 models and more than 3 car makers ? List the id and the maker .\n[SQL]:\n", "output": "select t1.id , t1.maker from car_makers as t1 join model_list as t2 on t1.id = t2.maker group by t1.id having count(*) >= 2 intersect select t1.id , t1.maker from car_makers as t1 join model_list as t2 on t1.id = t2.maker join car_names as t3 on t2.model = t3.model group by t1.id having count(*) > 3;", "db_id": "car_1", "query": "select t1.id , t1.maker from car_makers as t1 join model_list as t2 on t1.id = t2.maker group by t1.id having count(*) >= 2 intersect select t1.id , t1.maker from car_makers as t1 join model_list as t2 on t1.id = t2.maker join car_names as t3 on t2.model = t3.model group by t1.id having count(*) > 3;", "question": "Which are the car makers which produce at least 2 models and more than 3 car makers ? List the id and the maker .", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the ids and makers of all car makers that produce at least 2 models and make more than 3 cars?\n[SQL]:\n", "output": "SELECT T1.Id , T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) >= 2 INTERSECT SELECT T1.Id , T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model GROUP BY T1.Id HAVING count(*) > 3;", "db_id": "car_1", "query": "SELECT T1.Id , T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker GROUP BY T1.Id HAVING count(*) >= 2 INTERSECT SELECT T1.Id , T1.Maker FROM CAR_MAKERS AS T1 JOIN MODEL_LIST AS T2 ON T1.Id = T2.Maker JOIN CAR_NAMES AS T3 ON T2.model = T3.model GROUP BY T1.Id HAVING count(*) > 3;", "question": "What are the ids and makers of all car makers that produce at least 2 models and make more than 3 cars?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the id and names of the countries which have more than 3 car makers or produce the 'fiat' model?\n[SQL]:\n", "output": "SELECT T1.countryId , T1.CountryName FROM Countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.countryId HAVING count(*) > 3 UNION SELECT T1.countryId , T1.CountryName FROM Countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country JOIN MODEL_LIST AS T3 ON T2.Id = T3.Maker WHERE T3.Model = 'fiat';", "db_id": "car_1", "query": "SELECT T1.countryId , T1.CountryName FROM Countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country GROUP BY T1.countryId HAVING count(*) > 3 UNION SELECT T1.countryId , T1.CountryName FROM Countries AS T1 JOIN CAR_MAKERS AS T2 ON T1.CountryId = T2.Country JOIN MODEL_LIST AS T3 ON T2.Id = T3.Maker WHERE T3.Model = 'fiat';", "question": "What are the id and names of the countries which have more than 3 car makers or produce the 'fiat' model?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);\"\n[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id\"\n[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid\"\nAnswer the following question with a SQL Statement:What are the ids and names of all countries that either have more than 3 car makers or produce fiat model ?\n[SQL]:\n", "output": "select t1.countryid , t1.countryname from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 3 union select t1.countryid , t1.countryname from countries as t1 join car_makers as t2 on t1.countryid = t2.country join model_list as t3 on t2.id = t3.maker where t3.model = 'fiat';", "db_id": "car_1", "query": "select t1.countryid , t1.countryname from countries as t1 join car_makers as t2 on t1.countryid = t2.country group by t1.countryid having count(*) > 3 union select t1.countryid , t1.countryname from countries as t1 join car_makers as t2 on t1.countryid = t2.country join model_list as t3 on t2.id = t3.maker where t3.model = 'fiat';", "question": "What are the ids and names of all countries that either have more than 3 car makers or produce fiat model ?", "schema": "[Schema (values) (types)]: | car_1 | continents : contid (text) , continent (number) | countries : countryid (text) , countryname (number) , continent (text) | car_makers : id (text) , maker (number) , fullname (text) , country (number) | model_list : modelid (text) , maker (number) , model (text) | car_names : makeid (text) , model (number) , make (text) | cars_data : id (text) , mpg (number) , cylinders (text) , edispl (number) , horsepower (text) , weight (number) , accelerate (number) , year (text);", "primary_keys": "[Primary Keys]: continents : contid, countries : countryid, car_makers : id, model_list : modelid, car_names : makeid, cars_data : id", "foreign_keys": "[Foreign Keys]: countries : continent = continents : contid | car_makers : country = countries : countryid | model_list : maker = car_makers : id | car_names : model = model_list : model | cars_data : id = car_names : makeid"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which country does Airline \"JetBlue Airways\" belong to?\n[SQL]:\n", "output": "SELECT Country FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "db_id": "flight_2", "query": "SELECT Country FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "question": "Which country does Airline \"JetBlue Airways\" belong to?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What country is Jetblue Airways affiliated with?\n[SQL]:\n", "output": "SELECT Country FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "db_id": "flight_2", "query": "SELECT Country FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "question": "What country is Jetblue Airways affiliated with?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the abbreviation of Airline \"JetBlue Airways\"?\n[SQL]:\n", "output": "SELECT Abbreviation FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "db_id": "flight_2", "query": "SELECT Abbreviation FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "question": "What is the abbreviation of Airline \"JetBlue Airways\"?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which abbreviation corresponds to Jetblue Airways?\n[SQL]:\n", "output": "SELECT Abbreviation FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "db_id": "flight_2", "query": "SELECT Abbreviation FROM AIRLINES WHERE Airline = \"JetBlue Airways\"", "question": "Which abbreviation corresponds to Jetblue Airways?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:List all airline names and their abbreviations in \"USA\".\n[SQL]:\n", "output": "SELECT Airline , Abbreviation FROM AIRLINES WHERE Country = \"USA\"", "db_id": "flight_2", "query": "SELECT Airline , Abbreviation FROM AIRLINES WHERE Country = \"USA\"", "question": "List all airline names and their abbreviations in \"USA\".", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are the airline names and abbreviations for airlines in the USA?\n[SQL]:\n", "output": "SELECT Airline , Abbreviation FROM AIRLINES WHERE Country = \"USA\"", "db_id": "flight_2", "query": "SELECT Airline , Abbreviation FROM AIRLINES WHERE Country = \"USA\"", "question": "What are the airline names and abbreviations for airlines in the USA?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:List the airport code and name in the city of Anthony.\n[SQL]:\n", "output": "SELECT AirportCode , AirportName FROM AIRPORTS WHERE city = \"Anthony\"", "db_id": "flight_2", "query": "SELECT AirportCode , AirportName FROM AIRPORTS WHERE city = \"Anthony\"", "question": "List the airport code and name in the city of Anthony.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the airport code and airport name corresonding to the city Anthony.\n[SQL]:\n", "output": "SELECT AirportCode , AirportName FROM AIRPORTS WHERE city = \"Anthony\"", "db_id": "flight_2", "query": "SELECT AirportCode , AirportName FROM AIRPORTS WHERE city = \"Anthony\"", "question": "Give the airport code and airport name corresonding to the city Anthony.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many airlines do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES", "question": "How many airlines do we have?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the total number of airlines?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES", "question": "What is the total number of airlines?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many airports do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRPORTS", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRPORTS", "question": "How many airports do we have?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of airports.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRPORTS", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRPORTS", "question": "Return the number of airports.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS", "question": "How many flights do we have?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of flights.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS", "question": "Return the number of flights.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airline has abbreviation 'UAL'?\n[SQL]:\n", "output": "SELECT Airline FROM AIRLINES WHERE Abbreviation = \"UAL\"", "db_id": "flight_2", "query": "SELECT Airline FROM AIRLINES WHERE Abbreviation = \"UAL\"", "question": "Which airline has abbreviation 'UAL'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the airline with abbreviation 'UAL'.\n[SQL]:\n", "output": "SELECT Airline FROM AIRLINES WHERE Abbreviation = \"UAL\"", "db_id": "flight_2", "query": "SELECT Airline FROM AIRLINES WHERE Abbreviation = \"UAL\"", "question": "Give the airline with abbreviation 'UAL'.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many airlines are from USA?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES WHERE Country = \"USA\"", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES WHERE Country = \"USA\"", "question": "How many airlines are from USA?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of airlines in the USA.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES WHERE Country = \"USA\"", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES WHERE Country = \"USA\"", "question": "Return the number of airlines in the USA.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city and country is the Alton airport at?\n[SQL]:\n", "output": "SELECT City , Country FROM AIRPORTS WHERE AirportName = \"Alton\"", "db_id": "flight_2", "query": "SELECT City , Country FROM AIRPORTS WHERE AirportName = \"Alton\"", "question": "Which city and country is the Alton airport at?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the city and country for the Alton airport.\n[SQL]:\n", "output": "SELECT City , Country FROM AIRPORTS WHERE AirportName = \"Alton\"", "db_id": "flight_2", "query": "SELECT City , Country FROM AIRPORTS WHERE AirportName = \"Alton\"", "question": "Give the city and country for the Alton airport.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the airport name for airport 'AKO'?\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE AirportCode = \"AKO\"", "db_id": "flight_2", "query": "SELECT AirportName FROM AIRPORTS WHERE AirportCode = \"AKO\"", "question": "What is the airport name for airport 'AKO'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the name of the airport with code 'AKO'.\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE AirportCode = \"AKO\"", "db_id": "flight_2", "query": "SELECT AirportName FROM AIRPORTS WHERE AirportCode = \"AKO\"", "question": "Return the name of the airport with code 'AKO'.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are airport names at City 'Aberdeen'?\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT AirportName FROM AIRPORTS WHERE City = \"Aberdeen\"", "question": "What are airport names at City 'Aberdeen'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are the names of airports in Aberdeen?\n[SQL]:\n", "output": "SELECT AirportName FROM AIRPORTS WHERE City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT AirportName FROM AIRPORTS WHERE City = \"Aberdeen\"", "question": "What are the names of airports in Aberdeen?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights depart from 'APG'?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE SourceAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS WHERE SourceAirport = \"APG\"", "question": "How many flights depart from 'APG'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of flights departing from 'APG'.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE SourceAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS WHERE SourceAirport = \"APG\"", "question": "Count the number of flights departing from 'APG'.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights have destination ATO?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE DestAirport = \"ATO\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS WHERE DestAirport = \"ATO\"", "question": "How many flights have destination ATO?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of flights into ATO.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS WHERE DestAirport = \"ATO\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS WHERE DestAirport = \"ATO\"", "question": "Count the number of flights into ATO.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights depart from City Aberdeen?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "How many flights depart from City Aberdeen?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of flights departing from Aberdeen.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "Return the number of flights departing from Aberdeen.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights arriving in Aberdeen city?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "How many flights arriving in Aberdeen city?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of flights arriving in Aberdeen.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "Return the number of flights arriving in Aberdeen.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights depart from City 'Aberdeen' and have destination City 'Ashley'?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRPORTS AS T3 ON T1.SourceAirport = T3.AirportCode WHERE T2.City = \"Ashley\" AND T3.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRPORTS AS T3 ON T1.SourceAirport = T3.AirportCode WHERE T2.City = \"Ashley\" AND T3.City = \"Aberdeen\"", "question": "How many flights depart from City 'Aberdeen' and have destination City 'Ashley'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights fly from Aberdeen to Ashley?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRPORTS AS T3 ON T1.SourceAirport = T3.AirportCode WHERE T2.City = \"Ashley\" AND T3.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRPORTS AS T3 ON T1.SourceAirport = T3.AirportCode WHERE T2.City = \"Ashley\" AND T3.City = \"Aberdeen\"", "question": "How many flights fly from Aberdeen to Ashley?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights does airline 'JetBlue Airways' have?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T1.Airline = T2.uid WHERE T2.Airline = \"JetBlue Airways\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T1.Airline = T2.uid WHERE T2.Airline = \"JetBlue Airways\"", "question": "How many flights does airline 'JetBlue Airways' have?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the number of Jetblue Airways flights.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T1.Airline = T2.uid WHERE T2.Airline = \"JetBlue Airways\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T1.Airline = T2.uid WHERE T2.Airline = \"JetBlue Airways\"", "question": "Give the number of Jetblue Airways flights.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many 'United Airlines' flights go to Airport 'ASY'?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.DestAirport = \"ASY\"", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.DestAirport = \"ASY\"", "question": "How many 'United Airlines' flights go to Airport 'ASY'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of United Airlines flights arriving in ASY Airport.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.DestAirport = \"ASY\"", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.DestAirport = \"ASY\"", "question": "Count the number of United Airlines flights arriving in ASY Airport.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many 'United Airlines' flights depart from Airport 'AHD'?\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.SourceAirport = \"AHD\"", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.SourceAirport = \"AHD\"", "question": "How many 'United Airlines' flights depart from Airport 'AHD'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Return the number of United Airlines flights leaving from AHD Airport.\n[SQL]:\n", "output": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.SourceAirport = \"AHD\"", "db_id": "flight_2", "query": "SELECT count(*) FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T2.Airline = T1.uid WHERE T1.Airline = \"United Airlines\" AND T2.SourceAirport = \"AHD\"", "question": "Return the number of United Airlines flights leaving from AHD Airport.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many United Airlines flights go to City 'Aberdeen'?\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRLINES AS T3 ON T3.uid = T1.Airline WHERE T2.City = \"Aberdeen\" AND T3.Airline = \"United Airlines\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRLINES AS T3 ON T3.uid = T1.Airline WHERE T2.City = \"Aberdeen\" AND T3.Airline = \"United Airlines\"", "question": "How many United Airlines flights go to City 'Aberdeen'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Count the number of United Airlines flights that arrive in Aberdeen.\n[SQL]:\n", "output": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRLINES AS T3 ON T3.uid = T1.Airline WHERE T2.City = \"Aberdeen\" AND T3.Airline = \"United Airlines\"", "db_id": "flight_2", "query": "SELECT count(*) FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode JOIN AIRLINES AS T3 ON T3.uid = T1.Airline WHERE T2.City = \"Aberdeen\" AND T3.Airline = \"United Airlines\"", "question": "Count the number of United Airlines flights that arrive in Aberdeen.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city has most number of arriving flights?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "question": "Which city has most number of arriving flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city has the most frequent destination airport?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "question": "Which city has the most frequent destination airport?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city has most number of departing flights?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.SourceAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.SourceAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "question": "Which city has most number of departing flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which city is the most frequent source airport?\n[SQL]:\n", "output": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.SourceAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.City FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.SourceAirport GROUP BY T1.City ORDER BY count(*) DESC LIMIT 1", "question": "Which city is the most frequent source airport?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the code of airport that has the highest number of flights?\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) DESC LIMIT 1", "question": "What is the code of airport that has the highest number of flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the airport code of the airport with the most flights?\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) DESC LIMIT 1", "question": "What is the airport code of the airport with the most flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the code of airport that has fewest number of flights?\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) LIMIT 1", "question": "What is the code of airport that has fewest number of flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the code of the airport with the least flights.\n[SQL]:\n", "output": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.AirportCode FROM AIRPORTS AS T1 JOIN FLIGHTS AS T2 ON T1.AirportCode = T2.DestAirport OR T1.AirportCode = T2.SourceAirport GROUP BY T1.AirportCode ORDER BY count(*) LIMIT 1", "question": "Give the code of the airport with the least flights.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airline has most number of flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) DESC LIMIT 1", "question": "Which airline has most number of flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What airline serves the most flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) DESC LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) DESC LIMIT 1", "question": "What airline serves the most flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find the abbreviation and country of the airline that has fewest number of flights?\n[SQL]:\n", "output": "SELECT T1.Abbreviation , T1.Country FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.Abbreviation , T1.Country FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) LIMIT 1", "question": "Find the abbreviation and country of the airline that has fewest number of flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What is the abbreviation of the airilne has the fewest flights and what country is it in?\n[SQL]:\n", "output": "SELECT T1.Abbreviation , T1.Country FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) LIMIT 1", "db_id": "flight_2", "query": "SELECT T1.Abbreviation , T1.Country FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline ORDER BY count(*) LIMIT 1", "question": "What is the abbreviation of the airilne has the fewest flights and what country is it in?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are airlines that have some flight departing from airport 'AHD'?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"AHD\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"AHD\"", "question": "What are airlines that have some flight departing from airport 'AHD'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have a flight with source airport AHD?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"AHD\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"AHD\"", "question": "Which airlines have a flight with source airport AHD?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are airlines that have flights arriving at airport 'AHD'?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.DestAirport = \"AHD\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.DestAirport = \"AHD\"", "question": "What are airlines that have flights arriving at airport 'AHD'?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have a flight with destination airport AHD?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.DestAirport = \"AHD\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.DestAirport = \"AHD\"", "question": "Which airlines have a flight with destination airport AHD?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have flights from both airports 'APG' and 'CVO'.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\" INTERSECT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\" INTERSECT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\"", "question": "Find all airlines that have flights from both airports 'APG' and 'CVO'.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have departing flights from both APG and CVO airports?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\" INTERSECT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\" INTERSECT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\"", "question": "Which airlines have departing flights from both APG and CVO airports?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have flights from airport 'CVO' but not from 'APG'.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\" EXCEPT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\" EXCEPT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\"", "question": "Find all airlines that have flights from airport 'CVO' but not from 'APG'.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have departures from CVO but not from APG airports?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\" EXCEPT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"CVO\" EXCEPT SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline WHERE T2.SourceAirport = \"APG\"", "question": "Which airlines have departures from CVO but not from APG airports?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have at least 10 flights.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) > 10", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) > 10", "question": "Find all airlines that have at least 10 flights.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have at least 10 flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) > 10", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) > 10", "question": "Which airlines have at least 10 flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find all airlines that have fewer than 200 flights.\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) < 200", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) < 200", "question": "Find all airlines that have fewer than 200 flights.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airlines have less than 200 flights?\n[SQL]:\n", "output": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) < 200", "db_id": "flight_2", "query": "SELECT T1.Airline FROM AIRLINES AS T1 JOIN FLIGHTS AS T2 ON T1.uid = T2.Airline GROUP BY T1.Airline HAVING count(*) < 200", "question": "Which airlines have less than 200 flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of Airline \"United Airlines\"?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T2.uid = T1.Airline WHERE T2.Airline = \"United Airlines\"", "db_id": "flight_2", "query": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T2.uid = T1.Airline WHERE T2.Airline = \"United Airlines\"", "question": "What are flight numbers of Airline \"United Airlines\"?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which flight numbers correspond to United Airlines flights?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T2.uid = T1.Airline WHERE T2.Airline = \"United Airlines\"", "db_id": "flight_2", "query": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRLINES AS T2 ON T2.uid = T1.Airline WHERE T2.Airline = \"United Airlines\"", "question": "Which flight numbers correspond to United Airlines flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights departing from Airport \"APG\"?\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE SourceAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT FlightNo FROM FLIGHTS WHERE SourceAirport = \"APG\"", "question": "What are flight numbers of flights departing from Airport \"APG\"?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights leaving from APG.\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE SourceAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT FlightNo FROM FLIGHTS WHERE SourceAirport = \"APG\"", "question": "Give the flight numbers of flights leaving from APG.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights arriving at Airport \"APG\"?\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE DestAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT FlightNo FROM FLIGHTS WHERE DestAirport = \"APG\"", "question": "What are flight numbers of flights arriving at Airport \"APG\"?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights landing at APG.\n[SQL]:\n", "output": "SELECT FlightNo FROM FLIGHTS WHERE DestAirport = \"APG\"", "db_id": "flight_2", "query": "SELECT FlightNo FROM FLIGHTS WHERE DestAirport = \"APG\"", "question": "Give the flight numbers of flights landing at APG.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights departing from City \"Aberdeen \"?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "What are flight numbers of flights departing from City \"Aberdeen \"?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights leaving from Aberdeen.\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.SourceAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "Give the flight numbers of flights leaving from Aberdeen.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:What are flight numbers of flights arriving at City \"Aberdeen\"?\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "What are flight numbers of flights arriving at City \"Aberdeen\"?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Give the flight numbers of flights arriving in Aberdeen.\n[SQL]:\n", "output": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "db_id": "flight_2", "query": "SELECT T1.FlightNo FROM FLIGHTS AS T1 JOIN AIRPORTS AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.City = \"Aberdeen\"", "question": "Give the flight numbers of flights arriving in Aberdeen.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find the number of flights landing in the city of Aberdeen or Abilene.\n[SQL]:\n", "output": "SELECT count(*) FROM Flights AS T1 JOIN Airports AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.city = \"Aberdeen\" OR T2.city = \"Abilene\"", "db_id": "flight_2", "query": "SELECT count(*) FROM Flights AS T1 JOIN Airports AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.city = \"Aberdeen\" OR T2.city = \"Abilene\"", "question": "Find the number of flights landing in the city of Aberdeen or Abilene.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:How many flights land in Aberdeen or Abilene?\n[SQL]:\n", "output": "SELECT count(*) FROM Flights AS T1 JOIN Airports AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.city = \"Aberdeen\" OR T2.city = \"Abilene\"", "db_id": "flight_2", "query": "SELECT count(*) FROM Flights AS T1 JOIN Airports AS T2 ON T1.DestAirport = T2.AirportCode WHERE T2.city = \"Aberdeen\" OR T2.city = \"Abilene\"", "question": "How many flights land in Aberdeen or Abilene?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Find the name of airports which do not have any flight in and out.\n[SQL]:\n", "output": "SELECT AirportName FROM Airports WHERE AirportCode NOT IN (SELECT SourceAirport FROM Flights UNION SELECT DestAirport FROM Flights)", "db_id": "flight_2", "query": "SELECT AirportName FROM Airports WHERE AirportCode NOT IN (SELECT SourceAirport FROM Flights UNION SELECT DestAirport FROM Flights)", "question": "Find the name of airports which do not have any flight in and out.", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);\"\n[Primary Keys]: airlines : uid, airports : airportcode, flights : airline\"\n[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode\"\nAnswer the following question with a SQL Statement:Which airports do not have departing or arriving flights?\n[SQL]:\n", "output": "SELECT AirportName FROM Airports WHERE AirportCode NOT IN (SELECT SourceAirport FROM Flights UNION SELECT DestAirport FROM Flights)", "db_id": "flight_2", "query": "SELECT AirportName FROM Airports WHERE AirportCode NOT IN (SELECT SourceAirport FROM Flights UNION SELECT DestAirport FROM Flights)", "question": "Which airports do not have departing or arriving flights?", "schema": "[Schema (values) (types)]: | flight_2 | airlines : uid (text) , airline (number) , abbreviation (text) , country (text) | airports : city (text) , airportcode (number) , airportname (text) , country (text) , countryabbrev (text) | flights : airline (text) , flightno (number) , sourceairport (text) , destairport (text);", "primary_keys": "[Primary Keys]: airlines : uid, airports : airportcode, flights : airline", "foreign_keys": "[Foreign Keys]: flights : destairport = airports : airportcode | flights : sourceairport = airports : airportcode"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:How many employees are there?\n[SQL]:\n", "output": "SELECT count(*) FROM employee", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) FROM employee", "question": "How many employees are there?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Count the number of employees\n[SQL]:\n", "output": "SELECT count(*) FROM employee", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) FROM employee", "question": "Count the number of employees", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Sort employee names by their age in ascending order.\n[SQL]:\n", "output": "SELECT name FROM employee ORDER BY age", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM employee ORDER BY age", "question": "Sort employee names by their age in ascending order.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:List the names of employees and sort in ascending order of age.\n[SQL]:\n", "output": "SELECT name FROM employee ORDER BY age", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM employee ORDER BY age", "question": "List the names of employees and sort in ascending order of age.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is the number of employees from each city?\n[SQL]:\n", "output": "SELECT count(*) , city FROM employee GROUP BY city", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) , city FROM employee GROUP BY city", "question": "What is the number of employees from each city?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Count the number of employees for each city.\n[SQL]:\n", "output": "SELECT count(*) , city FROM employee GROUP BY city", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) , city FROM employee GROUP BY city", "question": "Count the number of employees for each city.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which cities do more than one employee under age 30 come from?\n[SQL]:\n", "output": "SELECT city FROM employee WHERE age < 30 GROUP BY city HAVING count(*) > 1", "db_id": "employee_hire_evaluation", "query": "SELECT city FROM employee WHERE age < 30 GROUP BY city HAVING count(*) > 1", "question": "Which cities do more than one employee under age 30 come from?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the cities that have more than one employee under age 30.\n[SQL]:\n", "output": "SELECT city FROM employee WHERE age < 30 GROUP BY city HAVING count(*) > 1", "db_id": "employee_hire_evaluation", "query": "SELECT city FROM employee WHERE age < 30 GROUP BY city HAVING count(*) > 1", "question": "Find the cities that have more than one employee under age 30.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the number of shops in each location.\n[SQL]:\n", "output": "SELECT count(*) , LOCATION FROM shop GROUP BY LOCATION", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) , LOCATION FROM shop GROUP BY LOCATION", "question": "Find the number of shops in each location.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:How many shops are there in each location?\n[SQL]:\n", "output": "SELECT count(*) , LOCATION FROM shop GROUP BY LOCATION", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) , LOCATION FROM shop GROUP BY LOCATION", "question": "How many shops are there in each location?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the manager name and district of the shop whose number of products is the largest.\n[SQL]:\n", "output": "SELECT manager_name , district FROM shop ORDER BY number_products DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT manager_name , district FROM shop ORDER BY number_products DESC LIMIT 1", "question": "Find the manager name and district of the shop whose number of products is the largest.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What are the manager name and district of the shop that sells the largest number of products?\n[SQL]:\n", "output": "SELECT manager_name , district FROM shop ORDER BY number_products DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT manager_name , district FROM shop ORDER BY number_products DESC LIMIT 1", "question": "What are the manager name and district of the shop that sells the largest number of products?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:find the minimum and maximum number of products of all stores.\n[SQL]:\n", "output": "SELECT min(Number_products) , max(Number_products) FROM shop", "db_id": "employee_hire_evaluation", "query": "SELECT min(Number_products) , max(Number_products) FROM shop", "question": "find the minimum and maximum number of products of all stores.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What are the minimum and maximum number of products across all the shops?\n[SQL]:\n", "output": "SELECT min(Number_products) , max(Number_products) FROM shop", "db_id": "employee_hire_evaluation", "query": "SELECT min(Number_products) , max(Number_products) FROM shop", "question": "What are the minimum and maximum number of products across all the shops?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Return the name, location and district of all shops in descending order of number of products.\n[SQL]:\n", "output": "SELECT name , LOCATION , district FROM shop ORDER BY number_products DESC", "db_id": "employee_hire_evaluation", "query": "SELECT name , LOCATION , district FROM shop ORDER BY number_products DESC", "question": "Return the name, location and district of all shops in descending order of number of products.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Sort all the shops by number products in descending order, and return the name, location and district of each shop.\n[SQL]:\n", "output": "SELECT name , LOCATION , district FROM shop ORDER BY number_products DESC", "db_id": "employee_hire_evaluation", "query": "SELECT name , LOCATION , district FROM shop ORDER BY number_products DESC", "question": "Sort all the shops by number products in descending order, and return the name, location and district of each shop.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the names of stores whose number products is more than the average number of products.\n[SQL]:\n", "output": "SELECT name FROM shop WHERE number_products > (SELECT avg(number_products) FROM shop)", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM shop WHERE number_products > (SELECT avg(number_products) FROM shop)", "question": "Find the names of stores whose number products is more than the average number of products.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which shops' number products is above the average? Give me the shop names.\n[SQL]:\n", "output": "SELECT name FROM shop WHERE number_products > (SELECT avg(number_products) FROM shop)", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM shop WHERE number_products > (SELECT avg(number_products) FROM shop)", "question": "Which shops' number products is above the average? Give me the shop names.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:find the name of employee who was awarded the most times in the evaluation.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID GROUP BY t2.Employee_ID ORDER BY count(*) DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID GROUP BY t2.Employee_ID ORDER BY count(*) DESC LIMIT 1", "question": "find the name of employee who was awarded the most times in the evaluation.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which employee received the most awards in evaluations? Give me the employee name.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID GROUP BY t2.Employee_ID ORDER BY count(*) DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID GROUP BY t2.Employee_ID ORDER BY count(*) DESC LIMIT 1", "question": "Which employee received the most awards in evaluations? Give me the employee name.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the name of the employee who got the highest one time bonus.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID ORDER BY t2.bonus DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID ORDER BY t2.bonus DESC LIMIT 1", "question": "Find the name of the employee who got the highest one time bonus.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which employee received the biggest bonus? Give me the employee name.\n[SQL]:\n", "output": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID ORDER BY t2.bonus DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT t1.name FROM employee AS t1 JOIN evaluation AS t2 ON t1.Employee_ID = t2.Employee_ID ORDER BY t2.bonus DESC LIMIT 1", "question": "Which employee received the biggest bonus? Give me the employee name.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the names of employees who never won any award in the evaluation.\n[SQL]:\n", "output": "SELECT name FROM employee WHERE Employee_ID NOT IN (SELECT Employee_ID FROM evaluation)", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM employee WHERE Employee_ID NOT IN (SELECT Employee_ID FROM evaluation)", "question": "Find the names of employees who never won any award in the evaluation.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What are the names of the employees who never received any evaluation?\n[SQL]:\n", "output": "SELECT name FROM employee WHERE Employee_ID NOT IN (SELECT Employee_ID FROM evaluation)", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM employee WHERE Employee_ID NOT IN (SELECT Employee_ID FROM evaluation)", "question": "What are the names of the employees who never received any evaluation?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is the name of the shop that is hiring the largest number of employees?\n[SQL]:\n", "output": "SELECT t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t1.shop_id ORDER BY count(*) DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t1.shop_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the name of the shop that is hiring the largest number of employees?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which shop has the most employees? Give me the shop name.\n[SQL]:\n", "output": "SELECT t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t1.shop_id ORDER BY count(*) DESC LIMIT 1", "db_id": "employee_hire_evaluation", "query": "SELECT t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t1.shop_id ORDER BY count(*) DESC LIMIT 1", "question": "Which shop has the most employees? Give me the shop name.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the name of the shops that do not hire any employee.\n[SQL]:\n", "output": "SELECT name FROM shop WHERE shop_id NOT IN (SELECT shop_id FROM hiring)", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM shop WHERE shop_id NOT IN (SELECT shop_id FROM hiring)", "question": "Find the name of the shops that do not hire any employee.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which shops run with no employees? Find the shop names\n[SQL]:\n", "output": "SELECT name FROM shop WHERE shop_id NOT IN (SELECT shop_id FROM hiring)", "db_id": "employee_hire_evaluation", "query": "SELECT name FROM shop WHERE shop_id NOT IN (SELECT shop_id FROM hiring)", "question": "Which shops run with no employees? Find the shop names", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the number of employees hired in each shop; show the shop name as well.\n[SQL]:\n", "output": "SELECT count(*) , t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t2.name", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) , t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t2.name", "question": "Find the number of employees hired in each shop; show the shop name as well.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:For each shop, return the number of employees working there and the name of the shop.\n[SQL]:\n", "output": "SELECT count(*) , t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t2.name", "db_id": "employee_hire_evaluation", "query": "SELECT count(*) , t2.name FROM hiring AS t1 JOIN shop AS t2 ON t1.shop_id = t2.shop_id GROUP BY t2.name", "question": "For each shop, return the number of employees working there and the name of the shop.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is total bonus given in all evaluations?\n[SQL]:\n", "output": "SELECT sum(bonus) FROM evaluation", "db_id": "employee_hire_evaluation", "query": "SELECT sum(bonus) FROM evaluation", "question": "What is total bonus given in all evaluations?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the total amount of bonus given in all the evaluations.\n[SQL]:\n", "output": "SELECT sum(bonus) FROM evaluation", "db_id": "employee_hire_evaluation", "query": "SELECT sum(bonus) FROM evaluation", "question": "Find the total amount of bonus given in all the evaluations.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Give me all the information about hiring.\n[SQL]:\n", "output": "SELECT * FROM hiring", "db_id": "employee_hire_evaluation", "query": "SELECT * FROM hiring", "question": "Give me all the information about hiring.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:What is all the information about hiring?\n[SQL]:\n", "output": "SELECT * FROM hiring", "db_id": "employee_hire_evaluation", "query": "SELECT * FROM hiring", "question": "What is all the information about hiring?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Which district has both stores with less than 3000 products and stores with more than 10000 products?\n[SQL]:\n", "output": "SELECT district FROM shop WHERE Number_products < 3000 INTERSECT SELECT district FROM shop WHERE Number_products > 10000", "db_id": "employee_hire_evaluation", "query": "SELECT district FROM shop WHERE Number_products < 3000 INTERSECT SELECT district FROM shop WHERE Number_products > 10000", "question": "Which district has both stores with less than 3000 products and stores with more than 10000 products?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Find the districts in which there are both shops selling less than 3000 products and shops selling more than 10000 products.\n[SQL]:\n", "output": "SELECT district FROM shop WHERE Number_products < 3000 INTERSECT SELECT district FROM shop WHERE Number_products > 10000", "db_id": "employee_hire_evaluation", "query": "SELECT district FROM shop WHERE Number_products < 3000 INTERSECT SELECT district FROM shop WHERE Number_products > 10000", "question": "Find the districts in which there are both shops selling less than 3000 products and shops selling more than 10000 products.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:How many different store locations are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT LOCATION) FROM shop", "db_id": "employee_hire_evaluation", "query": "SELECT count(DISTINCT LOCATION) FROM shop", "question": "How many different store locations are there?", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);\"\n[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id\"\n[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id\"\nAnswer the following question with a SQL Statement:Count the number of distinct store locations.\n[SQL]:\n", "output": "SELECT count(DISTINCT LOCATION) FROM shop", "db_id": "employee_hire_evaluation", "query": "SELECT count(DISTINCT LOCATION) FROM shop", "question": "Count the number of distinct store locations.", "schema": "[Schema (values) (types)]: | employee_hire_evaluation | employee : employee_id (text) , name (number) , age (text) , city (number) | shop : shop_id (text) , name (number) , location (text) , district (number) , number_products (text) , manager_name (number) | hiring : shop_id (text) , employee_id (number) , start_from (text) , is_full_time (number) | evaluation : employee_id (text) , year_awarded (number) , bonus (text);", "primary_keys": "[Primary Keys]: employee : employee_id, shop : shop_id, hiring : employee_id, evaluation : employee_id", "foreign_keys": "[Foreign Keys]: hiring : employee_id = employee : employee_id | hiring : shop_id = shop : shop_id | evaluation : employee_id = employee : employee_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many documents do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Documents", "question": "How many documents do we have?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of documents.\n[SQL]:\n", "output": "SELECT count(*) FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Documents", "question": "Count the number of documents.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:List document IDs, document names, and document descriptions for all documents.\n[SQL]:\n", "output": "SELECT document_id , document_name , document_description FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id , document_name , document_description FROM Documents", "question": "List document IDs, document names, and document descriptions for all documents.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids, names, and descriptions for all documents?\n[SQL]:\n", "output": "SELECT document_id , document_name , document_description FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id , document_name , document_description FROM Documents", "question": "What are the ids, names, and descriptions for all documents?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document name and template id for document with description with the letter 'w' in it?\n[SQL]:\n", "output": "SELECT document_name , template_id FROM Documents WHERE Document_Description LIKE \"%w%\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_name , template_id FROM Documents WHERE Document_Description LIKE \"%w%\"", "question": "What is the document name and template id for document with description with the letter 'w' in it?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the names and template ids for documents that contain the letter w in their description.\n[SQL]:\n", "output": "SELECT document_name , template_id FROM Documents WHERE Document_Description LIKE \"%w%\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_name , template_id FROM Documents WHERE Document_Description LIKE \"%w%\"", "question": "Return the names and template ids for documents that contain the letter w in their description.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id, template id and description for document named \"Robbin CV\"?\n[SQL]:\n", "output": "SELECT document_id , template_id , Document_Description FROM Documents WHERE document_name = \"Robbin CV\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id , template_id , Document_Description FROM Documents WHERE document_name = \"Robbin CV\"", "question": "What is the document id, template id and description for document named \"Robbin CV\"?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the document id, template id, and description for the document with the name Robbin CV.\n[SQL]:\n", "output": "SELECT document_id , template_id , Document_Description FROM Documents WHERE document_name = \"Robbin CV\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id , template_id , Document_Description FROM Documents WHERE document_name = \"Robbin CV\"", "question": "Return the document id, template id, and description for the document with the name Robbin CV.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many different templates do all document use?\n[SQL]:\n", "output": "SELECT count(DISTINCT template_id) FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(DISTINCT template_id) FROM Documents", "question": "How many different templates do all document use?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of different templates used for documents.\n[SQL]:\n", "output": "SELECT count(DISTINCT template_id) FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(DISTINCT template_id) FROM Documents", "question": "Count the number of different templates used for documents.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many documents are using the template with type code 'PPT'?\n[SQL]:\n", "output": "SELECT count(*) FROM Documents AS T1 JOIN Templates AS T2 ON T1.Template_ID = T2.Template_ID WHERE T2.Template_Type_Code = 'PPT'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Documents AS T1 JOIN Templates AS T2 ON T1.Template_ID = T2.Template_ID WHERE T2.Template_Type_Code = 'PPT'", "question": "How many documents are using the template with type code 'PPT'?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of documents that use the PPT template type.\n[SQL]:\n", "output": "SELECT count(*) FROM Documents AS T1 JOIN Templates AS T2 ON T1.Template_ID = T2.Template_ID WHERE T2.Template_Type_Code = 'PPT'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Documents AS T1 JOIN Templates AS T2 ON T1.Template_ID = T2.Template_ID WHERE T2.Template_Type_Code = 'PPT'", "question": "Count the number of documents that use the PPT template type.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template ids and number of documents using each template.\n[SQL]:\n", "output": "SELECT template_id , count(*) FROM Documents GROUP BY template_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id , count(*) FROM Documents GROUP BY template_id", "question": "Show all template ids and number of documents using each template.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are all different template ids used for documents, and how many times were each of them used?\n[SQL]:\n", "output": "SELECT template_id , count(*) FROM Documents GROUP BY template_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id , count(*) FROM Documents GROUP BY template_id", "question": "What are all different template ids used for documents, and how many times were each of them used?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the id and type code for the template used by the most documents?\n[SQL]:\n", "output": "SELECT T1.template_id , T2.Template_Type_Code FROM Documents AS T1 JOIN Templates AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_id ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_id , T2.Template_Type_Code FROM Documents AS T1 JOIN Templates AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the id and type code for the template used by the most documents?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the id and type code of the template that is used for the greatest number of documents.\n[SQL]:\n", "output": "SELECT T1.template_id , T2.Template_Type_Code FROM Documents AS T1 JOIN Templates AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_id ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_id , T2.Template_Type_Code FROM Documents AS T1 JOIN Templates AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_id ORDER BY count(*) DESC LIMIT 1", "question": "Return the id and type code of the template that is used for the greatest number of documents.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show ids for all templates that are used by more than one document.\n[SQL]:\n", "output": "SELECT template_id FROM Documents GROUP BY template_id HAVING count(*) > 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id FROM Documents GROUP BY template_id HAVING count(*) > 1", "question": "Show ids for all templates that are used by more than one document.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the template ids of any templates used in more than a single document?\n[SQL]:\n", "output": "SELECT template_id FROM Documents GROUP BY template_id HAVING count(*) > 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id FROM Documents GROUP BY template_id HAVING count(*) > 1", "question": "What are the template ids of any templates used in more than a single document?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show ids for all templates not used by any document.\n[SQL]:\n", "output": "SELECT template_id FROM Templates EXCEPT SELECT template_id FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id FROM Templates EXCEPT SELECT template_id FROM Documents", "question": "Show ids for all templates not used by any document.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids for templates that are not used in any documents?\n[SQL]:\n", "output": "SELECT template_id FROM Templates EXCEPT SELECT template_id FROM Documents", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id FROM Templates EXCEPT SELECT template_id FROM Documents", "question": "What are the ids for templates that are not used in any documents?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many templates do we have?\n[SQL]:\n", "output": "SELECT count(*) FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Templates", "question": "How many templates do we have?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of templates.\n[SQL]:\n", "output": "SELECT count(*) FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Templates", "question": "Count the number of templates.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show template ids, version numbers, and template type codes for all templates.\n[SQL]:\n", "output": "SELECT template_id , version_number , template_type_code FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id , version_number , template_type_code FROM Templates", "question": "Show template ids, version numbers, and template type codes for all templates.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids, version numbers, and type codes for each template?\n[SQL]:\n", "output": "SELECT template_id , version_number , template_type_code FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id , version_number , template_type_code FROM Templates", "question": "What are the ids, version numbers, and type codes for each template?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all distinct template type codes for all templates.\n[SQL]:\n", "output": "SELECT DISTINCT template_type_code FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT DISTINCT template_type_code FROM Templates", "question": "Show all distinct template type codes for all templates.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the different template type codes?\n[SQL]:\n", "output": "SELECT DISTINCT template_type_code FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT DISTINCT template_type_code FROM Templates", "question": "What are the different template type codes?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids of templates with template type code PP or PPT?\n[SQL]:\n", "output": "SELECT template_id FROM Templates WHERE template_type_code = \"PP\" OR template_type_code = \"PPT\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id FROM Templates WHERE template_type_code = \"PP\" OR template_type_code = \"PPT\"", "question": "What are the ids of templates with template type code PP or PPT?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the ids of templates that have the code PP or PPT.\n[SQL]:\n", "output": "SELECT template_id FROM Templates WHERE template_type_code = \"PP\" OR template_type_code = \"PPT\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_id FROM Templates WHERE template_type_code = \"PP\" OR template_type_code = \"PPT\"", "question": "Return the ids of templates that have the code PP or PPT.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many templates have template type code CV?\n[SQL]:\n", "output": "SELECT count(*) FROM Templates WHERE template_type_code = \"CV\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Templates WHERE template_type_code = \"CV\"", "question": "How many templates have template type code CV?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of templates of the type CV.\n[SQL]:\n", "output": "SELECT count(*) FROM Templates WHERE template_type_code = \"CV\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Templates WHERE template_type_code = \"CV\"", "question": "Count the number of templates of the type CV.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the version number and template type code for the template with version number later than 5?\n[SQL]:\n", "output": "SELECT version_number , template_type_code FROM Templates WHERE version_number > 5", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT version_number , template_type_code FROM Templates WHERE version_number > 5", "question": "What is the version number and template type code for the template with version number later than 5?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the version numbers and template type codes of templates with a version number greater than 5.\n[SQL]:\n", "output": "SELECT version_number , template_type_code FROM Templates WHERE version_number > 5", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT version_number , template_type_code FROM Templates WHERE version_number > 5", "question": "Return the version numbers and template type codes of templates with a version number greater than 5.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes and number of templates for each.\n[SQL]:\n", "output": "SELECT template_type_code , count(*) FROM Templates GROUP BY template_type_code", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code , count(*) FROM Templates GROUP BY template_type_code", "question": "Show all template type codes and number of templates for each.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the different template type codes, and how many templates correspond to each?\n[SQL]:\n", "output": "SELECT template_type_code , count(*) FROM Templates GROUP BY template_type_code", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code , count(*) FROM Templates GROUP BY template_type_code", "question": "What are the different template type codes, and how many templates correspond to each?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Which template type code has most number of templates?\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Templates GROUP BY template_type_code ORDER BY count(*) DESC LIMIT 1", "question": "Which template type code has most number of templates?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the type code of the template type that the most templates belong to.\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Templates GROUP BY template_type_code ORDER BY count(*) DESC LIMIT 1", "question": "Return the type code of the template type that the most templates belong to.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes with less than three templates.\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code HAVING count(*) < 3", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Templates GROUP BY template_type_code HAVING count(*) < 3", "question": "Show all template type codes with less than three templates.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the codes of template types that have fewer than 3 templates?\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates GROUP BY template_type_code HAVING count(*) < 3", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Templates GROUP BY template_type_code HAVING count(*) < 3", "question": "What are the codes of template types that have fewer than 3 templates?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What the smallest version number and its template type code?\n[SQL]:\n", "output": "SELECT min(Version_Number) , template_type_code FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT min(Version_Number) , template_type_code FROM Templates", "question": "What the smallest version number and its template type code?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the lowest version number, along with its corresponding template type code.\n[SQL]:\n", "output": "SELECT min(Version_Number) , template_type_code FROM Templates", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT min(Version_Number) , template_type_code FROM Templates", "question": "Return the lowest version number, along with its corresponding template type code.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the template type code of the template used by document with the name \"Data base\"?\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T2.document_name = \"Data base\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T2.document_name = \"Data base\"", "question": "What is the template type code of the template used by document with the name \"Data base\"?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the template type code of the template that is used by a document named Data base.\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T2.document_name = \"Data base\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T2.document_name = \"Data base\"", "question": "Return the template type code of the template that is used by a document named Data base.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all document names using templates with template type code BK.\n[SQL]:\n", "output": "SELECT T2.document_name FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T1.template_type_code = \"BK\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T2.document_name FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T1.template_type_code = \"BK\"", "question": "Show all document names using templates with template type code BK.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the names of documents that use templates with the code BK?\n[SQL]:\n", "output": "SELECT T2.document_name FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T1.template_type_code = \"BK\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T2.document_name FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id WHERE T1.template_type_code = \"BK\"", "question": "What are the names of documents that use templates with the code BK?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes and the number of documents using each type.\n[SQL]:\n", "output": "SELECT T1.template_type_code , count(*) FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_type_code , count(*) FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code", "question": "Show all template type codes and the number of documents using each type.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the different template type codes, and how many documents use each type?\n[SQL]:\n", "output": "SELECT T1.template_type_code , count(*) FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_type_code , count(*) FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code", "question": "What are the different template type codes, and how many documents use each type?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Which template type code is used by most number of documents?\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code ORDER BY count(*) DESC LIMIT 1", "question": "Which template type code is used by most number of documents?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the code of the template type that is most commonly used in documents.\n[SQL]:\n", "output": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id GROUP BY T1.template_type_code ORDER BY count(*) DESC LIMIT 1", "question": "Return the code of the template type that is most commonly used in documents.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes that are not used by any document.\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates EXCEPT SELECT template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Templates EXCEPT SELECT template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id", "question": "Show all template type codes that are not used by any document.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the codes of template types that are not used for any document?\n[SQL]:\n", "output": "SELECT template_type_code FROM Templates EXCEPT SELECT template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Templates EXCEPT SELECT template_type_code FROM Templates AS T1 JOIN Documents AS T2 ON T1.template_id = T2.template_id", "question": "What are the codes of template types that are not used for any document?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all template type codes and descriptions.\n[SQL]:\n", "output": "SELECT template_type_code , template_type_description FROM Ref_template_types", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code , template_type_description FROM Ref_template_types", "question": "Show all template type codes and descriptions.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the type codes and descriptions for all template types?\n[SQL]:\n", "output": "SELECT template_type_code , template_type_description FROM Ref_template_types", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code , template_type_description FROM Ref_template_types", "question": "What are the type codes and descriptions for all template types?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the template type descriptions for template type code \"AD\".\n[SQL]:\n", "output": "SELECT template_type_description FROM Ref_template_types WHERE template_type_code = \"AD\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_description FROM Ref_template_types WHERE template_type_code = \"AD\"", "question": "What is the template type descriptions for template type code \"AD\".", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the template type description of the template type with the code AD.\n[SQL]:\n", "output": "SELECT template_type_description FROM Ref_template_types WHERE template_type_code = \"AD\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_description FROM Ref_template_types WHERE template_type_code = \"AD\"", "question": "Return the template type description of the template type with the code AD.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the template type code for template type description \"Book\".\n[SQL]:\n", "output": "SELECT template_type_code FROM Ref_template_types WHERE template_type_description = \"Book\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Ref_template_types WHERE template_type_description = \"Book\"", "question": "What is the template type code for template type description \"Book\".", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the type code of the template type with the description \"Book\".\n[SQL]:\n", "output": "SELECT template_type_code FROM Ref_template_types WHERE template_type_description = \"Book\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT template_type_code FROM Ref_template_types WHERE template_type_description = \"Book\"", "question": "Return the type code of the template type with the description \"Book\".", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the distinct template type descriptions for the templates ever used by any document?\n[SQL]:\n", "output": "SELECT DISTINCT T1.template_type_description FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code JOIN Documents AS T3 ON T2.Template_ID = T3.template_ID", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT DISTINCT T1.template_type_description FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code JOIN Documents AS T3 ON T2.Template_ID = T3.template_ID", "question": "What are the distinct template type descriptions for the templates ever used by any document?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the different descriptions for templates that have been used in a document.\n[SQL]:\n", "output": "SELECT DISTINCT T1.template_type_description FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code JOIN Documents AS T3 ON T2.Template_ID = T3.template_ID", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT DISTINCT T1.template_type_description FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code JOIN Documents AS T3 ON T2.Template_ID = T3.template_ID", "question": "Return the different descriptions for templates that have been used in a document.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the template ids with template type description \"Presentation\".\n[SQL]:\n", "output": "SELECT T2.template_id FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code WHERE T1.template_type_description = \"Presentation\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T2.template_id FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code WHERE T1.template_type_description = \"Presentation\"", "question": "What are the template ids with template type description \"Presentation\".", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the ids corresponding to templates with the description 'Presentation'.\n[SQL]:\n", "output": "SELECT T2.template_id FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code WHERE T1.template_type_description = \"Presentation\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T2.template_id FROM Ref_template_types AS T1 JOIN Templates AS T2 ON T1.template_type_code = T2.template_type_code WHERE T1.template_type_description = \"Presentation\"", "question": "Return the ids corresponding to templates with the description 'Presentation'.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many paragraphs in total?\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Paragraphs", "question": "How many paragraphs in total?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of paragraphs.\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Paragraphs", "question": "Count the number of paragraphs.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:How many paragraphs for the document with name 'Summer Show'?\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_ID = T2.document_ID WHERE T2.document_name = 'Summer Show'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_ID = T2.document_ID WHERE T2.document_name = 'Summer Show'", "question": "How many paragraphs for the document with name 'Summer Show'?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Count the number of paragraphs in the document named 'Summer Show'.\n[SQL]:\n", "output": "SELECT count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_ID = T2.document_ID WHERE T2.document_name = 'Summer Show'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_ID = T2.document_ID WHERE T2.document_name = 'Summer Show'", "question": "Count the number of paragraphs in the document named 'Summer Show'.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show paragraph details for paragraph with text 'Korea ' .\n[SQL]:\n", "output": "select other_details from paragraphs where paragraph_text like 'korea'", "db_id": "cre_Doc_Template_Mgt", "query": "select other_details from paragraphs where paragraph_text like 'korea'", "question": "Show paragraph details for paragraph with text 'Korea ' .", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the details for the paragraph that includes the text 'Korea ' ?\n[SQL]:\n", "output": "select other_details from paragraphs where paragraph_text like 'korea'", "db_id": "cre_Doc_Template_Mgt", "query": "select other_details from paragraphs where paragraph_text like 'korea'", "question": "What are the details for the paragraph that includes the text 'Korea ' ?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all paragraph ids and texts for the document with name 'Welcome to NY'.\n[SQL]:\n", "output": "SELECT T1.paragraph_id , T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.Document_Name = 'Welcome to NY'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.paragraph_id , T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.Document_Name = 'Welcome to NY'", "question": "Show all paragraph ids and texts for the document with name 'Welcome to NY'.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids and texts of paragraphs in the document titled 'Welcome to NY'?\n[SQL]:\n", "output": "SELECT T1.paragraph_id , T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.Document_Name = 'Welcome to NY'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.paragraph_id , T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.Document_Name = 'Welcome to NY'", "question": "What are the ids and texts of paragraphs in the document titled 'Welcome to NY'?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all paragraph texts for the document \"Customer reviews\".\n[SQL]:\n", "output": "SELECT T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.document_name = \"Customer reviews\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.document_name = \"Customer reviews\"", "question": "Show all paragraph texts for the document \"Customer reviews\".", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the paragraph texts for the document with the name 'Customer reviews'?\n[SQL]:\n", "output": "SELECT T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.document_name = \"Customer reviews\"", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.paragraph_text FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id WHERE T2.document_name = \"Customer reviews\"", "question": "What are the paragraph texts for the document with the name 'Customer reviews'?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all document ids and the number of paragraphs in each document. Order by document id.\n[SQL]:\n", "output": "SELECT document_id , count(*) FROM Paragraphs GROUP BY document_id ORDER BY document_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id , count(*) FROM Paragraphs GROUP BY document_id ORDER BY document_id", "question": "Show all document ids and the number of paragraphs in each document. Order by document id.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the different document ids along with the number of paragraphs corresponding to each, ordered by id.\n[SQL]:\n", "output": "SELECT document_id , count(*) FROM Paragraphs GROUP BY document_id ORDER BY document_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id , count(*) FROM Paragraphs GROUP BY document_id ORDER BY document_id", "question": "Return the different document ids along with the number of paragraphs corresponding to each, ordered by id.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show all document ids, names and the number of paragraphs in each document.\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name , count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.document_id , T2.document_name , count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id", "question": "Show all document ids, names and the number of paragraphs in each document.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids and names of each document, as well as the number of paragraphs in each?\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name , count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.document_id , T2.document_name , count(*) FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id", "question": "What are the ids and names of each document, as well as the number of paragraphs in each?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:List all document ids with at least two paragraphs.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) >= 2", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) >= 2", "question": "List all document ids with at least two paragraphs.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids of documents that have 2 or more paragraphs?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) >= 2", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) >= 2", "question": "What are the ids of documents that have 2 or more paragraphs?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id and name with greatest number of paragraphs?\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.document_id , T2.document_name FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the document id and name with greatest number of paragraphs?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the id and name of the document with the most paragraphs.\n[SQL]:\n", "output": "SELECT T1.document_id , T2.document_name FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id ORDER BY count(*) DESC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT T1.document_id , T2.document_name FROM Paragraphs AS T1 JOIN Documents AS T2 ON T1.document_id = T2.document_id GROUP BY T1.document_id ORDER BY count(*) DESC LIMIT 1", "question": "Return the id and name of the document with the most paragraphs.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id with least number of paragraphs?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id ORDER BY count(*) ASC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs GROUP BY document_id ORDER BY count(*) ASC LIMIT 1", "question": "What is the document id with least number of paragraphs?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Return the id of the document with the fewest paragraphs.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id ORDER BY count(*) ASC LIMIT 1", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs GROUP BY document_id ORDER BY count(*) ASC LIMIT 1", "question": "Return the id of the document with the fewest paragraphs.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What is the document id with 1 to 2 paragraphs?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) BETWEEN 1 AND 2", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) BETWEEN 1 AND 2", "question": "What is the document id with 1 to 2 paragraphs?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Give the ids of documents that have between one and two paragraphs.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) BETWEEN 1 AND 2", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs GROUP BY document_id HAVING count(*) BETWEEN 1 AND 2", "question": "Give the ids of documents that have between one and two paragraphs.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:Show the document id with paragraph text 'Brazil' and 'Ireland'.\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Brazil' INTERSECT SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Ireland'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Brazil' INTERSECT SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Ireland'", "question": "Show the document id with paragraph text 'Brazil' and 'Ireland'.", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);\"\n[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id\"\n[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id\"\nAnswer the following question with a SQL Statement:What are the ids of documents that contain the paragraph text 'Brazil' and 'Ireland'?\n[SQL]:\n", "output": "SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Brazil' INTERSECT SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Ireland'", "db_id": "cre_Doc_Template_Mgt", "query": "SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Brazil' INTERSECT SELECT document_id FROM Paragraphs WHERE paragraph_text = 'Ireland'", "question": "What are the ids of documents that contain the paragraph text 'Brazil' and 'Ireland'?", "schema": "[Schema (values) (types)]: | cre_Doc_Template_Mgt | Ref_Template_Types : template_type_code (text) , template_type_description (text) | Templates : template_id (text) , version_number (text) , template_type_code (text) , date_effective_from (number) , date_effective_to (number) , template_details (text) | Documents : document_id (text) , template_id (text) , document_name (text) , document_description (number) , other_details (number) | Paragraphs : paragraph_id (text) , document_id (text) , paragraph_text (text) , other_details (number);", "primary_keys": "[Primary Keys]: ref_template_types : template_type_code, templates : template_id, documents : document_id, paragraphs : paragraph_id", "foreign_keys": "[Foreign Keys]: templates : template_type_code = ref_template_types : template_type_code | documents : template_id = templates : template_id | paragraphs : document_id = documents : document_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:How many teachers are there?\n[SQL]:\n", "output": "SELECT count(*) FROM teacher", "db_id": "course_teach", "query": "SELECT count(*) FROM teacher", "question": "How many teachers are there?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the total count of teachers?\n[SQL]:\n", "output": "SELECT count(*) FROM teacher", "db_id": "course_teach", "query": "SELECT count(*) FROM teacher", "question": "What is the total count of teachers?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the names of teachers in ascending order of age.\n[SQL]:\n", "output": "SELECT Name FROM teacher ORDER BY Age ASC", "db_id": "course_teach", "query": "SELECT Name FROM teacher ORDER BY Age ASC", "question": "List the names of teachers in ascending order of age.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers ordered by ascending age?\n[SQL]:\n", "output": "SELECT Name FROM teacher ORDER BY Age ASC", "db_id": "course_teach", "query": "SELECT Name FROM teacher ORDER BY Age ASC", "question": "What are the names of the teachers ordered by ascending age?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the age and hometown of teachers?\n[SQL]:\n", "output": "SELECT Age , Hometown FROM teacher", "db_id": "course_teach", "query": "SELECT Age , Hometown FROM teacher", "question": "What are the age and hometown of teachers?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the age and hometown of every teacher?\n[SQL]:\n", "output": "SELECT Age , Hometown FROM teacher", "db_id": "course_teach", "query": "SELECT Age , Hometown FROM teacher", "question": "What is the age and hometown of every teacher?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the name of teachers whose hometown is not `` Little Lever Urban District '' .\n[SQL]:\n", "output": "select name from teacher where hometown != \"little lever urban district\"", "db_id": "course_teach", "query": "select name from teacher where hometown != \"little lever urban district\"", "question": "List the name of teachers whose hometown is not `` Little Lever Urban District '' .", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers whose hometown is not `` Little Lever Urban District '' ?\n[SQL]:\n", "output": "select name from teacher where hometown != \"little lever urban district\"", "db_id": "course_teach", "query": "select name from teacher where hometown != \"little lever urban district\"", "question": "What are the names of the teachers whose hometown is not `` Little Lever Urban District '' ?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show the name of teachers aged either 32 or 33?\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Age = 32 OR Age = 33", "db_id": "course_teach", "query": "SELECT Name FROM teacher WHERE Age = 32 OR Age = 33", "question": "Show the name of teachers aged either 32 or 33?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers who are aged either 32 or 33?\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Age = 32 OR Age = 33", "db_id": "course_teach", "query": "SELECT Name FROM teacher WHERE Age = 32 OR Age = 33", "question": "What are the names of the teachers who are aged either 32 or 33?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the hometown of the youngest teacher?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher ORDER BY Age ASC LIMIT 1", "db_id": "course_teach", "query": "SELECT Hometown FROM teacher ORDER BY Age ASC LIMIT 1", "question": "What is the hometown of the youngest teacher?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Where is the youngest teacher from?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher ORDER BY Age ASC LIMIT 1", "db_id": "course_teach", "query": "SELECT Hometown FROM teacher ORDER BY Age ASC LIMIT 1", "question": "Where is the youngest teacher from?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show different hometown of teachers and the number of teachers from each hometown.\n[SQL]:\n", "output": "SELECT Hometown , COUNT(*) FROM teacher GROUP BY Hometown", "db_id": "course_teach", "query": "SELECT Hometown , COUNT(*) FROM teacher GROUP BY Hometown", "question": "Show different hometown of teachers and the number of teachers from each hometown.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:For each hometown, how many teachers are there?\n[SQL]:\n", "output": "SELECT Hometown , COUNT(*) FROM teacher GROUP BY Hometown", "db_id": "course_teach", "query": "SELECT Hometown , COUNT(*) FROM teacher GROUP BY Hometown", "question": "For each hometown, how many teachers are there?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the most common hometown of teachers.\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "course_teach", "query": "SELECT Hometown FROM teacher GROUP BY Hometown ORDER BY COUNT(*) DESC LIMIT 1", "question": "List the most common hometown of teachers.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the most commmon hometowns for teachers?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "course_teach", "query": "SELECT Hometown FROM teacher GROUP BY Hometown ORDER BY COUNT(*) DESC LIMIT 1", "question": "What is the most commmon hometowns for teachers?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show the hometowns shared by at least two teachers.\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown HAVING COUNT(*) >= 2", "db_id": "course_teach", "query": "SELECT Hometown FROM teacher GROUP BY Hometown HAVING COUNT(*) >= 2", "question": "Show the hometowns shared by at least two teachers.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the towns from which at least two teachers come from?\n[SQL]:\n", "output": "SELECT Hometown FROM teacher GROUP BY Hometown HAVING COUNT(*) >= 2", "db_id": "course_teach", "query": "SELECT Hometown FROM teacher GROUP BY Hometown HAVING COUNT(*) >= 2", "question": "What are the towns from which at least two teachers come from?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers and the courses they are arranged to teach.\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID", "db_id": "course_teach", "query": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID", "question": "Show names of teachers and the courses they are arranged to teach.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What is the name of each teacher and what course they teach?\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID", "db_id": "course_teach", "query": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID", "question": "What is the name of each teacher and what course they teach?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers and the courses they are arranged to teach in ascending alphabetical order of the teacher's name.\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID ORDER BY T3.Name", "db_id": "course_teach", "query": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID ORDER BY T3.Name", "question": "Show names of teachers and the courses they are arranged to teach in ascending alphabetical order of the teacher's name.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers and the courses they teach in ascending alphabetical order by the name of the teacher?\n[SQL]:\n", "output": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID ORDER BY T3.Name", "db_id": "course_teach", "query": "SELECT T3.Name , T2.Course FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID ORDER BY T3.Name", "question": "What are the names of the teachers and the courses they teach in ascending alphabetical order by the name of the teacher?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show the name of the teacher for the math course.\n[SQL]:\n", "output": "SELECT T3.Name FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID WHERE T2.Course = \"Math\"", "db_id": "course_teach", "query": "SELECT T3.Name FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID WHERE T2.Course = \"Math\"", "question": "Show the name of the teacher for the math course.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the people who teach math courses?\n[SQL]:\n", "output": "SELECT T3.Name FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID WHERE T2.Course = \"Math\"", "db_id": "course_teach", "query": "SELECT T3.Name FROM course_arrange AS T1 JOIN course AS T2 ON T1.Course_ID = T2.Course_ID JOIN teacher AS T3 ON T1.Teacher_ID = T3.Teacher_ID WHERE T2.Course = \"Math\"", "question": "What are the names of the people who teach math courses?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers and the number of courses they teach.\n[SQL]:\n", "output": "SELECT T2.Name , COUNT(*) FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name", "db_id": "course_teach", "query": "SELECT T2.Name , COUNT(*) FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name", "question": "Show names of teachers and the number of courses they teach.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers and how many courses do they teach?\n[SQL]:\n", "output": "SELECT T2.Name , COUNT(*) FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name", "db_id": "course_teach", "query": "SELECT T2.Name , COUNT(*) FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name", "question": "What are the names of the teachers and how many courses do they teach?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:Show names of teachers that teach at least two courses.\n[SQL]:\n", "output": "SELECT T2.Name FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name HAVING COUNT(*) >= 2", "db_id": "course_teach", "query": "SELECT T2.Name FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name HAVING COUNT(*) >= 2", "question": "Show names of teachers that teach at least two courses.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers who teach at least two courses?\n[SQL]:\n", "output": "SELECT T2.Name FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name HAVING COUNT(*) >= 2", "db_id": "course_teach", "query": "SELECT T2.Name FROM course_arrange AS T1 JOIN teacher AS T2 ON T1.Teacher_ID = T2.Teacher_ID GROUP BY T2.Name HAVING COUNT(*) >= 2", "question": "What are the names of the teachers who teach at least two courses?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:List the names of teachers who have not been arranged to teach courses.\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Teacher_id NOT IN (SELECT Teacher_id FROM course_arrange)", "db_id": "course_teach", "query": "SELECT Name FROM teacher WHERE Teacher_id NOT IN (SELECT Teacher_id FROM course_arrange)", "question": "List the names of teachers who have not been arranged to teach courses.", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);\"\n[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id\"\n[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id\"\nAnswer the following question with a SQL Statement:What are the names of the teachers whose courses have not been arranged?\n[SQL]:\n", "output": "SELECT Name FROM teacher WHERE Teacher_id NOT IN (SELECT Teacher_id FROM course_arrange)", "db_id": "course_teach", "query": "SELECT Name FROM teacher WHERE Teacher_id NOT IN (SELECT Teacher_id FROM course_arrange)", "question": "What are the names of the teachers whose courses have not been arranged?", "schema": "[Schema (values) (types)]: | course_teach | course : course_id (text) , staring_date (number) , course (text) | teacher : teacher_id (text) , name (number) , age (text) , hometown (text) | course_arrange : course_id (text) , teacher_id (number) , grade (text);", "primary_keys": "[Primary Keys]: course : course_id, teacher : teacher_id, course_arrange : course_id", "foreign_keys": "[Foreign Keys]: course_arrange : teacher_id = teacher : teacher_id | course_arrange : course_id = course : course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:How many visitors below age 30 are there?\n[SQL]:\n", "output": "SELECT count(*) FROM visitor WHERE age < 30", "db_id": "museum_visit", "query": "SELECT count(*) FROM visitor WHERE age < 30", "question": "How many visitors below age 30 are there?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the names of the visitors whose membership level is higher than 4, and order the results by the level from high to low.\n[SQL]:\n", "output": "SELECT name FROM visitor WHERE Level_of_membership > 4 ORDER BY Level_of_membership DESC", "db_id": "museum_visit", "query": "SELECT name FROM visitor WHERE Level_of_membership > 4 ORDER BY Level_of_membership DESC", "question": "Find the names of the visitors whose membership level is higher than 4, and order the results by the level from high to low.", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the average age of the visitors whose membership level is not higher than 4?\n[SQL]:\n", "output": "SELECT avg(age) FROM visitor WHERE Level_of_membership <= 4", "db_id": "museum_visit", "query": "SELECT avg(age) FROM visitor WHERE Level_of_membership <= 4", "question": "What is the average age of the visitors whose membership level is not higher than 4?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the name and membership level of the visitors whose membership level is higher than 4, and sort by their age from old to young.\n[SQL]:\n", "output": "SELECT name , Level_of_membership FROM visitor WHERE Level_of_membership > 4 ORDER BY age DESC", "db_id": "museum_visit", "query": "SELECT name , Level_of_membership FROM visitor WHERE Level_of_membership > 4 ORDER BY age DESC", "question": "Find the name and membership level of the visitors whose membership level is higher than 4, and sort by their age from old to young.", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the id and name of the museum that has the most staff members?\n[SQL]:\n", "output": "SELECT museum_id , name FROM museum ORDER BY num_of_staff DESC LIMIT 1", "db_id": "museum_visit", "query": "SELECT museum_id , name FROM museum ORDER BY num_of_staff DESC LIMIT 1", "question": "Find the id and name of the museum that has the most staff members?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the average number of staff working for the museums that were open before 2009.\n[SQL]:\n", "output": "SELECT avg(num_of_staff) FROM museum WHERE open_year < 2009", "db_id": "museum_visit", "query": "SELECT avg(num_of_staff) FROM museum WHERE open_year < 2009", "question": "Find the average number of staff working for the museums that were open before 2009.", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the opening year and staff number of the museum named Plaza Museum?\n[SQL]:\n", "output": "SELECT Num_of_Staff , Open_Year FROM museum WHERE name = 'Plaza Museum'", "db_id": "museum_visit", "query": "SELECT Num_of_Staff , Open_Year FROM museum WHERE name = 'Plaza Museum'", "question": "What are the opening year and staff number of the museum named Plaza Museum?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:find the names of museums which have more staff than the minimum staff number of all museums opened after 2010.\n[SQL]:\n", "output": "SELECT name FROM museum WHERE num_of_staff > (SELECT min(num_of_staff) FROM museum WHERE open_year > 2010)", "db_id": "museum_visit", "query": "SELECT name FROM museum WHERE num_of_staff > (SELECT min(num_of_staff) FROM museum WHERE open_year > 2010)", "question": "find the names of museums which have more staff than the minimum staff number of all museums opened after 2010.", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:find the id, name and age for visitors who visited some museums more than once.\n[SQL]:\n", "output": "SELECT t1.id , t1.name , t1.age FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id GROUP BY t1.id HAVING count(*) > 1", "db_id": "museum_visit", "query": "SELECT t1.id , t1.name , t1.age FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id GROUP BY t1.id HAVING count(*) > 1", "question": "find the id, name and age for visitors who visited some museums more than once.", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the id, name and membership level of visitors who have spent the largest amount of money in total in all museum tickets?\n[SQL]:\n", "output": "SELECT t2.visitor_id , t1.name , t1.Level_of_membership FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id GROUP BY t2.visitor_id ORDER BY sum(t2.Total_spent) DESC LIMIT 1", "db_id": "museum_visit", "query": "SELECT t2.visitor_id , t1.name , t1.Level_of_membership FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id GROUP BY t2.visitor_id ORDER BY sum(t2.Total_spent) DESC LIMIT 1", "question": "What are the id, name and membership level of visitors who have spent the largest amount of money in total in all museum tickets?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the id and name of the museum visited most times?\n[SQL]:\n", "output": "SELECT t2.Museum_ID , t1.name FROM museum AS t1 JOIN visit AS t2 ON t1.Museum_ID = t2.Museum_ID GROUP BY t2.Museum_ID ORDER BY count(*) DESC LIMIT 1", "db_id": "museum_visit", "query": "SELECT t2.Museum_ID , t1.name FROM museum AS t1 JOIN visit AS t2 ON t1.Museum_ID = t2.Museum_ID GROUP BY t2.Museum_ID ORDER BY count(*) DESC LIMIT 1", "question": "What are the id and name of the museum visited most times?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the name of the museum that had no visitor yet?\n[SQL]:\n", "output": "SELECT name FROM museum WHERE Museum_ID NOT IN (SELECT museum_id FROM visit)", "db_id": "museum_visit", "query": "SELECT name FROM museum WHERE Museum_ID NOT IN (SELECT museum_id FROM visit)", "question": "What is the name of the museum that had no visitor yet?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the name and age of the visitor who bought the most tickets at once.\n[SQL]:\n", "output": "SELECT t1.name , t1.age FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id ORDER BY t2.num_of_ticket DESC LIMIT 1", "db_id": "museum_visit", "query": "SELECT t1.name , t1.age FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id ORDER BY t2.num_of_ticket DESC LIMIT 1", "question": "Find the name and age of the visitor who bought the most tickets at once.", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What are the average and maximum number of tickets bought in all visits?\n[SQL]:\n", "output": "SELECT avg(num_of_ticket) , max(num_of_ticket) FROM visit", "db_id": "museum_visit", "query": "SELECT avg(num_of_ticket) , max(num_of_ticket) FROM visit", "question": "What are the average and maximum number of tickets bought in all visits?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the total ticket expense of the visitors whose membership level is 1?\n[SQL]:\n", "output": "SELECT sum(t2.Total_spent) FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id WHERE t1.Level_of_membership = 1", "db_id": "museum_visit", "query": "SELECT sum(t2.Total_spent) FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id WHERE t1.Level_of_membership = 1", "question": "What is the total ticket expense of the visitors whose membership level is 1?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:What is the name of the visitor who visited both a museum opened before 2009 and a museum opened after 2011?\n[SQL]:\n", "output": "SELECT t1.name FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id JOIN museum AS t3 ON t3.Museum_ID = t2.Museum_ID WHERE t3.open_year < 2009 INTERSECT SELECT t1.name FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id JOIN museum AS t3 ON t3.Museum_ID = t2.Museum_ID WHERE t3.open_year > 2011", "db_id": "museum_visit", "query": "SELECT t1.name FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id JOIN museum AS t3 ON t3.Museum_ID = t2.Museum_ID WHERE t3.open_year < 2009 INTERSECT SELECT t1.name FROM visitor AS t1 JOIN visit AS t2 ON t1.id = t2.visitor_id JOIN museum AS t3 ON t3.Museum_ID = t2.Museum_ID WHERE t3.open_year > 2011", "question": "What is the name of the visitor who visited both a museum opened before 2009 and a museum opened after 2011?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:Find the number of visitors who did not visit any museum opened after 2010.\n[SQL]:\n", "output": "SELECT count(*) FROM visitor WHERE id NOT IN (SELECT t2.visitor_id FROM museum AS t1 JOIN visit AS t2 ON t1.Museum_ID = t2.Museum_ID WHERE t1.open_year > 2010)", "db_id": "museum_visit", "query": "SELECT count(*) FROM visitor WHERE id NOT IN (SELECT t2.visitor_id FROM museum AS t1 JOIN visit AS t2 ON t1.Museum_ID = t2.Museum_ID WHERE t1.open_year > 2010)", "question": "Find the number of visitors who did not visit any museum opened after 2010.", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);\"\n[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id\"\n[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id\"\nAnswer the following question with a SQL Statement:How many museums were opened after 2013 or before 2008?\n[SQL]:\n", "output": "SELECT count(*) FROM museum WHERE open_year > 2013 OR open_year < 2008", "db_id": "museum_visit", "query": "SELECT count(*) FROM museum WHERE open_year > 2013 OR open_year < 2008", "question": "How many museums were opened after 2013 or before 2008?", "schema": "[Schema (values) (types)]: | museum_visit | museum : museum_id (text) , name (number) , num_of_staff (text) , open_year (number) | visitor : id (text) , name (number) , level_of_membership (text) , age (number) | visit : museum_id (text) , visitor_id (number) , num_of_ticket (text) , total_spent (number);", "primary_keys": "[Primary Keys]: museum : museum_id, visitor : id, visit : museum_id", "foreign_keys": "[Foreign Keys]: visit : visitor_id = visitor : id | visit : museum_id = museum : museum_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total number of players.\n[SQL]:\n", "output": "SELECT count(*) FROM players", "db_id": "wta_1", "query": "SELECT count(*) FROM players", "question": "Find the total number of players.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many players are there?\n[SQL]:\n", "output": "SELECT count(*) FROM players", "db_id": "wta_1", "query": "SELECT count(*) FROM players", "question": "How many players are there?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total number of matches.\n[SQL]:\n", "output": "SELECT count(*) FROM matches", "db_id": "wta_1", "query": "SELECT count(*) FROM matches", "question": "Find the total number of matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Count the number of matches.\n[SQL]:\n", "output": "SELECT count(*) FROM matches", "db_id": "wta_1", "query": "SELECT count(*) FROM matches", "question": "Count the number of matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the first name and birth date of all players from the country with code USA.\n[SQL]:\n", "output": "SELECT first_name , birth_date FROM players WHERE country_code = 'USA'", "db_id": "wta_1", "query": "SELECT first_name , birth_date FROM players WHERE country_code = 'USA'", "question": "List the first name and birth date of all players from the country with code USA.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names and birth dates of players from the USA?\n[SQL]:\n", "output": "SELECT first_name , birth_date FROM players WHERE country_code = 'USA'", "db_id": "wta_1", "query": "SELECT first_name , birth_date FROM players WHERE country_code = 'USA'", "question": "What are the first names and birth dates of players from the USA?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the average age of losers and winners of all matches.\n[SQL]:\n", "output": "SELECT avg(loser_age) , avg(winner_age) FROM matches", "db_id": "wta_1", "query": "SELECT avg(loser_age) , avg(winner_age) FROM matches", "question": "Find the average age of losers and winners of all matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the average ages of losers and winners across matches?\n[SQL]:\n", "output": "SELECT avg(loser_age) , avg(winner_age) FROM matches", "db_id": "wta_1", "query": "SELECT avg(loser_age) , avg(winner_age) FROM matches", "question": "What are the average ages of losers and winners across matches?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the average rank of winners in all matches.\n[SQL]:\n", "output": "SELECT avg(winner_rank) FROM matches", "db_id": "wta_1", "query": "SELECT avg(winner_rank) FROM matches", "question": "Find the average rank of winners in all matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the average rank for winners in all matches?\n[SQL]:\n", "output": "SELECT avg(winner_rank) FROM matches", "db_id": "wta_1", "query": "SELECT avg(winner_rank) FROM matches", "question": "What is the average rank for winners in all matches?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the highest rank of losers in all matches.\n[SQL]:\n", "output": "SELECT min(loser_rank) FROM matches", "db_id": "wta_1", "query": "SELECT min(loser_rank) FROM matches", "question": "Find the highest rank of losers in all matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the best rank of losers across all matches?\n[SQL]:\n", "output": "SELECT min(loser_rank) FROM matches", "db_id": "wta_1", "query": "SELECT min(loser_rank) FROM matches", "question": "What is the best rank of losers across all matches?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the number of distinct country codes of all players.\n[SQL]:\n", "output": "SELECT count(DISTINCT country_code) FROM players", "db_id": "wta_1", "query": "SELECT count(DISTINCT country_code) FROM players", "question": "find the number of distinct country codes of all players.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many distinct countries do players come from?\n[SQL]:\n", "output": "SELECT count(DISTINCT country_code) FROM players", "db_id": "wta_1", "query": "SELECT count(DISTINCT country_code) FROM players", "question": "How many distinct countries do players come from?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of distinct name of losers.\n[SQL]:\n", "output": "SELECT count(DISTINCT loser_name) FROM matches", "db_id": "wta_1", "query": "SELECT count(DISTINCT loser_name) FROM matches", "question": "Find the number of distinct name of losers.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many different loser names are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT loser_name) FROM matches", "db_id": "wta_1", "query": "SELECT count(DISTINCT loser_name) FROM matches", "question": "How many different loser names are there?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name of tourney that has more than 10 matches.\n[SQL]:\n", "output": "SELECT tourney_name FROM matches GROUP BY tourney_name HAVING count(*) > 10", "db_id": "wta_1", "query": "SELECT tourney_name FROM matches GROUP BY tourney_name HAVING count(*) > 10", "question": "Find the name of tourney that has more than 10 matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names of tournaments that have more than 10 matches?\n[SQL]:\n", "output": "SELECT tourney_name FROM matches GROUP BY tourney_name HAVING count(*) > 10", "db_id": "wta_1", "query": "SELECT tourney_name FROM matches GROUP BY tourney_name HAVING count(*) > 10", "question": "What are the names of tournaments that have more than 10 matches?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the names of all winners who played in both 2013 and 2016.\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE YEAR = 2013 INTERSECT SELECT winner_name FROM matches WHERE YEAR = 2016", "db_id": "wta_1", "query": "SELECT winner_name FROM matches WHERE YEAR = 2013 INTERSECT SELECT winner_name FROM matches WHERE YEAR = 2016", "question": "List the names of all winners who played in both 2013 and 2016.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names of players who won in both 2013 and 2016?\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE YEAR = 2013 INTERSECT SELECT winner_name FROM matches WHERE YEAR = 2016", "db_id": "wta_1", "query": "SELECT winner_name FROM matches WHERE YEAR = 2013 INTERSECT SELECT winner_name FROM matches WHERE YEAR = 2016", "question": "What are the names of players who won in both 2013 and 2016?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the number of all matches who played in years of 2013 or 2016.\n[SQL]:\n", "output": "SELECT count(*) FROM matches WHERE YEAR = 2013 OR YEAR = 2016", "db_id": "wta_1", "query": "SELECT count(*) FROM matches WHERE YEAR = 2013 OR YEAR = 2016", "question": "List the number of all matches who played in years of 2013 or 2016.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many matches were played in 2013 or 2016?\n[SQL]:\n", "output": "SELECT count(*) FROM matches WHERE YEAR = 2013 OR YEAR = 2016", "db_id": "wta_1", "query": "SELECT count(*) FROM matches WHERE YEAR = 2013 OR YEAR = 2016", "question": "How many matches were played in 2013 or 2016?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the country code and first name of the players who won in both tourney WTA Championships and Australian Open?\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'WTA Championships' INTERSECT SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'Australian Open'", "db_id": "wta_1", "query": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'WTA Championships' INTERSECT SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'Australian Open'", "question": "What are the country code and first name of the players who won in both tourney WTA Championships and Australian Open?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names and country codes for players who won both the WTA Championships and the Australian Open?\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'WTA Championships' INTERSECT SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'Australian Open'", "db_id": "wta_1", "query": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'WTA Championships' INTERSECT SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id WHERE T2.tourney_name = 'Australian Open'", "question": "What are the first names and country codes for players who won both the WTA Championships and the Australian Open?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the first name and country code of the oldest player.\n[SQL]:\n", "output": "SELECT first_name , country_code FROM players ORDER BY birth_date LIMIT 1", "db_id": "wta_1", "query": "SELECT first_name , country_code FROM players ORDER BY birth_date LIMIT 1", "question": "Find the first name and country code of the oldest player.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the first name and country code of the oldest player?\n[SQL]:\n", "output": "SELECT first_name , country_code FROM players ORDER BY birth_date LIMIT 1", "db_id": "wta_1", "query": "SELECT first_name , country_code FROM players ORDER BY birth_date LIMIT 1", "question": "What is the first name and country code of the oldest player?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the first and last name of all players in the order of birth date.\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players ORDER BY birth_date", "db_id": "wta_1", "query": "SELECT first_name , last_name FROM players ORDER BY birth_date", "question": "List the first and last name of all players in the order of birth date.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the full names of all players, sorted by birth date?\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players ORDER BY birth_date", "db_id": "wta_1", "query": "SELECT first_name , last_name FROM players ORDER BY birth_date", "question": "What are the full names of all players, sorted by birth date?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:List the first and last name of all players who are left / L hand in the order of birth date.\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players WHERE hand = 'L' ORDER BY birth_date", "db_id": "wta_1", "query": "SELECT first_name , last_name FROM players WHERE hand = 'L' ORDER BY birth_date", "question": "List the first and last name of all players who are left / L hand in the order of birth date.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the full names of all left handed players, in order of birth date?\n[SQL]:\n", "output": "SELECT first_name , last_name FROM players WHERE hand = 'L' ORDER BY birth_date", "db_id": "wta_1", "query": "SELECT first_name , last_name FROM players WHERE hand = 'L' ORDER BY birth_date", "question": "What are the full names of all left handed players, in order of birth date?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the first name and country code of the player who did the most number of tours.\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id ORDER BY T2.tours DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id ORDER BY T2.tours DESC LIMIT 1", "question": "Find the first name and country code of the player who did the most number of tours.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the first name and country code of the player with the most tours?\n[SQL]:\n", "output": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id ORDER BY T2.tours DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT T1.country_code , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id ORDER BY T2.tours DESC LIMIT 1", "question": "What is the first name and country code of the player with the most tours?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the year that has the most number of matches.\n[SQL]:\n", "output": "SELECT YEAR FROM matches GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT YEAR FROM matches GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "question": "Find the year that has the most number of matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Which year had the most matches?\n[SQL]:\n", "output": "SELECT YEAR FROM matches GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT YEAR FROM matches GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1", "question": "Which year had the most matches?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name and rank points of the winner who won the most times.\n[SQL]:\n", "output": "SELECT winner_name , winner_rank_points FROM matches GROUP BY winner_name ORDER BY count(*) DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT winner_name , winner_rank_points FROM matches GROUP BY winner_name ORDER BY count(*) DESC LIMIT 1", "question": "Find the name and rank points of the winner who won the most times.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the name of the winner who has won the most matches, and how many rank points does this player have?\n[SQL]:\n", "output": "SELECT winner_name , winner_rank_points FROM matches GROUP BY winner_name ORDER BY count(*) DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT winner_name , winner_rank_points FROM matches GROUP BY winner_name ORDER BY count(*) DESC LIMIT 1", "question": "What is the name of the winner who has won the most matches, and how many rank points does this player have?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name of the winner who has the highest rank points and participated in the Australian Open tourney.\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE tourney_name = 'Australian Open' ORDER BY winner_rank_points DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT winner_name FROM matches WHERE tourney_name = 'Australian Open' ORDER BY winner_rank_points DESC LIMIT 1", "question": "Find the name of the winner who has the highest rank points and participated in the Australian Open tourney.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the name of the winner with the most rank points who participated in the Australian Open tournament?\n[SQL]:\n", "output": "SELECT winner_name FROM matches WHERE tourney_name = 'Australian Open' ORDER BY winner_rank_points DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT winner_name FROM matches WHERE tourney_name = 'Australian Open' ORDER BY winner_rank_points DESC LIMIT 1", "question": "What is the name of the winner with the most rank points who participated in the Australian Open tournament?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the names of loser and winner who played in the match with greatest number of minutes.\n[SQL]:\n", "output": "SELECT winner_name , loser_name FROM matches ORDER BY minutes DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT winner_name , loser_name FROM matches ORDER BY minutes DESC LIMIT 1", "question": "find the names of loser and winner who played in the match with greatest number of minutes.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names of the winner and loser who played in the longest match?\n[SQL]:\n", "output": "SELECT winner_name , loser_name FROM matches ORDER BY minutes DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT winner_name , loser_name FROM matches ORDER BY minutes DESC LIMIT 1", "question": "What are the names of the winner and loser who played in the longest match?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the average ranking for each player and their first name.\n[SQL]:\n", "output": "SELECT avg(ranking) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "db_id": "wta_1", "query": "SELECT avg(ranking) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "question": "Find the average ranking for each player and their first name.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names of all players, and their average rankings?\n[SQL]:\n", "output": "SELECT avg(ranking) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "db_id": "wta_1", "query": "SELECT avg(ranking) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "question": "What are the first names of all players, and their average rankings?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total ranking points for each player and their first name.\n[SQL]:\n", "output": "SELECT sum(ranking_points) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "db_id": "wta_1", "query": "SELECT sum(ranking_points) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "question": "Find the total ranking points for each player and their first name.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the first names of all players, and their total ranking points?\n[SQL]:\n", "output": "SELECT sum(ranking_points) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "db_id": "wta_1", "query": "SELECT sum(ranking_points) , T1.first_name FROM players AS T1 JOIN rankings AS T2 ON T1.player_id = T2.player_id GROUP BY T1.first_name", "question": "What are the first names of all players, and their total ranking points?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the number of players for each country.\n[SQL]:\n", "output": "SELECT count(*) , country_code FROM players GROUP BY country_code", "db_id": "wta_1", "query": "SELECT count(*) , country_code FROM players GROUP BY country_code", "question": "find the number of players for each country.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many players are from each country?\n[SQL]:\n", "output": "SELECT count(*) , country_code FROM players GROUP BY country_code", "db_id": "wta_1", "query": "SELECT count(*) , country_code FROM players GROUP BY country_code", "question": "How many players are from each country?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:find the code of the country where has the greatest number of players.\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code ORDER BY count(*) DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT country_code FROM players GROUP BY country_code ORDER BY count(*) DESC LIMIT 1", "question": "find the code of the country where has the greatest number of players.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the code of the country with the most players?\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code ORDER BY count(*) DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT country_code FROM players GROUP BY country_code ORDER BY count(*) DESC LIMIT 1", "question": "What is the code of the country with the most players?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the codes of countries that have more than 50 players.\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code HAVING count(*) > 50", "db_id": "wta_1", "query": "SELECT country_code FROM players GROUP BY country_code HAVING count(*) > 50", "question": "Find the codes of countries that have more than 50 players.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the codes of countries with more than 50 players?\n[SQL]:\n", "output": "SELECT country_code FROM players GROUP BY country_code HAVING count(*) > 50", "db_id": "wta_1", "query": "SELECT country_code FROM players GROUP BY country_code HAVING count(*) > 50", "question": "What are the codes of countries with more than 50 players?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the total number of tours for each ranking date.\n[SQL]:\n", "output": "SELECT sum(tours) , ranking_date FROM rankings GROUP BY ranking_date", "db_id": "wta_1", "query": "SELECT sum(tours) , ranking_date FROM rankings GROUP BY ranking_date", "question": "Find the total number of tours for each ranking date.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many total tours were there for each ranking date?\n[SQL]:\n", "output": "SELECT sum(tours) , ranking_date FROM rankings GROUP BY ranking_date", "db_id": "wta_1", "query": "SELECT sum(tours) , ranking_date FROM rankings GROUP BY ranking_date", "question": "How many total tours were there for each ranking date?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of matches happened in each year.\n[SQL]:\n", "output": "SELECT count(*) , YEAR FROM matches GROUP BY YEAR", "db_id": "wta_1", "query": "SELECT count(*) , YEAR FROM matches GROUP BY YEAR", "question": "Find the number of matches happened in each year.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many matches were played in each year?\n[SQL]:\n", "output": "SELECT count(*) , YEAR FROM matches GROUP BY YEAR", "db_id": "wta_1", "query": "SELECT count(*) , YEAR FROM matches GROUP BY YEAR", "question": "How many matches were played in each year?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the name and rank of the 3 youngest winners across all matches.\n[SQL]:\n", "output": "SELECT DISTINCT winner_name , winner_rank FROM matches ORDER BY winner_age LIMIT 3", "db_id": "wta_1", "query": "SELECT DISTINCT winner_name , winner_rank FROM matches ORDER BY winner_age LIMIT 3", "question": "Find the name and rank of the 3 youngest winners across all matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What are the names and ranks of the three youngest winners across all matches?\n[SQL]:\n", "output": "SELECT DISTINCT winner_name , winner_rank FROM matches ORDER BY winner_age LIMIT 3", "db_id": "wta_1", "query": "SELECT DISTINCT winner_name , winner_rank FROM matches ORDER BY winner_age LIMIT 3", "question": "What are the names and ranks of the three youngest winners across all matches?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many different winners both participated in the WTA Championships and were left handed?\n[SQL]:\n", "output": "SELECT count(DISTINCT winner_name) FROM matches WHERE tourney_name = 'WTA Championships' AND winner_hand = 'L'", "db_id": "wta_1", "query": "SELECT count(DISTINCT winner_name) FROM matches WHERE tourney_name = 'WTA Championships' AND winner_hand = 'L'", "question": "How many different winners both participated in the WTA Championships and were left handed?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of left handed winners who participated in the WTA Championships.\n[SQL]:\n", "output": "SELECT count(DISTINCT winner_name) FROM matches WHERE tourney_name = 'WTA Championships' AND winner_hand = 'L'", "db_id": "wta_1", "query": "SELECT count(DISTINCT winner_name) FROM matches WHERE tourney_name = 'WTA Championships' AND winner_hand = 'L'", "question": "Find the number of left handed winners who participated in the WTA Championships.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the first name, country code and birth date of the winner who has the highest rank points in all matches.\n[SQL]:\n", "output": "SELECT T1.first_name , T1.country_code , T1.birth_date FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id ORDER BY T2.winner_rank_points DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT T1.first_name , T1.country_code , T1.birth_date FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id ORDER BY T2.winner_rank_points DESC LIMIT 1", "question": "Find the first name, country code and birth date of the winner who has the highest rank points in all matches.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:What is the first name, country code, and birth date of the player with the most winner rank points across all matches?\n[SQL]:\n", "output": "SELECT T1.first_name , T1.country_code , T1.birth_date FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id ORDER BY T2.winner_rank_points DESC LIMIT 1", "db_id": "wta_1", "query": "SELECT T1.first_name , T1.country_code , T1.birth_date FROM players AS T1 JOIN matches AS T2 ON T1.player_id = T2.winner_id ORDER BY T2.winner_rank_points DESC LIMIT 1", "question": "What is the first name, country code, and birth date of the player with the most winner rank points across all matches?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:Find the number of players for each hand type.\n[SQL]:\n", "output": "SELECT count(*) , hand FROM players GROUP BY hand", "db_id": "wta_1", "query": "SELECT count(*) , hand FROM players GROUP BY hand", "question": "Find the number of players for each hand type.", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);\"\n[Primary Keys]: players : player_id\"\n[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id\"\nAnswer the following question with a SQL Statement:How many players are there for each hand type?\n[SQL]:\n", "output": "SELECT count(*) , hand FROM players GROUP BY hand", "db_id": "wta_1", "query": "SELECT count(*) , hand FROM players GROUP BY hand", "question": "How many players are there for each hand type?", "schema": "[Schema (values) (types)]: | wta_1 | players : player_id (text) , first_name (number) , last_name (text) , hand (text) , birth_date (text) , country_code (time) | matches : best_of (text) , draw_size (number) , loser_age (text) , loser_entry (text) , loser_hand (text) , loser_ht (time) , loser_id (text) , loser_ioc (number) , loser_name (number) , loser_rank (number) , loser_rank_points (text) , loser_seed (text) , match_num (number) , minutes (number) , round (text) , score (text) , surface (number) , tourney_date (number) , tourney_id (number) , tourney_level (number) , tourney_name (number) , winner_age (text) , winner_entry (text) , winner_hand (text) , winner_ht (time) , winner_id (text) , winner_ioc (text) , winner_name (text) , winner_rank (number) , winner_rank_points (text) , winner_seed (text) , year (number) | rankings : ranking_date (text) , ranking (number) , player_id (text) , ranking_points (text) , tours (text);", "primary_keys": "[Primary Keys]: players : player_id", "foreign_keys": "[Foreign Keys]: matches : winner_id = players : player_id | matches : loser_id = players : player_id | rankings : player_id = players : player_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:How many ships ended up being 'Captured'?\n[SQL]:\n", "output": "SELECT count(*) FROM ship WHERE disposition_of_ship = 'Captured'", "db_id": "battle_death", "query": "SELECT count(*) FROM ship WHERE disposition_of_ship = 'Captured'", "question": "How many ships ended up being 'Captured'?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:List the name and tonnage ordered by in descending alphaetical order for the names.\n[SQL]:\n", "output": "SELECT name , tonnage FROM ship ORDER BY name DESC", "db_id": "battle_death", "query": "SELECT name , tonnage FROM ship ORDER BY name DESC", "question": "List the name and tonnage ordered by in descending alphaetical order for the names.", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:List the name, date and result of each battle.\n[SQL]:\n", "output": "SELECT name , date FROM battle", "db_id": "battle_death", "query": "SELECT name , date FROM battle", "question": "List the name, date and result of each battle.", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What is maximum and minimum death toll caused each time?\n[SQL]:\n", "output": "SELECT max(killed) , min(killed) FROM death", "db_id": "battle_death", "query": "SELECT max(killed) , min(killed) FROM death", "question": "What is maximum and minimum death toll caused each time?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What is the average number of injuries caused each time?\n[SQL]:\n", "output": "SELECT avg(injured) FROM death", "db_id": "battle_death", "query": "SELECT avg(injured) FROM death", "question": "What is the average number of injuries caused each time?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the death and injury situations caused by the ship with tonnage 't'?\n[SQL]:\n", "output": "SELECT T1.killed , T1.injured FROM death AS T1 JOIN ship AS t2 ON T1.caused_by_ship_id = T2.id WHERE T2.tonnage = 't'", "db_id": "battle_death", "query": "SELECT T1.killed , T1.injured FROM death AS T1 JOIN ship AS t2 ON T1.caused_by_ship_id = T2.id WHERE T2.tonnage = 't'", "question": "What are the death and injury situations caused by the ship with tonnage 't'?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the name and results of the battles when the bulgarian commander is not 'Boril'\n[SQL]:\n", "output": "SELECT name , RESULT FROM battle WHERE bulgarian_commander != 'Boril'", "db_id": "battle_death", "query": "SELECT name , RESULT FROM battle WHERE bulgarian_commander != 'Boril'", "question": "What are the name and results of the battles when the bulgarian commander is not 'Boril'", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the different ids and names of the battles that lost any 'Brig' type shipes?\n[SQL]:\n", "output": "SELECT DISTINCT T1.id , T1.name FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.ship_type = 'Brig'", "db_id": "battle_death", "query": "SELECT DISTINCT T1.id , T1.name FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.ship_type = 'Brig'", "question": "What are the different ids and names of the battles that lost any 'Brig' type shipes?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the ids and names of the battles that led to more than 10 people killed in total.\n[SQL]:\n", "output": "SELECT T1.id , T1.name FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle JOIN death AS T3 ON T2.id = T3.caused_by_ship_id GROUP BY T1.id HAVING sum(T3.killed) > 10", "db_id": "battle_death", "query": "SELECT T1.id , T1.name FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle JOIN death AS T3 ON T2.id = T3.caused_by_ship_id GROUP BY T1.id HAVING sum(T3.killed) > 10", "question": "What are the ids and names of the battles that led to more than 10 people killed in total.", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What is the ship id and name that caused most total injuries?\n[SQL]:\n", "output": "SELECT T2.id , T2.name FROM death AS T1 JOIN ship AS t2 ON T1.caused_by_ship_id = T2.id GROUP BY T2.id ORDER BY count(*) DESC LIMIT 1", "db_id": "battle_death", "query": "SELECT T2.id , T2.name FROM death AS T1 JOIN ship AS t2 ON T1.caused_by_ship_id = T2.id GROUP BY T2.id ORDER BY count(*) DESC LIMIT 1", "question": "What is the ship id and name that caused most total injuries?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the distinct battle names which are between bulgarian commander 'Kaloyan' and latin commander 'Baldwin I'?\n[SQL]:\n", "output": "SELECT name FROM battle WHERE bulgarian_commander = 'Kaloyan' AND latin_commander = 'Baldwin I'", "db_id": "battle_death", "query": "SELECT name FROM battle WHERE bulgarian_commander = 'Kaloyan' AND latin_commander = 'Baldwin I'", "question": "What are the distinct battle names which are between bulgarian commander 'Kaloyan' and latin commander 'Baldwin I'?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:How many different results are there for the battles?\n[SQL]:\n", "output": "SELECT count(DISTINCT RESULT) FROM battle", "db_id": "battle_death", "query": "SELECT count(DISTINCT RESULT) FROM battle", "question": "How many different results are there for the battles?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:How many battles did not lose any ship with tonnage '225'?\n[SQL]:\n", "output": "SELECT count(*) FROM battle WHERE id NOT IN ( SELECT lost_in_battle FROM ship WHERE tonnage = '225' );", "db_id": "battle_death", "query": "SELECT count(*) FROM battle WHERE id NOT IN ( SELECT lost_in_battle FROM ship WHERE tonnage = '225' );", "question": "How many battles did not lose any ship with tonnage '225'?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:List the name and date the battle that has lost the ship named 'Lettice' and the ship named 'HMS Atalanta'\n[SQL]:\n", "output": "SELECT T1.name , T1.date FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.name = 'Lettice' INTERSECT SELECT T1.name , T1.date FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.name = 'HMS Atalanta'", "db_id": "battle_death", "query": "SELECT T1.name , T1.date FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.name = 'Lettice' INTERSECT SELECT T1.name , T1.date FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.name = 'HMS Atalanta'", "question": "List the name and date the battle that has lost the ship named 'Lettice' and the ship named 'HMS Atalanta'", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:Show names, results and bulgarian commanders of the battles with no ships lost in the 'English Channel'.\n[SQL]:\n", "output": "SELECT name , RESULT , bulgarian_commander FROM battle EXCEPT SELECT T1.name , T1.result , T1.bulgarian_commander FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.location = 'English Channel'", "db_id": "battle_death", "query": "SELECT name , RESULT , bulgarian_commander FROM battle EXCEPT SELECT T1.name , T1.result , T1.bulgarian_commander FROM battle AS T1 JOIN ship AS T2 ON T1.id = T2.lost_in_battle WHERE T2.location = 'English Channel'", "question": "Show names, results and bulgarian commanders of the battles with no ships lost in the 'English Channel'.", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);\"\n[Primary Keys]: battle : id, ship : id, death : id\"\n[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id\"\nAnswer the following question with a SQL Statement:What are the notes of the death events which has substring 'East'?\n[SQL]:\n", "output": "SELECT note FROM death WHERE note LIKE '%East%'", "db_id": "battle_death", "query": "SELECT note FROM death WHERE note LIKE '%East%'", "question": "What are the notes of the death events which has substring 'East'?", "schema": "[Schema (values) (types)]: | battle_death | battle : id (text) , name (number) , date (text) , bulgarian_commander (text) , latin_commander (text) , result (text) | ship : lost_in_battle (text) , id (number) , name (text) , tonnage (text) , ship_type (text) , location (text) , disposition_of_ship (text) | death : caused_by_ship_id (text) , id (number) , note (text) , killed (text) , injured (text);", "primary_keys": "[Primary Keys]: battle : id, ship : id, death : id", "foreign_keys": "[Foreign Keys]: ship : lost_in_battle = battle : id | death : caused_by_ship_id = ship : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:what are all the addresses including line 1 and line 2?\n[SQL]:\n", "output": "SELECT line_1 , line_2 FROM addresses", "db_id": "student_transcripts_tracking", "query": "SELECT line_1 , line_2 FROM addresses", "question": "what are all the addresses including line 1 and line 2?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first and second line for all addresses?\n[SQL]:\n", "output": "SELECT line_1 , line_2 FROM addresses", "db_id": "student_transcripts_tracking", "query": "SELECT line_1 , line_2 FROM addresses", "question": "What is the first and second line for all addresses?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many courses in total are listed?\n[SQL]:\n", "output": "SELECT count(*) FROM Courses", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) FROM Courses", "question": "How many courses in total are listed?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many courses are there?\n[SQL]:\n", "output": "SELECT count(*) FROM Courses", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) FROM Courses", "question": "How many courses are there?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How is the math course described?\n[SQL]:\n", "output": "SELECT course_description FROM Courses WHERE course_name = 'math'", "db_id": "student_transcripts_tracking", "query": "SELECT course_description FROM Courses WHERE course_name = 'math'", "question": "How is the math course described?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the descriptions for all the math courses?\n[SQL]:\n", "output": "SELECT course_description FROM Courses WHERE course_name = 'math'", "db_id": "student_transcripts_tracking", "query": "SELECT course_description FROM Courses WHERE course_name = 'math'", "question": "What are the descriptions for all the math courses?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the zip code of the address in the city Port Chelsea?\n[SQL]:\n", "output": "SELECT zip_postcode FROM Addresses WHERE city = 'Port Chelsea'", "db_id": "student_transcripts_tracking", "query": "SELECT zip_postcode FROM Addresses WHERE city = 'Port Chelsea'", "question": "What is the zip code of the address in the city Port Chelsea?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the zip code for Port Chelsea?\n[SQL]:\n", "output": "SELECT zip_postcode FROM Addresses WHERE city = 'Port Chelsea'", "db_id": "student_transcripts_tracking", "query": "SELECT zip_postcode FROM Addresses WHERE city = 'Port Chelsea'", "question": "What is the zip code for Port Chelsea?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which department offers the most number of degrees? List department name and id.\n[SQL]:\n", "output": "SELECT T2.department_name , T1.department_id FROM Degree_Programs AS T1 JOIN Departments AS T2 ON T1.department_id = T2.department_id GROUP BY T1.department_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T2.department_name , T1.department_id FROM Degree_Programs AS T1 JOIN Departments AS T2 ON T1.department_id = T2.department_id GROUP BY T1.department_id ORDER BY count(*) DESC LIMIT 1", "question": "Which department offers the most number of degrees? List department name and id.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the name and id of the department with the most number of degrees ?\n[SQL]:\n", "output": "select t2.department_name , t1.department_id from degree_programs as t1 join departments as t2 on t1.department_id = t2.department_id group by t1.department_id order by count(*) desc limit 1", "db_id": "student_transcripts_tracking", "query": "select t2.department_name , t1.department_id from degree_programs as t1 join departments as t2 on t1.department_id = t2.department_id group by t1.department_id order by count(*) desc limit 1", "question": "What is the name and id of the department with the most number of degrees ?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many departments offer any degree?\n[SQL]:\n", "output": "SELECT count(DISTINCT department_id) FROM Degree_Programs", "db_id": "student_transcripts_tracking", "query": "SELECT count(DISTINCT department_id) FROM Degree_Programs", "question": "How many departments offer any degree?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different departments offer degrees?\n[SQL]:\n", "output": "SELECT count(DISTINCT department_id) FROM Degree_Programs", "db_id": "student_transcripts_tracking", "query": "SELECT count(DISTINCT department_id) FROM Degree_Programs", "question": "How many different departments offer degrees?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different degree names are offered?\n[SQL]:\n", "output": "SELECT count(DISTINCT degree_summary_name) FROM Degree_Programs", "db_id": "student_transcripts_tracking", "query": "SELECT count(DISTINCT degree_summary_name) FROM Degree_Programs", "question": "How many different degree names are offered?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different degrees are offered?\n[SQL]:\n", "output": "SELECT count(DISTINCT degree_summary_name) FROM Degree_Programs", "db_id": "student_transcripts_tracking", "query": "SELECT count(DISTINCT degree_summary_name) FROM Degree_Programs", "question": "How many different degrees are offered?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many degrees does the engineering department offer?\n[SQL]:\n", "output": "SELECT count(*) FROM Departments AS T1 JOIN Degree_Programs AS T2 ON T1.department_id = T2.department_id WHERE T1.department_name = 'engineer'", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) FROM Departments AS T1 JOIN Degree_Programs AS T2 ON T1.department_id = T2.department_id WHERE T1.department_name = 'engineer'", "question": "How many degrees does the engineering department offer?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many degrees does the engineering department have?\n[SQL]:\n", "output": "SELECT count(*) FROM Departments AS T1 JOIN Degree_Programs AS T2 ON T1.department_id = T2.department_id WHERE T1.department_name = 'engineer'", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) FROM Departments AS T1 JOIN Degree_Programs AS T2 ON T1.department_id = T2.department_id WHERE T1.department_name = 'engineer'", "question": "How many degrees does the engineering department have?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and descriptions of all the sections?\n[SQL]:\n", "output": "SELECT section_name , section_description FROM Sections", "db_id": "student_transcripts_tracking", "query": "SELECT section_name , section_description FROM Sections", "question": "What are the names and descriptions of all the sections?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and descriptions for all the sections?\n[SQL]:\n", "output": "SELECT section_name , section_description FROM Sections", "db_id": "student_transcripts_tracking", "query": "SELECT section_name , section_description FROM Sections", "question": "What are the names and descriptions for all the sections?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and id of courses having at most 2 sections?\n[SQL]:\n", "output": "SELECT T1.course_name , T1.course_id FROM Courses AS T1 JOIN Sections AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_id HAVING count(*) <= 2", "db_id": "student_transcripts_tracking", "query": "SELECT T1.course_name , T1.course_id FROM Courses AS T1 JOIN Sections AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_id HAVING count(*) <= 2", "question": "What are the names and id of courses having at most 2 sections?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names and ids of every course with less than 2 sections?\n[SQL]:\n", "output": "SELECT T1.course_name , T1.course_id FROM Courses AS T1 JOIN Sections AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_id HAVING count(*) <= 2", "db_id": "student_transcripts_tracking", "query": "SELECT T1.course_name , T1.course_id FROM Courses AS T1 JOIN Sections AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_id HAVING count(*) <= 2", "question": "What are the names and ids of every course with less than 2 sections?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:List the section_name in reversed lexicographical order.\n[SQL]:\n", "output": "SELECT section_name FROM Sections ORDER BY section_name DESC", "db_id": "student_transcripts_tracking", "query": "SELECT section_name FROM Sections ORDER BY section_name DESC", "question": "List the section_name in reversed lexicographical order.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names of the sections in reverse alphabetical order?\n[SQL]:\n", "output": "SELECT section_name FROM Sections ORDER BY section_name DESC", "db_id": "student_transcripts_tracking", "query": "SELECT section_name FROM Sections ORDER BY section_name DESC", "question": "What are the names of the sections in reverse alphabetical order?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the semester which most student registered in? Show both the name and the id.\n[SQL]:\n", "output": "SELECT T1.semester_name , T1.semester_id FROM Semesters AS T1 JOIN Student_Enrolment AS T2 ON T1.semester_id = T2.semester_id GROUP BY T1.semester_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.semester_name , T1.semester_id FROM Semesters AS T1 JOIN Student_Enrolment AS T2 ON T1.semester_id = T2.semester_id GROUP BY T1.semester_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the semester which most student registered in? Show both the name and the id.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:For each semester, what is the name and id of the one with the most students registered?\n[SQL]:\n", "output": "SELECT T1.semester_name , T1.semester_id FROM Semesters AS T1 JOIN Student_Enrolment AS T2 ON T1.semester_id = T2.semester_id GROUP BY T1.semester_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.semester_name , T1.semester_id FROM Semesters AS T1 JOIN Student_Enrolment AS T2 ON T1.semester_id = T2.semester_id GROUP BY T1.semester_id ORDER BY count(*) DESC LIMIT 1", "question": "For each semester, what is the name and id of the one with the most students registered?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the description of the department whose name has the substring the computer?\n[SQL]:\n", "output": "SELECT department_description FROM Departments WHERE department_name LIKE '%computer%'", "db_id": "student_transcripts_tracking", "query": "SELECT department_description FROM Departments WHERE department_name LIKE '%computer%'", "question": "What is the description of the department whose name has the substring the computer?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the department description for the one whose name has the word computer?\n[SQL]:\n", "output": "SELECT department_description FROM Departments WHERE department_name LIKE '%computer%'", "db_id": "student_transcripts_tracking", "query": "SELECT department_description FROM Departments WHERE department_name LIKE '%computer%'", "question": "What is the department description for the one whose name has the word computer?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who are enrolled in 2 degree programs in one semester? List the first name, middle name and last name and the id.\n[SQL]:\n", "output": "SELECT T1.first_name , T1.middle_name , T1.last_name , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id HAVING count(*) = 2", "db_id": "student_transcripts_tracking", "query": "SELECT T1.first_name , T1.middle_name , T1.last_name , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id HAVING count(*) = 2", "question": "Who are enrolled in 2 degree programs in one semester? List the first name, middle name and last name and the id.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the first, middle, and last names, along with the ids, of all students who enrolled in 2 degree programs in one semester?\n[SQL]:\n", "output": "SELECT T1.first_name , T1.middle_name , T1.last_name , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id HAVING count(*) = 2", "db_id": "student_transcripts_tracking", "query": "SELECT T1.first_name , T1.middle_name , T1.last_name , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id HAVING count(*) = 2", "question": "What are the first, middle, and last names, along with the ids, of all students who enrolled in 2 degree programs in one semester?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who is enrolled in a Bachelor degree program? List the first name, middle name, last name.\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.middle_name , T1.last_name FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id JOIN Degree_Programs AS T3 ON T2.degree_program_id = T3.degree_program_id WHERE T3.degree_summary_name = 'Bachelor'", "db_id": "student_transcripts_tracking", "query": "SELECT DISTINCT T1.first_name , T1.middle_name , T1.last_name FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id JOIN Degree_Programs AS T3 ON T2.degree_program_id = T3.degree_program_id WHERE T3.degree_summary_name = 'Bachelor'", "question": "Who is enrolled in a Bachelor degree program? List the first name, middle name, last name.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the first, middle, and last names for everybody enrolled in a Bachelors program?\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.middle_name , T1.last_name FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id JOIN Degree_Programs AS T3 ON T2.degree_program_id = T3.degree_program_id WHERE T3.degree_summary_name = 'Bachelor'", "db_id": "student_transcripts_tracking", "query": "SELECT DISTINCT T1.first_name , T1.middle_name , T1.last_name FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id JOIN Degree_Programs AS T3 ON T2.degree_program_id = T3.degree_program_id WHERE T3.degree_summary_name = 'Bachelor'", "question": "What are the first, middle, and last names for everybody enrolled in a Bachelors program?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the kind of program which most number of students are enrolled in?\n[SQL]:\n", "output": "SELECT T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_summary_name ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_summary_name ORDER BY count(*) DESC LIMIT 1", "question": "Find the kind of program which most number of students are enrolled in?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the degree summary name that has the most number of students enrolled?\n[SQL]:\n", "output": "SELECT T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_summary_name ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_summary_name ORDER BY count(*) DESC LIMIT 1", "question": "What is the degree summary name that has the most number of students enrolled?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the program which most number of students are enrolled in. List both the id and the summary.\n[SQL]:\n", "output": "SELECT T1.degree_program_id , T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_program_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.degree_program_id , T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_program_id ORDER BY count(*) DESC LIMIT 1", "question": "Find the program which most number of students are enrolled in. List both the id and the summary.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the program id and the summary of the degree that has the most students enrolled?\n[SQL]:\n", "output": "SELECT T1.degree_program_id , T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_program_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.degree_program_id , T1.degree_summary_name FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id GROUP BY T1.degree_program_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the program id and the summary of the degree that has the most students enrolled?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which student has enrolled for the most times in any program? List the id, first name, middle name, last name, the number of enrollments and student id.\n[SQL]:\n", "output": "SELECT T1.student_id , T1.first_name , T1.middle_name , T1.last_name , count(*) , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.student_id , T1.first_name , T1.middle_name , T1.last_name , count(*) , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "question": "Which student has enrolled for the most times in any program? List the id, first name, middle name, last name, the number of enrollments and student id.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first, middle, and last name, along with the id and number of enrollments, for the student who enrolled the most in any program?\n[SQL]:\n", "output": "SELECT T1.student_id , T1.first_name , T1.middle_name , T1.last_name , count(*) , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.student_id , T1.first_name , T1.middle_name , T1.last_name , count(*) , T1.student_id FROM Students AS T1 JOIN Student_Enrolment AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the first, middle, and last name, along with the id and number of enrollments, for the student who enrolled the most in any program?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which semesters do not have any student enrolled? List the semester name.\n[SQL]:\n", "output": "SELECT semester_name FROM Semesters WHERE semester_id NOT IN( SELECT semester_id FROM Student_Enrolment )", "db_id": "student_transcripts_tracking", "query": "SELECT semester_name FROM Semesters WHERE semester_id NOT IN( SELECT semester_id FROM Student_Enrolment )", "question": "Which semesters do not have any student enrolled? List the semester name.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the name of the semester with no students enrolled?\n[SQL]:\n", "output": "SELECT semester_name FROM Semesters WHERE semester_id NOT IN( SELECT semester_id FROM Student_Enrolment )", "db_id": "student_transcripts_tracking", "query": "SELECT semester_name FROM Semesters WHERE semester_id NOT IN( SELECT semester_id FROM Student_Enrolment )", "question": "What is the name of the semester with no students enrolled?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are all the course names of the courses which ever have students enrolled in?\n[SQL]:\n", "output": "SELECT DISTINCT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id", "db_id": "student_transcripts_tracking", "query": "SELECT DISTINCT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id", "question": "What are all the course names of the courses which ever have students enrolled in?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the names of all courses that have some students enrolled?\n[SQL]:\n", "output": "SELECT DISTINCT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id", "db_id": "student_transcripts_tracking", "query": "SELECT DISTINCT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id", "question": "What are the names of all courses that have some students enrolled?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What's the name of the course with most number of enrollments?\n[SQL]:\n", "output": "SELECT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_name ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_name ORDER BY count(*) DESC LIMIT 1", "question": "What's the name of the course with most number of enrollments?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the name of the course with the most students enrolled?\n[SQL]:\n", "output": "SELECT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_name ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.course_name FROM Courses AS T1 JOIN Student_Enrolment_Courses AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_name ORDER BY count(*) DESC LIMIT 1", "question": "What is the name of the course with the most students enrolled?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the last name of the students who currently live in the state of North Carolina but have not registered in any degree program.\n[SQL]:\n", "output": "SELECT T1.last_name FROM Students AS T1 JOIN Addresses AS T2 ON T1.current_address_id = T2.address_id WHERE T2.state_province_county = 'NorthCarolina' EXCEPT SELECT DISTINCT T3.last_name FROM Students AS T3 JOIN Student_Enrolment AS T4 ON T3.student_id = T4.student_id", "db_id": "student_transcripts_tracking", "query": "SELECT T1.last_name FROM Students AS T1 JOIN Addresses AS T2 ON T1.current_address_id = T2.address_id WHERE T2.state_province_county = 'NorthCarolina' EXCEPT SELECT DISTINCT T3.last_name FROM Students AS T3 JOIN Student_Enrolment AS T4 ON T3.student_id = T4.student_id", "question": "Find the last name of the students who currently live in the state of North Carolina but have not registered in any degree program.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the last name of the students who live in North Carolina but have not registered in any degree programs?\n[SQL]:\n", "output": "SELECT T1.last_name FROM Students AS T1 JOIN Addresses AS T2 ON T1.current_address_id = T2.address_id WHERE T2.state_province_county = 'NorthCarolina' EXCEPT SELECT DISTINCT T3.last_name FROM Students AS T3 JOIN Student_Enrolment AS T4 ON T3.student_id = T4.student_id", "db_id": "student_transcripts_tracking", "query": "SELECT T1.last_name FROM Students AS T1 JOIN Addresses AS T2 ON T1.current_address_id = T2.address_id WHERE T2.state_province_county = 'NorthCarolina' EXCEPT SELECT DISTINCT T3.last_name FROM Students AS T3 JOIN Student_Enrolment AS T4 ON T3.student_id = T4.student_id", "question": "What are the last name of the students who live in North Carolina but have not registered in any degree programs?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Show the date and id of the transcript with at least 2 course results.\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id HAVING count(*) >= 2", "db_id": "student_transcripts_tracking", "query": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id HAVING count(*) >= 2", "question": "Show the date and id of the transcript with at least 2 course results.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the date and id of the transcript with at least 2 courses listed?\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id HAVING count(*) >= 2", "db_id": "student_transcripts_tracking", "query": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id HAVING count(*) >= 2", "question": "What is the date and id of the transcript with at least 2 courses listed?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the phone number of the man with the first name Timmothy and the last name Ward?\n[SQL]:\n", "output": "SELECT cell_mobile_number FROM Students WHERE first_name = 'Timmothy' AND last_name = 'Ward'", "db_id": "student_transcripts_tracking", "query": "SELECT cell_mobile_number FROM Students WHERE first_name = 'Timmothy' AND last_name = 'Ward'", "question": "What is the phone number of the man with the first name Timmothy and the last name Ward?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the mobile phone number of the student named Timmothy Ward ?\n[SQL]:\n", "output": "select cell_mobile_number from students where first_name = 'timmothy' and last_name = 'ward'", "db_id": "student_transcripts_tracking", "query": "select cell_mobile_number from students where first_name = 'timmothy' and last_name = 'ward'", "question": "What is the mobile phone number of the student named Timmothy Ward ?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who is the first student to register? List the first name, middle name and last name.\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_first_registered ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_first_registered ASC LIMIT 1", "question": "Who is the first student to register? List the first name, middle name and last name.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first, middle, and last name of the first student to register?\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_first_registered ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_first_registered ASC LIMIT 1", "question": "What is the first, middle, and last name of the first student to register?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Who is the earliest graduate of the school? List the first name, middle name and last name.\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_left ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_left ASC LIMIT 1", "question": "Who is the earliest graduate of the school? List the first name, middle name and last name.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first, middle, and last name of the earliest school graduate?\n[SQL]:\n", "output": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_left ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT first_name , middle_name , last_name FROM Students ORDER BY date_left ASC LIMIT 1", "question": "What is the first, middle, and last name of the earliest school graduate?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Whose permanent address is different from his or her current address? List his or her first name.\n[SQL]:\n", "output": "SELECT first_name FROM Students WHERE current_address_id != permanent_address_id", "db_id": "student_transcripts_tracking", "query": "SELECT first_name FROM Students WHERE current_address_id != permanent_address_id", "question": "Whose permanent address is different from his or her current address? List his or her first name.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the first name of the student whose permanent address is different from his or her current one?\n[SQL]:\n", "output": "SELECT first_name FROM Students WHERE current_address_id != permanent_address_id", "db_id": "student_transcripts_tracking", "query": "SELECT first_name FROM Students WHERE current_address_id != permanent_address_id", "question": "What is the first name of the student whose permanent address is different from his or her current one?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Which address holds the most number of students currently? List the address id and all lines.\n[SQL]:\n", "output": "SELECT T1.address_id , T1.line_1 , T1.line_2 FROM Addresses AS T1 JOIN Students AS T2 ON T1.address_id = T2.current_address_id GROUP BY T1.address_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.address_id , T1.line_1 , T1.line_2 FROM Addresses AS T1 JOIN Students AS T2 ON T1.address_id = T2.current_address_id GROUP BY T1.address_id ORDER BY count(*) DESC LIMIT 1", "question": "Which address holds the most number of students currently? List the address id and all lines.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the id, line 1, and line 2 of the address with the most students?\n[SQL]:\n", "output": "SELECT T1.address_id , T1.line_1 , T1.line_2 FROM Addresses AS T1 JOIN Students AS T2 ON T1.address_id = T2.current_address_id GROUP BY T1.address_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T1.address_id , T1.line_1 , T1.line_2 FROM Addresses AS T1 JOIN Students AS T2 ON T1.address_id = T2.current_address_id GROUP BY T1.address_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the id, line 1, and line 2 of the address with the most students?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:On average, when were the transcripts printed?\n[SQL]:\n", "output": "SELECT avg(transcript_date) FROM Transcripts", "db_id": "student_transcripts_tracking", "query": "SELECT avg(transcript_date) FROM Transcripts", "question": "On average, when were the transcripts printed?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the average transcript date?\n[SQL]:\n", "output": "SELECT avg(transcript_date) FROM Transcripts", "db_id": "student_transcripts_tracking", "query": "SELECT avg(transcript_date) FROM Transcripts", "question": "What is the average transcript date?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:When is the first transcript released? List the date and details.\n[SQL]:\n", "output": "SELECT transcript_date , other_details FROM Transcripts ORDER BY transcript_date ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT transcript_date , other_details FROM Transcripts ORDER BY transcript_date ASC LIMIT 1", "question": "When is the first transcript released? List the date and details.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the earliest date of a transcript release, and what details can you tell me?\n[SQL]:\n", "output": "SELECT transcript_date , other_details FROM Transcripts ORDER BY transcript_date ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT transcript_date , other_details FROM Transcripts ORDER BY transcript_date ASC LIMIT 1", "question": "What is the earliest date of a transcript release, and what details can you tell me?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many transcripts are released?\n[SQL]:\n", "output": "SELECT count(*) FROM Transcripts", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) FROM Transcripts", "question": "How many transcripts are released?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many transcripts are listed?\n[SQL]:\n", "output": "SELECT count(*) FROM Transcripts", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) FROM Transcripts", "question": "How many transcripts are listed?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the last transcript release date?\n[SQL]:\n", "output": "SELECT transcript_date FROM Transcripts ORDER BY transcript_date DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT transcript_date FROM Transcripts ORDER BY transcript_date DESC LIMIT 1", "question": "What is the last transcript release date?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:When was the last transcript released?\n[SQL]:\n", "output": "SELECT transcript_date FROM Transcripts ORDER BY transcript_date DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT transcript_date FROM Transcripts ORDER BY transcript_date DESC LIMIT 1", "question": "When was the last transcript released?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many times at most can a course enrollment result show in different transcripts? Also show the course enrollment id.\n[SQL]:\n", "output": "SELECT count(*) , student_course_id FROM Transcript_Contents GROUP BY student_course_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) , student_course_id FROM Transcript_Contents GROUP BY student_course_id ORDER BY count(*) DESC LIMIT 1", "question": "How many times at most can a course enrollment result show in different transcripts? Also show the course enrollment id.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the maximum number of times that a course shows up in different transcripts and what is that course's enrollment id?\n[SQL]:\n", "output": "SELECT count(*) , student_course_id FROM Transcript_Contents GROUP BY student_course_id ORDER BY count(*) DESC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT count(*) , student_course_id FROM Transcript_Contents GROUP BY student_course_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the maximum number of times that a course shows up in different transcripts and what is that course's enrollment id?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Show the date of the transcript which shows the least number of results, also list the id.\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id ORDER BY count(*) ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id ORDER BY count(*) ASC LIMIT 1", "question": "Show the date of the transcript which shows the least number of results, also list the id.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the date and id of the transcript with the least number of results?\n[SQL]:\n", "output": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id ORDER BY count(*) ASC LIMIT 1", "db_id": "student_transcripts_tracking", "query": "SELECT T2.transcript_date , T1.transcript_id FROM Transcript_Contents AS T1 JOIN Transcripts AS T2 ON T1.transcript_id = T2.transcript_id GROUP BY T1.transcript_id ORDER BY count(*) ASC LIMIT 1", "question": "What is the date and id of the transcript with the least number of results?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the semester when both Master students and Bachelor students got enrolled in.\n[SQL]:\n", "output": "SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Master' INTERSECT SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Bachelor'", "db_id": "student_transcripts_tracking", "query": "SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Master' INTERSECT SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Bachelor'", "question": "Find the semester when both Master students and Bachelor students got enrolled in.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the id of the semester that had both Masters and Bachelors students enrolled?\n[SQL]:\n", "output": "SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Master' INTERSECT SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Bachelor'", "db_id": "student_transcripts_tracking", "query": "SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Master' INTERSECT SELECT DISTINCT T2.semester_id FROM Degree_Programs AS T1 JOIN Student_Enrolment AS T2 ON T1.degree_program_id = T2.degree_program_id WHERE degree_summary_name = 'Bachelor'", "question": "What is the id of the semester that had both Masters and Bachelors students enrolled?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:How many different addresses do the students currently live?\n[SQL]:\n", "output": "SELECT count(DISTINCT current_address_id) FROM Students", "db_id": "student_transcripts_tracking", "query": "SELECT count(DISTINCT current_address_id) FROM Students", "question": "How many different addresses do the students currently live?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the different addresses that have students living there?\n[SQL]:\n", "output": "SELECT count(DISTINCT current_address_id) FROM Students", "db_id": "student_transcripts_tracking", "query": "SELECT count(DISTINCT current_address_id) FROM Students", "question": "What are the different addresses that have students living there?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:List all the student details in reversed lexicographical order.\n[SQL]:\n", "output": "SELECT other_student_details FROM Students ORDER BY other_student_details DESC", "db_id": "student_transcripts_tracking", "query": "SELECT other_student_details FROM Students ORDER BY other_student_details DESC", "question": "List all the student details in reversed lexicographical order.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What other details can you tell me about students in reverse alphabetical order?\n[SQL]:\n", "output": "SELECT other_student_details FROM Students ORDER BY other_student_details DESC", "db_id": "student_transcripts_tracking", "query": "SELECT other_student_details FROM Students ORDER BY other_student_details DESC", "question": "What other details can you tell me about students in reverse alphabetical order?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Describe the section h.\n[SQL]:\n", "output": "SELECT section_description FROM Sections WHERE section_name = 'h'", "db_id": "student_transcripts_tracking", "query": "SELECT section_description FROM Sections WHERE section_name = 'h'", "question": "Describe the section h.", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What is the description for the section named h?\n[SQL]:\n", "output": "SELECT section_description FROM Sections WHERE section_name = 'h'", "db_id": "student_transcripts_tracking", "query": "SELECT section_description FROM Sections WHERE section_name = 'h'", "question": "What is the description for the section named h?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:Find the first name of the students who permanently live in the country Haiti or have the cell phone number 09700166582 .\n[SQL]:\n", "output": "select t1.first_name from students as t1 join addresses as t2 on t1.permanent_address_id = t2.address_id where t2.country = 'haiti' or t1.cell_mobile_number = '09700166582'", "db_id": "student_transcripts_tracking", "query": "select t1.first_name from students as t1 join addresses as t2 on t1.permanent_address_id = t2.address_id where t2.country = 'haiti' or t1.cell_mobile_number = '09700166582'", "question": "Find the first name of the students who permanently live in the country Haiti or have the cell phone number 09700166582 .", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);\"\n[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id\"\n[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id\"\nAnswer the following question with a SQL Statement:What are the first names of the students who live in Haiti permanently or have the cell phone number 09700166582 ?\n[SQL]:\n", "output": "select t1.first_name from students as t1 join addresses as t2 on t1.permanent_address_id = t2.address_id where t2.country = 'haiti' or t1.cell_mobile_number = '09700166582'", "db_id": "student_transcripts_tracking", "query": "select t1.first_name from students as t1 join addresses as t2 on t1.permanent_address_id = t2.address_id where t2.country = 'haiti' or t1.cell_mobile_number = '09700166582'", "question": "What are the first names of the students who live in Haiti permanently or have the cell phone number 09700166582 ?", "schema": "[Schema (values) (types)]: | student_transcripts_tracking | Addresses : address_id (text) , line_1 (number) , line_2 (text) , line_3 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) , other_address_details (text) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | Departments : department_id (text) , department_name (number) , department_description (text) , other_details (text) | Degree_Programs : degree_program_id (text) , department_id (number) , degree_summary_name (text) , degree_summary_description (text) , other_details (text) | Sections : section_id (text) , course_id (number) , section_name (text) , section_description (text) , other_details (text) | Semesters : semester_id (text) , semester_name (number) , semester_description (text) , other_details (text) | Students : student_id (text) , current_address_id (number) , permanent_address_id (text) , first_name (text) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , ssn (text) , date_first_registered (text) , date_left (number) , other_student_details (text) | Student_Enrolment : student_enrolment_id (text) , degree_program_id (number) , semester_id (text) , student_id (text) , other_details (text) | Student_Enrolment_Courses : student_course_id (text) , course_id (number) , student_enrolment_id (text) | Transcripts : transcript_id (text) , transcript_date (number) , other_details (text) | Transcript_Contents : student_course_id (text) , transcript_id (number);", "primary_keys": "[Primary Keys]: addresses : address_id, courses : course_id, departments : department_id, degree_programs : degree_program_id, sections : section_id, semesters : semester_id, students : student_id, student_enrolment : student_enrolment_id, student_enrolment_courses : student_course_id, transcripts : transcript_id", "foreign_keys": "[Foreign Keys]: degree_programs : department_id = departments : department_id | sections : course_id = courses : course_id | students : permanent_address_id = addresses : address_id | students : current_address_id = addresses : address_id | student_enrolment : student_id = students : student_id | student_enrolment : semester_id = semesters : semester_id | student_enrolment : degree_program_id = degree_programs : degree_program_id | student_enrolment_courses : student_enrolment_id = student_enrolment : student_enrolment_id | student_enrolment_courses : course_id = courses : course_id | transcript_contents : transcript_id = transcripts : transcript_id | transcript_contents : student_course_id = student_enrolment_courses : student_course_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the title of all cartoons in alphabetical order.\n[SQL]:\n", "output": "SELECT Title FROM Cartoon ORDER BY title", "db_id": "tvshow", "query": "SELECT Title FROM Cartoon ORDER BY title", "question": "List the title of all cartoons in alphabetical order.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the titles of the cartoons sorted alphabetically?\n[SQL]:\n", "output": "SELECT Title FROM Cartoon ORDER BY title", "db_id": "tvshow", "query": "SELECT Title FROM Cartoon ORDER BY title", "question": "What are the titles of the cartoons sorted alphabetically?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List all cartoon directed by \"Ben Jones\".\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\";", "db_id": "tvshow", "query": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\";", "question": "List all cartoon directed by \"Ben Jones\".", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the names of all cartoons directed by Ben Jones?\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\";", "db_id": "tvshow", "query": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\";", "question": "What are the names of all cartoons directed by Ben Jones?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many cartoons were written by \"Joseph Kuhr\"?\n[SQL]:\n", "output": "SELECT count(*) FROM Cartoon WHERE Written_by = \"Joseph Kuhr\";", "db_id": "tvshow", "query": "SELECT count(*) FROM Cartoon WHERE Written_by = \"Joseph Kuhr\";", "question": "How many cartoons were written by \"Joseph Kuhr\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the number of cartoones written by Joseph Kuhr?\n[SQL]:\n", "output": "SELECT count(*) FROM Cartoon WHERE Written_by = \"Joseph Kuhr\";", "db_id": "tvshow", "query": "SELECT count(*) FROM Cartoon WHERE Written_by = \"Joseph Kuhr\";", "question": "What is the number of cartoones written by Joseph Kuhr?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:list all cartoon titles and their directors ordered by their air date\n[SQL]:\n", "output": "SELECT title , Directed_by FROM Cartoon ORDER BY Original_air_date", "db_id": "tvshow", "query": "SELECT title , Directed_by FROM Cartoon ORDER BY Original_air_date", "question": "list all cartoon titles and their directors ordered by their air date", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the name and directors of all the cartoons that are ordered by air date?\n[SQL]:\n", "output": "SELECT title , Directed_by FROM Cartoon ORDER BY Original_air_date", "db_id": "tvshow", "query": "SELECT title , Directed_by FROM Cartoon ORDER BY Original_air_date", "question": "What is the name and directors of all the cartoons that are ordered by air date?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the title of all cartoon directed by \"Ben Jones\" or \"Brandon Vietti\".\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\" OR Directed_by = \"Brandon Vietti\";", "db_id": "tvshow", "query": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\" OR Directed_by = \"Brandon Vietti\";", "question": "List the title of all cartoon directed by \"Ben Jones\" or \"Brandon Vietti\".", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the titles of all cartoons directed by Ben Jones or Brandon Vietti?\n[SQL]:\n", "output": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\" OR Directed_by = \"Brandon Vietti\";", "db_id": "tvshow", "query": "SELECT Title FROM Cartoon WHERE Directed_by = \"Ben Jones\" OR Directed_by = \"Brandon Vietti\";", "question": "What are the titles of all cartoons directed by Ben Jones or Brandon Vietti?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Which country has the most of TV Channels? List the country and number of TV Channels it has.\n[SQL]:\n", "output": "SELECT Country , count(*) FROM TV_Channel GROUP BY Country ORDER BY count(*) DESC LIMIT 1;", "db_id": "tvshow", "query": "SELECT Country , count(*) FROM TV_Channel GROUP BY Country ORDER BY count(*) DESC LIMIT 1;", "question": "Which country has the most of TV Channels? List the country and number of TV Channels it has.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the country with the most number of TV Channels and how many does it have?\n[SQL]:\n", "output": "SELECT Country , count(*) FROM TV_Channel GROUP BY Country ORDER BY count(*) DESC LIMIT 1;", "db_id": "tvshow", "query": "SELECT Country , count(*) FROM TV_Channel GROUP BY Country ORDER BY count(*) DESC LIMIT 1;", "question": "What is the country with the most number of TV Channels and how many does it have?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the number of different series names and contents in the TV Channel table.\n[SQL]:\n", "output": "SELECT count(DISTINCT series_name) , count(DISTINCT content) FROM TV_Channel;", "db_id": "tvshow", "query": "SELECT count(DISTINCT series_name) , count(DISTINCT content) FROM TV_Channel;", "question": "List the number of different series names and contents in the TV Channel table.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many different series and contents are listed in the TV Channel table?\n[SQL]:\n", "output": "SELECT count(DISTINCT series_name) , count(DISTINCT content) FROM TV_Channel;", "db_id": "tvshow", "query": "SELECT count(DISTINCT series_name) , count(DISTINCT content) FROM TV_Channel;", "question": "How many different series and contents are listed in the TV Channel table?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the content of TV Channel with serial name \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT Content FROM TV_Channel WHERE series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT Content FROM TV_Channel WHERE series_name = \"Sky Radio\";", "question": "What is the content of TV Channel with serial name \"Sky Radio\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the content of the series Sky Radio?\n[SQL]:\n", "output": "SELECT Content FROM TV_Channel WHERE series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT Content FROM TV_Channel WHERE series_name = \"Sky Radio\";", "question": "What is the content of the series Sky Radio?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the Package Option of TV Channel with serial name \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT Package_Option FROM TV_Channel WHERE series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT Package_Option FROM TV_Channel WHERE series_name = \"Sky Radio\";", "question": "What is the Package Option of TV Channel with serial name \"Sky Radio\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the Package Options of the TV Channels whose series names are Sky Radio?\n[SQL]:\n", "output": "SELECT Package_Option FROM TV_Channel WHERE series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT Package_Option FROM TV_Channel WHERE series_name = \"Sky Radio\";", "question": "What are the Package Options of the TV Channels whose series names are Sky Radio?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many TV Channel using language English?\n[SQL]:\n", "output": "SELECT count(*) FROM TV_Channel WHERE LANGUAGE = \"English\";", "db_id": "tvshow", "query": "SELECT count(*) FROM TV_Channel WHERE LANGUAGE = \"English\";", "question": "How many TV Channel using language English?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many TV Channels use the English language?\n[SQL]:\n", "output": "SELECT count(*) FROM TV_Channel WHERE LANGUAGE = \"English\";", "db_id": "tvshow", "query": "SELECT count(*) FROM TV_Channel WHERE LANGUAGE = \"English\";", "question": "How many TV Channels use the English language?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the language used least number of TV Channel. List language and number of TV Channel.\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE ORDER BY count(*) ASC LIMIT 1;", "db_id": "tvshow", "query": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE ORDER BY count(*) ASC LIMIT 1;", "question": "List the language used least number of TV Channel. List language and number of TV Channel.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the languages used by the least number of TV Channels and how many channels use it?\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE ORDER BY count(*) ASC LIMIT 1;", "db_id": "tvshow", "query": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE ORDER BY count(*) ASC LIMIT 1;", "question": "What are the languages used by the least number of TV Channels and how many channels use it?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List each language and the number of TV Channels using it.\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE", "db_id": "tvshow", "query": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE", "question": "List each language and the number of TV Channels using it.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:For each language, list the number of TV Channels that use it.\n[SQL]:\n", "output": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE", "db_id": "tvshow", "query": "SELECT LANGUAGE , count(*) FROM TV_Channel GROUP BY LANGUAGE", "question": "For each language, list the number of TV Channels that use it.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the TV Channel that shows the cartoon \"The Rise of the Blue Beetle!\"? List the TV Channel's series name.\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T2.Title = \"The Rise of the Blue Beetle!\";", "db_id": "tvshow", "query": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T2.Title = \"The Rise of the Blue Beetle!\";", "question": "What is the TV Channel that shows the cartoon \"The Rise of the Blue Beetle!\"? List the TV Channel's series name.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the series name of the TV Channel that shows the cartoon \"The Rise of the Blue Beetle\"?\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T2.Title = \"The Rise of the Blue Beetle!\";", "db_id": "tvshow", "query": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T2.Title = \"The Rise of the Blue Beetle!\";", "question": "What is the series name of the TV Channel that shows the cartoon \"The Rise of the Blue Beetle\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the title of all Cartoons showed on TV Channel with series name \"Sky Radio\".\n[SQL]:\n", "output": "SELECT T2.Title FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT T2.Title FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "question": "List the title of all Cartoons showed on TV Channel with series name \"Sky Radio\".", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the title of all the cartools that are on the TV Channel with the series name \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT T2.Title FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT T2.Title FROM TV_Channel AS T1 JOIN Cartoon AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "question": "What is the title of all the cartools that are on the TV Channel with the series name \"Sky Radio\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the Episode of all TV series sorted by rating.\n[SQL]:\n", "output": "SELECT Episode FROM TV_series ORDER BY rating", "db_id": "tvshow", "query": "SELECT Episode FROM TV_series ORDER BY rating", "question": "List the Episode of all TV series sorted by rating.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are all of the episodes ordered by ratings?\n[SQL]:\n", "output": "SELECT Episode FROM TV_series ORDER BY rating", "db_id": "tvshow", "query": "SELECT Episode FROM TV_series ORDER BY rating", "question": "What are all of the episodes ordered by ratings?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List top 3 highest Rating TV series. List the TV series's Episode and Rating.\n[SQL]:\n", "output": "SELECT Episode , Rating FROM TV_series ORDER BY Rating DESC LIMIT 3;", "db_id": "tvshow", "query": "SELECT Episode , Rating FROM TV_series ORDER BY Rating DESC LIMIT 3;", "question": "List top 3 highest Rating TV series. List the TV series's Episode and Rating.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are 3 most highly rated episodes in the TV series table and what were those ratings?\n[SQL]:\n", "output": "SELECT Episode , Rating FROM TV_series ORDER BY Rating DESC LIMIT 3;", "db_id": "tvshow", "query": "SELECT Episode , Rating FROM TV_series ORDER BY Rating DESC LIMIT 3;", "question": "What are 3 most highly rated episodes in the TV series table and what were those ratings?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is minimum and maximum share of TV series?\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM TV_series;", "db_id": "tvshow", "query": "SELECT max(SHARE) , min(SHARE) FROM TV_series;", "question": "What is minimum and maximum share of TV series?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the maximum and minimum share for the TV series?\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM TV_series;", "db_id": "tvshow", "query": "SELECT max(SHARE) , min(SHARE) FROM TV_series;", "question": "What is the maximum and minimum share for the TV series?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the air date of TV series with Episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT Air_Date FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "db_id": "tvshow", "query": "SELECT Air_Date FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "question": "What is the air date of TV series with Episode \"A Love of a Lifetime\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:When did the episode \"A Love of a Lifetime\" air?\n[SQL]:\n", "output": "SELECT Air_Date FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "db_id": "tvshow", "query": "SELECT Air_Date FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "question": "When did the episode \"A Love of a Lifetime\" air?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is Weekly Rank of TV series with Episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT Weekly_Rank FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "db_id": "tvshow", "query": "SELECT Weekly_Rank FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "question": "What is Weekly Rank of TV series with Episode \"A Love of a Lifetime\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the weekly rank for the episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT Weekly_Rank FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "db_id": "tvshow", "query": "SELECT Weekly_Rank FROM TV_series WHERE Episode = \"A Love of a Lifetime\";", "question": "What is the weekly rank for the episode \"A Love of a Lifetime\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the TV Channel of TV series with Episode \"A Love of a Lifetime\"? List the TV Channel's series name.\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T2.Episode = \"A Love of a Lifetime\";", "db_id": "tvshow", "query": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T2.Episode = \"A Love of a Lifetime\";", "question": "What is the TV Channel of TV series with Episode \"A Love of a Lifetime\"? List the TV Channel's series name.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the name of the series that has the episode \"A Love of a Lifetime\"?\n[SQL]:\n", "output": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T2.Episode = \"A Love of a Lifetime\";", "db_id": "tvshow", "query": "SELECT T1.series_name FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T2.Episode = \"A Love of a Lifetime\";", "question": "What is the name of the series that has the episode \"A Love of a Lifetime\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:List the Episode of all TV series showed on TV Channel with series name \"Sky Radio\".\n[SQL]:\n", "output": "SELECT T2.Episode FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT T2.Episode FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "question": "List the Episode of all TV series showed on TV Channel with series name \"Sky Radio\".", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the episode for the TV series named \"Sky Radio\"?\n[SQL]:\n", "output": "SELECT T2.Episode FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "db_id": "tvshow", "query": "SELECT T2.Episode FROM TV_Channel AS T1 JOIN TV_series AS T2 ON T1.id = T2.Channel WHERE T1.series_name = \"Sky Radio\";", "question": "What is the episode for the TV series named \"Sky Radio\"?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the number of cartoons directed by each of the listed directors.\n[SQL]:\n", "output": "SELECT count(*) , Directed_by FROM cartoon GROUP BY Directed_by", "db_id": "tvshow", "query": "SELECT count(*) , Directed_by FROM cartoon GROUP BY Directed_by", "question": "Find the number of cartoons directed by each of the listed directors.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:How many cartoons did each director create?\n[SQL]:\n", "output": "SELECT count(*) , Directed_by FROM cartoon GROUP BY Directed_by", "db_id": "tvshow", "query": "SELECT count(*) , Directed_by FROM cartoon GROUP BY Directed_by", "question": "How many cartoons did each director create?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the production code and channel of the most recently aired cartoon .\n[SQL]:\n", "output": "select production_code , channel from cartoon order by original_air_date desc limit 1", "db_id": "tvshow", "query": "select production_code , channel from cartoon order by original_air_date desc limit 1", "question": "Find the production code and channel of the most recently aired cartoon .", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the produdction code and channel of the most recent cartoon ?\n[SQL]:\n", "output": "select production_code , channel from cartoon order by original_air_date desc limit 1", "db_id": "tvshow", "query": "select production_code , channel from cartoon order by original_air_date desc limit 1", "question": "What is the produdction code and channel of the most recent cartoon ?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the package choice and series name of the TV channel that has high definition TV.\n[SQL]:\n", "output": "SELECT package_option , series_name FROM TV_Channel WHERE hight_definition_TV = \"yes\"", "db_id": "tvshow", "query": "SELECT package_option , series_name FROM TV_Channel WHERE hight_definition_TV = \"yes\"", "question": "Find the package choice and series name of the TV channel that has high definition TV.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the package options and the name of the series for the TV Channel that supports high definition TV?\n[SQL]:\n", "output": "SELECT package_option , series_name FROM TV_Channel WHERE hight_definition_TV = \"yes\"", "db_id": "tvshow", "query": "SELECT package_option , series_name FROM TV_Channel WHERE hight_definition_TV = \"yes\"", "question": "What are the package options and the name of the series for the TV Channel that supports high definition TV?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:which countries' tv channels are playing some cartoon written by Todd Casey?\n[SQL]:\n", "output": "SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "db_id": "tvshow", "query": "SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "question": "which countries' tv channels are playing some cartoon written by Todd Casey?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the countries that have cartoons on TV that were written by Todd Casey?\n[SQL]:\n", "output": "SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "db_id": "tvshow", "query": "SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "question": "What are the countries that have cartoons on TV that were written by Todd Casey?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:which countries' tv channels are not playing any cartoon written by Todd Casey?\n[SQL]:\n", "output": "SELECT country FROM TV_Channel EXCEPT SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "db_id": "tvshow", "query": "SELECT country FROM TV_Channel EXCEPT SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "question": "which countries' tv channels are not playing any cartoon written by Todd Casey?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the countries that are not playing cartoons written by Todd Casey?\n[SQL]:\n", "output": "SELECT country FROM TV_Channel EXCEPT SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "db_id": "tvshow", "query": "SELECT country FROM TV_Channel EXCEPT SELECT T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.written_by = 'Todd Casey'", "question": "What are the countries that are not playing cartoons written by Todd Casey?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:Find the series name and country of the tv channel that is playing some cartoons directed by Ben Jones and Michael Chang?\n[SQL]:\n", "output": "SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Michael Chang' INTERSECT SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Ben Jones'", "db_id": "tvshow", "query": "SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Michael Chang' INTERSECT SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Ben Jones'", "question": "Find the series name and country of the tv channel that is playing some cartoons directed by Ben Jones and Michael Chang?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the series name and country of all TV channels that are playing cartoons directed by Ben Jones and cartoons directed by Michael Chang?\n[SQL]:\n", "output": "SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Michael Chang' INTERSECT SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Ben Jones'", "db_id": "tvshow", "query": "SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Michael Chang' INTERSECT SELECT T1.series_name , T1.country FROM TV_Channel AS T1 JOIN cartoon AS T2 ON T1.id = T2.Channel WHERE T2.directed_by = 'Ben Jones'", "question": "What is the series name and country of all TV channels that are playing cartoons directed by Ben Jones and cartoons directed by Michael Chang?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find the pixel aspect ratio and nation of the tv channels that do not use English.\n[SQL]:\n", "output": "SELECT Pixel_aspect_ratio_PAR , country FROM tv_channel WHERE LANGUAGE != 'English'", "db_id": "tvshow", "query": "SELECT Pixel_aspect_ratio_PAR , country FROM tv_channel WHERE LANGUAGE != 'English'", "question": "find the pixel aspect ratio and nation of the tv channels that do not use English.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What is the pixel aspect ratio and country of origin for all TV channels that do not use English?\n[SQL]:\n", "output": "SELECT Pixel_aspect_ratio_PAR , country FROM tv_channel WHERE LANGUAGE != 'English'", "db_id": "tvshow", "query": "SELECT Pixel_aspect_ratio_PAR , country FROM tv_channel WHERE LANGUAGE != 'English'", "question": "What is the pixel aspect ratio and country of origin for all TV channels that do not use English?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find id of the tv channels that from the countries where have more than two tv channels.\n[SQL]:\n", "output": "SELECT id FROM tv_channel GROUP BY country HAVING count(*) > 2", "db_id": "tvshow", "query": "SELECT id FROM tv_channel GROUP BY country HAVING count(*) > 2", "question": "find id of the tv channels that from the countries where have more than two tv channels.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the ids of all tv channels that have more than 2 TV channels?\n[SQL]:\n", "output": "SELECT id FROM tv_channel GROUP BY country HAVING count(*) > 2", "db_id": "tvshow", "query": "SELECT id FROM tv_channel GROUP BY country HAVING count(*) > 2", "question": "What are the ids of all tv channels that have more than 2 TV channels?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find the id of tv channels that do not play any cartoon directed by Ben Jones.\n[SQL]:\n", "output": "SELECT id FROM TV_Channel EXCEPT SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones'", "db_id": "tvshow", "query": "SELECT id FROM TV_Channel EXCEPT SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones'", "question": "find the id of tv channels that do not play any cartoon directed by Ben Jones.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the ids of the TV channels that do not have any cartoons directed by Ben Jones?\n[SQL]:\n", "output": "SELECT id FROM TV_Channel EXCEPT SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones'", "db_id": "tvshow", "query": "SELECT id FROM TV_Channel EXCEPT SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones'", "question": "What are the ids of the TV channels that do not have any cartoons directed by Ben Jones?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:find the package option of the tv channel that do not have any cartoon directed by Ben Jones.\n[SQL]:\n", "output": "SELECT package_option FROM TV_Channel WHERE id NOT IN (SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones')", "db_id": "tvshow", "query": "SELECT package_option FROM TV_Channel WHERE id NOT IN (SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones')", "question": "find the package option of the tv channel that do not have any cartoon directed by Ben Jones.", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);\"\n[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id\"\n[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id\"\nAnswer the following question with a SQL Statement:What are the package options of all tv channels that are not playing any cartoons directed by Ben Jones?\n[SQL]:\n", "output": "SELECT package_option FROM TV_Channel WHERE id NOT IN (SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones')", "db_id": "tvshow", "query": "SELECT package_option FROM TV_Channel WHERE id NOT IN (SELECT channel FROM cartoon WHERE directed_by = 'Ben Jones')", "question": "What are the package options of all tv channels that are not playing any cartoons directed by Ben Jones?", "schema": "[Schema (values) (types)]: | tvshow | TV_Channel : id (text) , series_name (text) , country (text) , language (text) , content (text) , pixel_aspect_ratio_par (text) , hight_definition_tv (text) , pay_per_view_ppv (text) , package_option (text) | TV_series : id (text) , episode (text) , air_date (text) , rating (text) , share (text) , 18_49_rating_share (text) , viewers_m (text) , weekly_rank (text) , channel (text) | Cartoon : id (text) , title (text) , directed_by (text) , written_by (text) , original_air_date (text) , production_code (text) , channel (text);", "primary_keys": "[Primary Keys]: tv_channel : id, tv_series : id, cartoon : id", "foreign_keys": "[Foreign Keys]: tv_series : channel = tv_channel : id | cartoon : channel = tv_channel : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:How many poker players are there?\n[SQL]:\n", "output": "SELECT count(*) FROM poker_player", "db_id": "poker_player", "query": "SELECT count(*) FROM poker_player", "question": "How many poker players are there?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Count the number of poker players.\n[SQL]:\n", "output": "SELECT count(*) FROM poker_player", "db_id": "poker_player", "query": "SELECT count(*) FROM poker_player", "question": "Count the number of poker players.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the earnings of poker players in descending order.\n[SQL]:\n", "output": "SELECT Earnings FROM poker_player ORDER BY Earnings DESC", "db_id": "poker_player", "query": "SELECT Earnings FROM poker_player ORDER BY Earnings DESC", "question": "List the earnings of poker players in descending order.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the earnings of poker players, ordered descending by value?\n[SQL]:\n", "output": "SELECT Earnings FROM poker_player ORDER BY Earnings DESC", "db_id": "poker_player", "query": "SELECT Earnings FROM poker_player ORDER BY Earnings DESC", "question": "What are the earnings of poker players, ordered descending by value?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the final tables made and the best finishes of poker players.\n[SQL]:\n", "output": "SELECT Final_Table_Made , Best_Finish FROM poker_player", "db_id": "poker_player", "query": "SELECT Final_Table_Made , Best_Finish FROM poker_player", "question": "List the final tables made and the best finishes of poker players.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the final tables made and best finishes for all poker players?\n[SQL]:\n", "output": "SELECT Final_Table_Made , Best_Finish FROM poker_player", "db_id": "poker_player", "query": "SELECT Final_Table_Made , Best_Finish FROM poker_player", "question": "What are the final tables made and best finishes for all poker players?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the average earnings of poker players?\n[SQL]:\n", "output": "SELECT avg(Earnings) FROM poker_player", "db_id": "poker_player", "query": "SELECT avg(Earnings) FROM poker_player", "question": "What is the average earnings of poker players?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the average earnings across all poker players.\n[SQL]:\n", "output": "SELECT avg(Earnings) FROM poker_player", "db_id": "poker_player", "query": "SELECT avg(Earnings) FROM poker_player", "question": "Return the average earnings across all poker players.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the money rank of the poker player with the highest earnings?\n[SQL]:\n", "output": "SELECT Money_Rank FROM poker_player ORDER BY Earnings DESC LIMIT 1", "db_id": "poker_player", "query": "SELECT Money_Rank FROM poker_player ORDER BY Earnings DESC LIMIT 1", "question": "What is the money rank of the poker player with the highest earnings?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the money rank of the player with the greatest earnings.\n[SQL]:\n", "output": "SELECT Money_Rank FROM poker_player ORDER BY Earnings DESC LIMIT 1", "db_id": "poker_player", "query": "SELECT Money_Rank FROM poker_player ORDER BY Earnings DESC LIMIT 1", "question": "Return the money rank of the player with the greatest earnings.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the maximum number of final tables made among poker players with earnings less than 200000?\n[SQL]:\n", "output": "SELECT max(Final_Table_Made) FROM poker_player WHERE Earnings < 200000", "db_id": "poker_player", "query": "SELECT max(Final_Table_Made) FROM poker_player WHERE Earnings < 200000", "question": "What is the maximum number of final tables made among poker players with earnings less than 200000?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the maximum final tables made across all poker players who have earnings below 200000.\n[SQL]:\n", "output": "SELECT max(Final_Table_Made) FROM poker_player WHERE Earnings < 200000", "db_id": "poker_player", "query": "SELECT max(Final_Table_Made) FROM poker_player WHERE Earnings < 200000", "question": "Return the maximum final tables made across all poker players who have earnings below 200000.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID", "question": "What are the names of poker players?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the names of all the poker players.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID", "question": "Return the names of all the poker players.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players whose earnings is higher than 300000?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T2.Earnings > 300000", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T2.Earnings > 300000", "question": "What are the names of poker players whose earnings is higher than 300000?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Give the names of poker players who have earnings above 300000.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T2.Earnings > 300000", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T2.Earnings > 300000", "question": "Give the names of poker players who have earnings above 300000.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the names of poker players ordered by the final tables made in ascending order.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Final_Table_Made", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Final_Table_Made", "question": "List the names of poker players ordered by the final tables made in ascending order.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players, ordered ascending by the number of final tables they have made?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Final_Table_Made", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Final_Table_Made", "question": "What are the names of poker players, ordered ascending by the number of final tables they have made?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the birth date of the poker player with the lowest earnings?\n[SQL]:\n", "output": "SELECT T1.Birth_Date FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings ASC LIMIT 1", "db_id": "poker_player", "query": "SELECT T1.Birth_Date FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings ASC LIMIT 1", "question": "What is the birth date of the poker player with the lowest earnings?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the birth date of the poker player with the lowest earnings.\n[SQL]:\n", "output": "SELECT T1.Birth_Date FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings ASC LIMIT 1", "db_id": "poker_player", "query": "SELECT T1.Birth_Date FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings ASC LIMIT 1", "question": "Return the birth date of the poker player with the lowest earnings.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the money rank of the tallest poker player?\n[SQL]:\n", "output": "SELECT T2.Money_Rank FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Height DESC LIMIT 1", "db_id": "poker_player", "query": "SELECT T2.Money_Rank FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Height DESC LIMIT 1", "question": "What is the money rank of the tallest poker player?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the money rank of the poker player with the greatest height.\n[SQL]:\n", "output": "SELECT T2.Money_Rank FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Height DESC LIMIT 1", "db_id": "poker_player", "query": "SELECT T2.Money_Rank FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Height DESC LIMIT 1", "question": "Return the money rank of the poker player with the greatest height.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the average earnings of poker players with height higher than 200?\n[SQL]:\n", "output": "SELECT avg(T2.Earnings) FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T1.Height > 200", "db_id": "poker_player", "query": "SELECT avg(T2.Earnings) FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T1.Height > 200", "question": "What is the average earnings of poker players with height higher than 200?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Give average earnings of poker players who are taller than 200.\n[SQL]:\n", "output": "SELECT avg(T2.Earnings) FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T1.Height > 200", "db_id": "poker_player", "query": "SELECT avg(T2.Earnings) FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID WHERE T1.Height > 200", "question": "Give average earnings of poker players who are taller than 200.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of poker players in descending order of earnings?\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings DESC", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings DESC", "question": "What are the names of poker players in descending order of earnings?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the names of poker players sorted by their earnings descending.\n[SQL]:\n", "output": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings DESC", "db_id": "poker_player", "query": "SELECT T1.Name FROM people AS T1 JOIN poker_player AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Earnings DESC", "question": "Return the names of poker players sorted by their earnings descending.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are different nationalities of people and the corresponding number of people from each nation?\n[SQL]:\n", "output": "SELECT Nationality , COUNT(*) FROM people GROUP BY Nationality", "db_id": "poker_player", "query": "SELECT Nationality , COUNT(*) FROM people GROUP BY Nationality", "question": "What are different nationalities of people and the corresponding number of people from each nation?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:How many people are there of each nationality?\n[SQL]:\n", "output": "SELECT Nationality , COUNT(*) FROM people GROUP BY Nationality", "db_id": "poker_player", "query": "SELECT Nationality , COUNT(*) FROM people GROUP BY Nationality", "question": "How many people are there of each nationality?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What is the most common nationality of people?\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "poker_player", "query": "SELECT Nationality FROM people GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1", "question": "What is the most common nationality of people?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Give the nationality that is most common across all people.\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "poker_player", "query": "SELECT Nationality FROM people GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1", "question": "Give the nationality that is most common across all people.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the nationalities that are shared by at least two people?\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality HAVING COUNT(*) >= 2", "db_id": "poker_player", "query": "SELECT Nationality FROM people GROUP BY Nationality HAVING COUNT(*) >= 2", "question": "What are the nationalities that are shared by at least two people?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Return the nationalities for which there are two or more people.\n[SQL]:\n", "output": "SELECT Nationality FROM people GROUP BY Nationality HAVING COUNT(*) >= 2", "db_id": "poker_player", "query": "SELECT Nationality FROM people GROUP BY Nationality HAVING COUNT(*) >= 2", "question": "Return the nationalities for which there are two or more people.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the names and birth dates of people in ascending alphabetical order of name.\n[SQL]:\n", "output": "SELECT Name , Birth_Date FROM people ORDER BY Name ASC", "db_id": "poker_player", "query": "SELECT Name , Birth_Date FROM people ORDER BY Name ASC", "question": "List the names and birth dates of people in ascending alphabetical order of name.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names and birth dates of people, ordered by their names in alphabetical order?\n[SQL]:\n", "output": "SELECT Name , Birth_Date FROM people ORDER BY Name ASC", "db_id": "poker_player", "query": "SELECT Name , Birth_Date FROM people ORDER BY Name ASC", "question": "What are the names and birth dates of people, ordered by their names in alphabetical order?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Show names of people whose nationality is not \"Russia\".\n[SQL]:\n", "output": "SELECT Name FROM people WHERE Nationality != \"Russia\"", "db_id": "poker_player", "query": "SELECT Name FROM people WHERE Nationality != \"Russia\"", "question": "Show names of people whose nationality is not \"Russia\".", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of people who are not from Russia?\n[SQL]:\n", "output": "SELECT Name FROM people WHERE Nationality != \"Russia\"", "db_id": "poker_player", "query": "SELECT Name FROM people WHERE Nationality != \"Russia\"", "question": "What are the names of people who are not from Russia?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:List the names of people that are not poker players.\n[SQL]:\n", "output": "SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM poker_player)", "db_id": "poker_player", "query": "SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM poker_player)", "question": "List the names of people that are not poker players.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:What are the names of people who do not play poker?\n[SQL]:\n", "output": "SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM poker_player)", "db_id": "poker_player", "query": "SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM poker_player)", "question": "What are the names of people who do not play poker?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:How many distinct nationalities are there?\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM people", "db_id": "poker_player", "query": "SELECT count(DISTINCT Nationality) FROM people", "question": "How many distinct nationalities are there?", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);\"\n[Primary Keys]: poker_player : poker_player_id, people : people_id\"\n[Foreign Keys]: poker_player : people_id = people : people_id\"\nAnswer the following question with a SQL Statement:Count the number of different nationalities.\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM people", "db_id": "poker_player", "query": "SELECT count(DISTINCT Nationality) FROM people", "question": "Count the number of different nationalities.", "schema": "[Schema (values) (types)]: | poker_player | poker_player : poker_player_id (text) , people_id (number) , final_table_made (number) , best_finish (number) , money_rank (number) , earnings (number) | people : people_id (text) , nationality (number) , name (number) , birth_date (number) , height (number);", "primary_keys": "[Primary Keys]: poker_player : poker_player_id, people : people_id", "foreign_keys": "[Foreign Keys]: poker_player : people_id = people : people_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:How many states are there?\n[SQL]:\n", "output": "SELECT count(*) FROM area_code_state", "db_id": "voter_1", "query": "SELECT count(*) FROM area_code_state", "question": "How many states are there?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:List the contestant numbers and names, ordered by contestant name descending.\n[SQL]:\n", "output": "SELECT contestant_number , contestant_name FROM contestants ORDER BY contestant_name DESC", "db_id": "voter_1", "query": "SELECT contestant_number , contestant_name FROM contestants ORDER BY contestant_name DESC", "question": "List the contestant numbers and names, ordered by contestant name descending.", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:List the vote ids, phone numbers and states of all votes.\n[SQL]:\n", "output": "SELECT vote_id , phone_number , state FROM votes", "db_id": "voter_1", "query": "SELECT vote_id , phone_number , state FROM votes", "question": "List the vote ids, phone numbers and states of all votes.", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the maximum and minimum values of area codes?\n[SQL]:\n", "output": "SELECT max(area_code) , min(area_code) FROM area_code_state", "db_id": "voter_1", "query": "SELECT max(area_code) , min(area_code) FROM area_code_state", "question": "What are the maximum and minimum values of area codes?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What is last date created of votes from the state 'CA'?\n[SQL]:\n", "output": "SELECT max(created) FROM votes WHERE state = 'CA'", "db_id": "voter_1", "query": "SELECT max(created) FROM votes WHERE state = 'CA'", "question": "What is last date created of votes from the state 'CA'?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the names of the contestants whose names are not 'Jessie Alloway'\n[SQL]:\n", "output": "SELECT contestant_name FROM contestants WHERE contestant_name != 'Jessie Alloway'", "db_id": "voter_1", "query": "SELECT contestant_name FROM contestants WHERE contestant_name != 'Jessie Alloway'", "question": "What are the names of the contestants whose names are not 'Jessie Alloway'", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the distinct states and create time of all votes?\n[SQL]:\n", "output": "SELECT DISTINCT state , created FROM votes", "db_id": "voter_1", "query": "SELECT DISTINCT state , created FROM votes", "question": "What are the distinct states and create time of all votes?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the contestant numbers and names of the contestants who had at least two votes?\n[SQL]:\n", "output": "SELECT T1.contestant_number , T1.contestant_name FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number GROUP BY T1.contestant_number HAVING count(*) >= 2", "db_id": "voter_1", "query": "SELECT T1.contestant_number , T1.contestant_name FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number GROUP BY T1.contestant_number HAVING count(*) >= 2", "question": "What are the contestant numbers and names of the contestants who had at least two votes?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:Of all the contestants who got voted, what is the contestant number and name of the contestant who got least votes?\n[SQL]:\n", "output": "SELECT T1.contestant_number , T1.contestant_name FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number GROUP BY T1.contestant_number ORDER BY count(*) ASC LIMIT 1", "db_id": "voter_1", "query": "SELECT T1.contestant_number , T1.contestant_name FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number GROUP BY T1.contestant_number ORDER BY count(*) ASC LIMIT 1", "question": "Of all the contestants who got voted, what is the contestant number and name of the contestant who got least votes?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the number of votes from state 'NY' or 'CA'?\n[SQL]:\n", "output": "SELECT count(*) FROM votes WHERE state = 'NY' OR state = 'CA'", "db_id": "voter_1", "query": "SELECT count(*) FROM votes WHERE state = 'NY' OR state = 'CA'", "question": "What are the number of votes from state 'NY' or 'CA'?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:How many contestants did not get voted?\n[SQL]:\n", "output": "SELECT count(*) FROM contestants WHERE contestant_number NOT IN ( SELECT contestant_number FROM votes )", "db_id": "voter_1", "query": "SELECT count(*) FROM contestants WHERE contestant_number NOT IN ( SELECT contestant_number FROM votes )", "question": "How many contestants did not get voted?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What is the area code in which the most voters voted?\n[SQL]:\n", "output": "SELECT T1.area_code FROM area_code_state AS T1 JOIN votes AS T2 ON T1.state = T2.state GROUP BY T1.area_code ORDER BY count(*) DESC LIMIT 1", "db_id": "voter_1", "query": "SELECT T1.area_code FROM area_code_state AS T1 JOIN votes AS T2 ON T1.state = T2.state GROUP BY T1.area_code ORDER BY count(*) DESC LIMIT 1", "question": "What is the area code in which the most voters voted?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:What are the create dates, states, and phone numbers of the votes that were for the contestant named 'Tabatha Gehling'?\n[SQL]:\n", "output": "SELECT T2.created , T2.state , T2.phone_number FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number WHERE T1.contestant_name = 'Tabatha Gehling'", "db_id": "voter_1", "query": "SELECT T2.created , T2.state , T2.phone_number FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number WHERE T1.contestant_name = 'Tabatha Gehling'", "question": "What are the create dates, states, and phone numbers of the votes that were for the contestant named 'Tabatha Gehling'?", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:List the area codes in which voters voted both for the contestant 'Tabatha Gehling' and the contestant 'Kelly Clauss'.\n[SQL]:\n", "output": "SELECT T3.area_code FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number JOIN area_code_state AS T3 ON T2.state = T3.state WHERE T1.contestant_name = 'Tabatha Gehling' INTERSECT SELECT T3.area_code FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number JOIN area_code_state AS T3 ON T2.state = T3.state WHERE T1.contestant_name = 'Kelly Clauss'", "db_id": "voter_1", "query": "SELECT T3.area_code FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number JOIN area_code_state AS T3 ON T2.state = T3.state WHERE T1.contestant_name = 'Tabatha Gehling' INTERSECT SELECT T3.area_code FROM contestants AS T1 JOIN votes AS T2 ON T1.contestant_number = T2.contestant_number JOIN area_code_state AS T3 ON T2.state = T3.state WHERE T1.contestant_name = 'Kelly Clauss'", "question": "List the area codes in which voters voted both for the contestant 'Tabatha Gehling' and the contestant 'Kelly Clauss'.", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);\"\n[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id\"\n[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state\"\nAnswer the following question with a SQL Statement:Return the names of the contestants whose names contain the substring 'Al' .\n[SQL]:\n", "output": "select contestant_name from contestants where contestant_name like \"%al%\"", "db_id": "voter_1", "query": "select contestant_name from contestants where contestant_name like \"%al%\"", "question": "Return the names of the contestants whose names contain the substring 'Al' .", "schema": "[Schema (values) (types)]: | voter_1 | AREA_CODE_STATE : area_code (text) , state (number) | CONTESTANTS : contestant_number (text) , contestant_name (number) | VOTES : vote_id (text) , phone_number (number) , state (text) , contestant_number (number) , created (text);", "primary_keys": "[Primary Keys]: area_code_state : area_code, contestants : contestant_number, votes : vote_id", "foreign_keys": "[Foreign Keys]: votes : contestant_number = contestants : contestant_number | votes : state = area_code_state : state"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of all the countries that became independent after 1950?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE IndepYear > 1950", "db_id": "world_1", "query": "SELECT Name FROM country WHERE IndepYear > 1950", "question": "What are the names of all the countries that became independent after 1950?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of the nations that were founded after 1950.\n[SQL]:\n", "output": "SELECT Name FROM country WHERE IndepYear > 1950", "db_id": "world_1", "query": "SELECT Name FROM country WHERE IndepYear > 1950", "question": "Give the names of the nations that were founded after 1950.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many countries have a republic as their form of government?\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE GovernmentForm = \"Republic\"", "db_id": "world_1", "query": "SELECT count(*) FROM country WHERE GovernmentForm = \"Republic\"", "question": "How many countries have a republic as their form of government?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many countries have governments that are republics?\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE GovernmentForm = \"Republic\"", "db_id": "world_1", "query": "SELECT count(*) FROM country WHERE GovernmentForm = \"Republic\"", "question": "How many countries have governments that are republics?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total surface area of the countries in the Caribbean region?\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Region = \"Caribbean\"", "db_id": "world_1", "query": "SELECT sum(SurfaceArea) FROM country WHERE Region = \"Caribbean\"", "question": "What is the total surface area of the countries in the Caribbean region?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How much surface area do the countires in the Carribean cover together?\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Region = \"Caribbean\"", "db_id": "world_1", "query": "SELECT sum(SurfaceArea) FROM country WHERE Region = \"Caribbean\"", "question": "How much surface area do the countires in the Carribean cover together?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which continent is Anguilla in?\n[SQL]:\n", "output": "SELECT Continent FROM country WHERE Name = \"Anguilla\"", "db_id": "world_1", "query": "SELECT Continent FROM country WHERE Name = \"Anguilla\"", "question": "Which continent is Anguilla in?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the continent name which Anguilla belongs to?\n[SQL]:\n", "output": "SELECT Continent FROM country WHERE Name = \"Anguilla\"", "db_id": "world_1", "query": "SELECT Continent FROM country WHERE Name = \"Anguilla\"", "question": "What is the continent name which Anguilla belongs to?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which region is the city Kabul located in?\n[SQL]:\n", "output": "SELECT Region FROM country AS T1 JOIN city AS T2 ON T1.Code = T2.CountryCode WHERE T2.Name = \"Kabul\"", "db_id": "world_1", "query": "SELECT Region FROM country AS T1 JOIN city AS T2 ON T1.Code = T2.CountryCode WHERE T2.Name = \"Kabul\"", "question": "Which region is the city Kabul located in?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What region is Kabul in?\n[SQL]:\n", "output": "SELECT Region FROM country AS T1 JOIN city AS T2 ON T1.Code = T2.CountryCode WHERE T2.Name = \"Kabul\"", "db_id": "world_1", "query": "SELECT Region FROM country AS T1 JOIN city AS T2 ON T1.Code = T2.CountryCode WHERE T2.Name = \"Kabul\"", "question": "What region is Kabul in?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which language is the most popular in Aruba?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\" ORDER BY Percentage DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\" ORDER BY Percentage DESC LIMIT 1", "question": "Which language is the most popular in Aruba?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What language is predominantly spoken in Aruba?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\" ORDER BY Percentage DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\" ORDER BY Percentage DESC LIMIT 1", "question": "What language is predominantly spoken in Aruba?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the population and life expectancies in Brazil?\n[SQL]:\n", "output": "SELECT Population , LifeExpectancy FROM country WHERE Name = \"Brazil\"", "db_id": "world_1", "query": "SELECT Population , LifeExpectancy FROM country WHERE Name = \"Brazil\"", "question": "What are the population and life expectancies in Brazil?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give me Brazil\u2019s population and life expectancies.\n[SQL]:\n", "output": "SELECT Population , LifeExpectancy FROM country WHERE Name = \"Brazil\"", "db_id": "world_1", "query": "SELECT Population , LifeExpectancy FROM country WHERE Name = \"Brazil\"", "question": "Give me Brazil\u2019s population and life expectancies.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the region and population of Angola?\n[SQL]:\n", "output": "SELECT Population , Region FROM country WHERE Name = \"Angola\"", "db_id": "world_1", "query": "SELECT Population , Region FROM country WHERE Name = \"Angola\"", "question": "What are the region and population of Angola?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What region does Angola belong to and what is its population?\n[SQL]:\n", "output": "SELECT Population , Region FROM country WHERE Name = \"Angola\"", "db_id": "world_1", "query": "SELECT Population , Region FROM country WHERE Name = \"Angola\"", "question": "What region does Angola belong to and what is its population?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the average expected life expectancy for countries in the region of Central Africa?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Region = \"Central Africa\"", "db_id": "world_1", "query": "SELECT avg(LifeExpectancy) FROM country WHERE Region = \"Central Africa\"", "question": "What is the average expected life expectancy for countries in the region of Central Africa?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How long is the people\u2019s average life expectancy in Central Africa?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Region = \"Central Africa\"", "db_id": "world_1", "query": "SELECT avg(LifeExpectancy) FROM country WHERE Region = \"Central Africa\"", "question": "How long is the people\u2019s average life expectancy in Central Africa?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the name of country that has the shortest life expectancy in Asia?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" ORDER BY LifeExpectancy LIMIT 1", "db_id": "world_1", "query": "SELECT Name FROM country WHERE Continent = \"Asia\" ORDER BY LifeExpectancy LIMIT 1", "question": "What is the name of country that has the shortest life expectancy in Asia?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name of the country in Asia with the lowest life expectancy.\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" ORDER BY LifeExpectancy LIMIT 1", "db_id": "world_1", "query": "SELECT Name FROM country WHERE Continent = \"Asia\" ORDER BY LifeExpectancy LIMIT 1", "question": "Give the name of the country in Asia with the lowest life expectancy.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total population and maximum GNP in Asia?\n[SQL]:\n", "output": "SELECT sum(Population) , max(GNP) FROM country WHERE Continent = \"Asia\"", "db_id": "world_1", "query": "SELECT sum(Population) , max(GNP) FROM country WHERE Continent = \"Asia\"", "question": "What is the total population and maximum GNP in Asia?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many people live in Asia, and what is the largest GNP among them?\n[SQL]:\n", "output": "SELECT sum(Population) , max(GNP) FROM country WHERE Continent = \"Asia\"", "db_id": "world_1", "query": "SELECT sum(Population) , max(GNP) FROM country WHERE Continent = \"Asia\"", "question": "How many people live in Asia, and what is the largest GNP among them?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the average life expectancy in African countries that are republics?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Continent = \"Africa\" AND GovernmentForm = \"Republic\"", "db_id": "world_1", "query": "SELECT avg(LifeExpectancy) FROM country WHERE Continent = \"Africa\" AND GovernmentForm = \"Republic\"", "question": "What is the average life expectancy in African countries that are republics?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the average life expectancy for countries in Africa which are republics?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Continent = \"Africa\" AND GovernmentForm = \"Republic\"", "db_id": "world_1", "query": "SELECT avg(LifeExpectancy) FROM country WHERE Continent = \"Africa\" AND GovernmentForm = \"Republic\"", "question": "Give the average life expectancy for countries in Africa which are republics?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total surface area of the continents Asia and Europe?\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Continent = \"Asia\" OR Continent = \"Europe\"", "db_id": "world_1", "query": "SELECT sum(SurfaceArea) FROM country WHERE Continent = \"Asia\" OR Continent = \"Europe\"", "question": "What is the total surface area of the continents Asia and Europe?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the total surface area covered by countries in Asia or Europe.\n[SQL]:\n", "output": "SELECT sum(SurfaceArea) FROM country WHERE Continent = \"Asia\" OR Continent = \"Europe\"", "db_id": "world_1", "query": "SELECT sum(SurfaceArea) FROM country WHERE Continent = \"Asia\" OR Continent = \"Europe\"", "question": "Give the total surface area covered by countries in Asia or Europe.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many people live in Gelderland district?\n[SQL]:\n", "output": "SELECT sum(Population) FROM city WHERE District = \"Gelderland\"", "db_id": "world_1", "query": "SELECT sum(Population) FROM city WHERE District = \"Gelderland\"", "question": "How many people live in Gelderland district?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total population of Gelderland district?\n[SQL]:\n", "output": "SELECT sum(Population) FROM city WHERE District = \"Gelderland\"", "db_id": "world_1", "query": "SELECT sum(Population) FROM city WHERE District = \"Gelderland\"", "question": "What is the total population of Gelderland district?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the average GNP and total population in all nations whose government is US territory?\n[SQL]:\n", "output": "SELECT avg(GNP) , sum(population) FROM country WHERE GovernmentForm = \"US Territory\"", "db_id": "world_1", "query": "SELECT avg(GNP) , sum(population) FROM country WHERE GovernmentForm = \"US Territory\"", "question": "What is the average GNP and total population in all nations whose government is US territory?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the mean GNP and total population of nations which are considered US territory.\n[SQL]:\n", "output": "SELECT avg(GNP) , sum(population) FROM country WHERE GovernmentForm = \"US Territory\"", "db_id": "world_1", "query": "SELECT avg(GNP) , sum(population) FROM country WHERE GovernmentForm = \"US Territory\"", "question": "Give the mean GNP and total population of nations which are considered US territory.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many unique languages are spoken in the world?\n[SQL]:\n", "output": "SELECT count(DISTINCT LANGUAGE) FROM countrylanguage", "db_id": "world_1", "query": "SELECT count(DISTINCT LANGUAGE) FROM countrylanguage", "question": "How many unique languages are spoken in the world?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the number of distinct languages used around the world?\n[SQL]:\n", "output": "SELECT count(DISTINCT LANGUAGE) FROM countrylanguage", "db_id": "world_1", "query": "SELECT count(DISTINCT LANGUAGE) FROM countrylanguage", "question": "What is the number of distinct languages used around the world?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many type of governments are in Africa?\n[SQL]:\n", "output": "SELECT count(DISTINCT GovernmentForm) FROM country WHERE Continent = \"Africa\"", "db_id": "world_1", "query": "SELECT count(DISTINCT GovernmentForm) FROM country WHERE Continent = \"Africa\"", "question": "How many type of governments are in Africa?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many different forms of governments are there in Africa?\n[SQL]:\n", "output": "SELECT count(DISTINCT GovernmentForm) FROM country WHERE Continent = \"Africa\"", "db_id": "world_1", "query": "SELECT count(DISTINCT GovernmentForm) FROM country WHERE Continent = \"Africa\"", "question": "How many different forms of governments are there in Africa?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of languages used in Aruba?\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\"", "db_id": "world_1", "query": "SELECT COUNT(T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\"", "question": "What is the total number of languages used in Aruba?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many languages are spoken in Aruba?\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\"", "db_id": "world_1", "query": "SELECT COUNT(T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Aruba\"", "question": "How many languages are spoken in Aruba?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many official languages does Afghanistan have?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Afghanistan\" AND IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT COUNT(*) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Afghanistan\" AND IsOfficial = \"T\"", "question": "How many official languages does Afghanistan have?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many official languages are spoken in Afghanistan?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Afghanistan\" AND IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT COUNT(*) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = \"Afghanistan\" AND IsOfficial = \"T\"", "question": "How many official languages are spoken in Afghanistan?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is name of the country that speaks the largest number of languages?\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name ORDER BY COUNT(*) DESC LIMIT 1", "question": "What is name of the country that speaks the largest number of languages?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name of the nation that uses the greatest amount of languages.\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name ORDER BY COUNT(*) DESC LIMIT 1", "question": "Give the name of the nation that uses the greatest amount of languages.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which continent has the most diverse languages?\n[SQL]:\n", "output": "SELECT T1.Continent FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Continent ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T1.Continent FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Continent ORDER BY COUNT(*) DESC LIMIT 1", "question": "Which continent has the most diverse languages?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which continent speaks the most languages?\n[SQL]:\n", "output": "SELECT T1.Continent FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Continent ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T1.Continent FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Continent ORDER BY COUNT(*) DESC LIMIT 1", "question": "Which continent speaks the most languages?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many countries speak both English and Dutch?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\")", "db_id": "world_1", "query": "SELECT COUNT(*) FROM (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\")", "question": "How many countries speak both English and Dutch?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the number of nations that use English and Dutch?\n[SQL]:\n", "output": "SELECT COUNT(*) FROM (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\")", "db_id": "world_1", "query": "SELECT COUNT(*) FROM (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\")", "question": "What is the number of nations that use English and Dutch?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of nations speak both English and French?\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\"", "db_id": "world_1", "query": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\"", "question": "What are the names of nations speak both English and French?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of nations that speak both English and French.\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\"", "db_id": "world_1", "query": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\"", "question": "Give the names of nations that speak both English and French.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of nations where both English and French are official languages?\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\" AND T2.IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\" AND T2.IsOfficial = \"T\"", "question": "What are the names of nations where both English and French are official languages?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of countries with English and French as official languages.\n[SQL]:\n", "output": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\" AND T2.IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\" INTERSECT SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"French\" AND T2.IsOfficial = \"T\"", "question": "Give the names of countries with English and French as official languages.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the number of distinct continents where Chinese is spoken?\n[SQL]:\n", "output": "SELECT COUNT( DISTINCT Continent) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Chinese\"", "db_id": "world_1", "query": "SELECT COUNT( DISTINCT Continent) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Chinese\"", "question": "What is the number of distinct continents where Chinese is spoken?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many continents speak Chinese?\n[SQL]:\n", "output": "SELECT COUNT( DISTINCT Continent) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Chinese\"", "db_id": "world_1", "query": "SELECT COUNT( DISTINCT Continent) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Chinese\"", "question": "How many continents speak Chinese?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the regions that use English or Dutch?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Region FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" OR T2.Language = \"Dutch\"", "db_id": "world_1", "query": "SELECT DISTINCT T1.Region FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" OR T2.Language = \"Dutch\"", "question": "What are the regions that use English or Dutch?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which regions speak Dutch or English?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Region FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" OR T2.Language = \"Dutch\"", "db_id": "world_1", "query": "SELECT DISTINCT T1.Region FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" OR T2.Language = \"Dutch\"", "question": "Which regions speak Dutch or English?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the countries where either English or Dutch is the official language ?\n[SQL]:\n", "output": "select t1.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode where t2.language = \"english\" and isofficial = \"t\" union select t1.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode where t2.language = \"dutch\" and isofficial = \"t\"", "db_id": "world_1", "query": "select t1.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode where t2.language = \"english\" and isofficial = \"t\" union select t1.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode where t2.language = \"dutch\" and isofficial = \"t\"", "question": "What are the countries where either English or Dutch is the official language ?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which countries have either English or Dutch as an official language?\n[SQL]:\n", "output": "SELECT * FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND IsOfficial = \"T\" UNION SELECT * FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\" AND IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT * FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND IsOfficial = \"T\" UNION SELECT * FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"Dutch\" AND IsOfficial = \"T\"", "question": "Which countries have either English or Dutch as an official language?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which language is the most popular on the Asian continent?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = \"Asia\" GROUP BY T2.Language ORDER BY COUNT (*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = \"Asia\" GROUP BY T2.Language ORDER BY COUNT (*) DESC LIMIT 1", "question": "Which language is the most popular on the Asian continent?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the language that is used by the largest number of Asian nations?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = \"Asia\" GROUP BY T2.Language ORDER BY COUNT (*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = \"Asia\" GROUP BY T2.Language ORDER BY COUNT (*) DESC LIMIT 1", "question": "What is the language that is used by the largest number of Asian nations?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which languages are spoken by only one country in republic governments?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.GovernmentForm = \"Republic\" GROUP BY T2.Language HAVING COUNT(*) = 1", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.GovernmentForm = \"Republic\" GROUP BY T2.Language HAVING COUNT(*) = 1", "question": "Which languages are spoken by only one country in republic governments?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What languages are only used by a single country with a republic government?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.GovernmentForm = \"Republic\" GROUP BY T2.Language HAVING COUNT(*) = 1", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.GovernmentForm = \"Republic\" GROUP BY T2.Language HAVING COUNT(*) = 1", "question": "What languages are only used by a single country with a republic government?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the city with the largest population that uses English.\n[SQL]:\n", "output": "SELECT T1.Name , T1.Population FROM city AS T1 JOIN countrylanguage AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Language = \"English\" ORDER BY T1.Population DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T1.Name , T1.Population FROM city AS T1 JOIN countrylanguage AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Language = \"English\" ORDER BY T1.Population DESC LIMIT 1", "question": "Find the city with the largest population that uses English.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the most populace city that speaks English?\n[SQL]:\n", "output": "SELECT T1.Name , T1.Population FROM city AS T1 JOIN countrylanguage AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Language = \"English\" ORDER BY T1.Population DESC LIMIT 1", "db_id": "world_1", "query": "SELECT T1.Name , T1.Population FROM city AS T1 JOIN countrylanguage AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Language = \"English\" ORDER BY T1.Population DESC LIMIT 1", "question": "What is the most populace city that speaks English?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the name, population and expected life length of asian country with the largest area?\n[SQL]:\n", "output": "SELECT Name , Population , LifeExpectancy FROM country WHERE Continent = \"Asia\" ORDER BY SurfaceArea DESC LIMIT 1", "db_id": "world_1", "query": "SELECT Name , Population , LifeExpectancy FROM country WHERE Continent = \"Asia\" ORDER BY SurfaceArea DESC LIMIT 1", "question": "Find the name, population and expected life length of asian country with the largest area?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the name, population, and life expectancy of the largest Asian country by land?\n[SQL]:\n", "output": "SELECT Name , Population , LifeExpectancy FROM country WHERE Continent = \"Asia\" ORDER BY SurfaceArea DESC LIMIT 1", "db_id": "world_1", "query": "SELECT Name , Population , LifeExpectancy FROM country WHERE Continent = \"Asia\" ORDER BY SurfaceArea DESC LIMIT 1", "question": "What are the name, population, and life expectancy of the largest Asian country by land?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is average life expectancy in the countries where English is not the official language?\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\")", "db_id": "world_1", "query": "SELECT avg(LifeExpectancy) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\")", "question": "What is average life expectancy in the countries where English is not the official language?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the mean life expectancy of countries in which English is not the official language.\n[SQL]:\n", "output": "SELECT avg(LifeExpectancy) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\")", "db_id": "world_1", "query": "SELECT avg(LifeExpectancy) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\" AND T2.IsOfficial = \"T\")", "question": "Give the mean life expectancy of countries in which English is not the official language.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of people living in the nations that do not use English?\n[SQL]:\n", "output": "SELECT sum(Population) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\")", "db_id": "world_1", "query": "SELECT sum(Population) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\")", "question": "What is the total number of people living in the nations that do not use English?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many people live in countries that do not speak English?\n[SQL]:\n", "output": "SELECT sum(Population) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\")", "db_id": "world_1", "query": "SELECT sum(Population) FROM country WHERE Name NOT IN (SELECT T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = \"English\")", "question": "How many people live in countries that do not speak English?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the official language spoken in the country whose head of state is Beatrix?\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.HeadOfState = \"Beatrix\" AND T2.IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.HeadOfState = \"Beatrix\" AND T2.IsOfficial = \"T\"", "question": "What is the official language spoken in the country whose head of state is Beatrix?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the official language used in the country the name of whose head of state is Beatrix.\n[SQL]:\n", "output": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.HeadOfState = \"Beatrix\" AND T2.IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT T2.Language FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.HeadOfState = \"Beatrix\" AND T2.IsOfficial = \"T\"", "question": "What is the official language used in the country the name of whose head of state is Beatrix.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of unique official languages spoken in the countries that are founded before 1930?\n[SQL]:\n", "output": "SELECT count(DISTINCT T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE IndepYear < 1930 AND T2.IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT count(DISTINCT T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE IndepYear < 1930 AND T2.IsOfficial = \"T\"", "question": "What is the total number of unique official languages spoken in the countries that are founded before 1930?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:For the countries founded before 1930, what is the total number of distinct official languages?\n[SQL]:\n", "output": "SELECT count(DISTINCT T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE IndepYear < 1930 AND T2.IsOfficial = \"T\"", "db_id": "world_1", "query": "SELECT count(DISTINCT T2.Language) FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode WHERE IndepYear < 1930 AND T2.IsOfficial = \"T\"", "question": "For the countries founded before 1930, what is the total number of distinct official languages?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the countries that have greater surface area than any country in Europe?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE SurfaceArea > (SELECT min(SurfaceArea) FROM country WHERE Continent = \"Europe\")", "db_id": "world_1", "query": "SELECT Name FROM country WHERE SurfaceArea > (SELECT min(SurfaceArea) FROM country WHERE Continent = \"Europe\")", "question": "What are the countries that have greater surface area than any country in Europe?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which countries have greater area than that of any country in Europe?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE SurfaceArea > (SELECT min(SurfaceArea) FROM country WHERE Continent = \"Europe\")", "db_id": "world_1", "query": "SELECT Name FROM country WHERE SurfaceArea > (SELECT min(SurfaceArea) FROM country WHERE Continent = \"Europe\")", "question": "Which countries have greater area than that of any country in Europe?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the African countries that have a population less than any country in Asia?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Africa\" AND population < (SELECT max(population) FROM country WHERE Continent = \"Asia\")", "db_id": "world_1", "query": "SELECT Name FROM country WHERE Continent = \"Africa\" AND population < (SELECT max(population) FROM country WHERE Continent = \"Asia\")", "question": "What are the African countries that have a population less than any country in Asia?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which African countries have a smaller population than that of any country in Asia?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Africa\" AND population < (SELECT min(population) FROM country WHERE Continent = \"Asia\")", "db_id": "world_1", "query": "SELECT Name FROM country WHERE Continent = \"Africa\" AND population < (SELECT min(population) FROM country WHERE Continent = \"Asia\")", "question": "Which African countries have a smaller population than that of any country in Asia?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which Asian countries have a population that is larger than any country in Africa?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" AND population > (SELECT max(population) FROM country WHERE Continent = \"Africa\")", "db_id": "world_1", "query": "SELECT Name FROM country WHERE Continent = \"Asia\" AND population > (SELECT max(population) FROM country WHERE Continent = \"Africa\")", "question": "Which Asian countries have a population that is larger than any country in Africa?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the Asian countries which have a population larger than that of any country in Africa?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE Continent = \"Asia\" AND population > (SELECT min(population) FROM country WHERE Continent = \"Africa\")", "db_id": "world_1", "query": "SELECT Name FROM country WHERE Continent = \"Asia\" AND population > (SELECT min(population) FROM country WHERE Continent = \"Africa\")", "question": "What are the Asian countries which have a population larger than that of any country in Africa?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the country codes for countries that do not speak English?\n[SQL]:\n", "output": "SELECT CountryCode FROM countrylanguage EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "db_id": "world_1", "query": "SELECT CountryCode FROM countrylanguage EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "question": "What are the country codes for countries that do not speak English?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the country codes for countries that do not speak English.\n[SQL]:\n", "output": "SELECT CountryCode FROM countrylanguage EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "db_id": "world_1", "query": "SELECT CountryCode FROM countrylanguage EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "question": "Return the country codes for countries that do not speak English.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the country codes of countries where people use languages other than English?\n[SQL]:\n", "output": "SELECT DISTINCT CountryCode FROM countrylanguage WHERE LANGUAGE != \"English\"", "db_id": "world_1", "query": "SELECT DISTINCT CountryCode FROM countrylanguage WHERE LANGUAGE != \"English\"", "question": "What are the country codes of countries where people use languages other than English?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the country codes for countries in which people speak langauges that are not English.\n[SQL]:\n", "output": "SELECT DISTINCT CountryCode FROM countrylanguage WHERE LANGUAGE != \"English\"", "db_id": "world_1", "query": "SELECT DISTINCT CountryCode FROM countrylanguage WHERE LANGUAGE != \"English\"", "question": "Give the country codes for countries in which people speak langauges that are not English.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the codes of the countries that do not speak English and whose government forms are not Republic?\n[SQL]:\n", "output": "SELECT Code FROM country WHERE GovernmentForm != \"Republic\" EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "db_id": "world_1", "query": "SELECT Code FROM country WHERE GovernmentForm != \"Republic\" EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "question": "What are the codes of the countries that do not speak English and whose government forms are not Republic?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the codes of countries that do not speak English and do not have Republics for governments.\n[SQL]:\n", "output": "SELECT Code FROM country WHERE GovernmentForm != \"Republic\" EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "db_id": "world_1", "query": "SELECT Code FROM country WHERE GovernmentForm != \"Republic\" EXCEPT SELECT CountryCode FROM countrylanguage WHERE LANGUAGE = \"English\"", "question": "Return the codes of countries that do not speak English and do not have Republics for governments.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which cities are in European countries where English is not the official language?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Name FROM country AS T1 JOIN city AS T2 ON T2.CountryCode = T1.Code WHERE T1.Continent = 'Europe' AND T1.Name NOT IN (SELECT T3.Name FROM country AS T3 JOIN countrylanguage AS T4 ON T3.Code = T4.CountryCode WHERE T4.IsOfficial = 'T' AND T4.Language = 'English')", "db_id": "world_1", "query": "SELECT DISTINCT T2.Name FROM country AS T1 JOIN city AS T2 ON T2.CountryCode = T1.Code WHERE T1.Continent = 'Europe' AND T1.Name NOT IN (SELECT T3.Name FROM country AS T3 JOIN countrylanguage AS T4 ON T3.Code = T4.CountryCode WHERE T4.IsOfficial = 'T' AND T4.Language = 'English')", "question": "Which cities are in European countries where English is not the official language?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of cities in Europe for which English is not the official language?\n[SQL]:\n", "output": "SELECT DISTINCT T2.Name FROM country AS T1 JOIN city AS T2 ON T2.CountryCode = T1.Code WHERE T1.Continent = 'Europe' AND T1.Name NOT IN (SELECT T3.Name FROM country AS T3 JOIN countrylanguage AS T4 ON T3.Code = T4.CountryCode WHERE T4.IsOfficial = 'T' AND T4.Language = 'English')", "db_id": "world_1", "query": "SELECT DISTINCT T2.Name FROM country AS T1 JOIN city AS T2 ON T2.CountryCode = T1.Code WHERE T1.Continent = 'Europe' AND T1.Name NOT IN (SELECT T3.Name FROM country AS T3 JOIN countrylanguage AS T4 ON T3.Code = T4.CountryCode WHERE T4.IsOfficial = 'T' AND T4.Language = 'English')", "question": "What are the names of cities in Europe for which English is not the official language?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which unique cities are in Asian countries where Chinese is the official language ?\n[SQL]:\n", "output": "select distinct t3.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode join city as t3 on t1.code = t3.countrycode where t2.isofficial = 't' and t2.language = 'chinese' and t1.continent = \"asia\"", "db_id": "world_1", "query": "select distinct t3.name from country as t1 join countrylanguage as t2 on t1.code = t2.countrycode join city as t3 on t1.code = t3.countrycode where t2.isofficial = 't' and t2.language = 'chinese' and t1.continent = \"asia\"", "question": "Which unique cities are in Asian countries where Chinese is the official language ?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the different names of cities that are in Asia and for which Chinese is the official language.\n[SQL]:\n", "output": "SELECT DISTINCT T3.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode JOIN city AS T3 ON T1.Code = T3.CountryCode WHERE T2.IsOfficial = 'T' AND T2.Language = 'Chinese' AND T1.Continent = \"Asia\"", "db_id": "world_1", "query": "SELECT DISTINCT T3.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode JOIN city AS T3 ON T1.Code = T3.CountryCode WHERE T2.IsOfficial = 'T' AND T2.Language = 'Chinese' AND T1.Continent = \"Asia\"", "question": "Return the different names of cities that are in Asia and for which Chinese is the official language.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the name, independence year, and surface area of the country with the smallest population?\n[SQL]:\n", "output": "SELECT Name , SurfaceArea , IndepYear FROM country ORDER BY Population LIMIT 1", "db_id": "world_1", "query": "SELECT Name , SurfaceArea , IndepYear FROM country ORDER BY Population LIMIT 1", "question": "What are the name, independence year, and surface area of the country with the smallest population?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name, year of independence, and surface area of the country that has the lowest population.\n[SQL]:\n", "output": "SELECT Name , SurfaceArea , IndepYear FROM country ORDER BY Population LIMIT 1", "db_id": "world_1", "query": "SELECT Name , SurfaceArea , IndepYear FROM country ORDER BY Population LIMIT 1", "question": "Give the name, year of independence, and surface area of the country that has the lowest population.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the population, name and leader of the country with the largest area?\n[SQL]:\n", "output": "SELECT Name , population , HeadOfState FROM country ORDER BY SurfaceArea DESC LIMIT 1", "db_id": "world_1", "query": "SELECT Name , population , HeadOfState FROM country ORDER BY SurfaceArea DESC LIMIT 1", "question": "What are the population, name and leader of the country with the largest area?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the name, population, and head of state for the country that has the largest area.\n[SQL]:\n", "output": "SELECT Name , population , HeadOfState FROM country ORDER BY SurfaceArea DESC LIMIT 1", "db_id": "world_1", "query": "SELECT Name , population , HeadOfState FROM country ORDER BY SurfaceArea DESC LIMIT 1", "question": "Give the name, population, and head of state for the country that has the largest area.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the country name and the numbers of languages spoken for each country that speaks at least 3 languages.\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) , T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name HAVING COUNT(*) > 2", "db_id": "world_1", "query": "SELECT COUNT(T2.Language) , T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name HAVING COUNT(*) > 2", "question": "Return the country name and the numbers of languages spoken for each country that speaks at least 3 languages.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of countries that speak more than 2 languages, as well as how many languages they speak?\n[SQL]:\n", "output": "SELECT COUNT(T2.Language) , T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name HAVING COUNT(*) > 2", "db_id": "world_1", "query": "SELECT COUNT(T2.Language) , T1.Name FROM country AS T1 JOIN countrylanguage AS T2 ON T1.Code = T2.CountryCode GROUP BY T1.Name HAVING COUNT(*) > 2", "question": "What are the names of countries that speak more than 2 languages, as well as how many languages they speak?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the number of cities in each district whose population is greater than the average population of cities?\n[SQL]:\n", "output": "SELECT count(*) , District FROM city WHERE Population > (SELECT avg(Population) FROM city) GROUP BY District", "db_id": "world_1", "query": "SELECT count(*) , District FROM city WHERE Population > (SELECT avg(Population) FROM city) GROUP BY District", "question": "Find the number of cities in each district whose population is greater than the average population of cities?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:How many cities in each district have a population that is above the average population across all cities?\n[SQL]:\n", "output": "SELECT count(*) , District FROM city WHERE Population > (SELECT avg(Population) FROM city) GROUP BY District", "db_id": "world_1", "query": "SELECT count(*) , District FROM city WHERE Population > (SELECT avg(Population) FROM city) GROUP BY District", "question": "How many cities in each district have a population that is above the average population across all cities?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the government form name and total population for each government form whose average life expectancy is longer than 72.\n[SQL]:\n", "output": "SELECT sum(Population) , GovernmentForm FROM country GROUP BY GovernmentForm HAVING avg(LifeExpectancy) > 72", "db_id": "world_1", "query": "SELECT sum(Population) , GovernmentForm FROM country GROUP BY GovernmentForm HAVING avg(LifeExpectancy) > 72", "question": "Find the government form name and total population for each government form whose average life expectancy is longer than 72.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the different government forms and what is the total population of each for government forms that have an average life expectancy greater than 72?\n[SQL]:\n", "output": "SELECT sum(Population) , GovernmentForm FROM country GROUP BY GovernmentForm HAVING avg(LifeExpectancy) > 72", "db_id": "world_1", "query": "SELECT sum(Population) , GovernmentForm FROM country GROUP BY GovernmentForm HAVING avg(LifeExpectancy) > 72", "question": "What are the different government forms and what is the total population of each for government forms that have an average life expectancy greater than 72?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Find the average life expectancy and total population for each continent where the average life expectancy is shorter than 72?\n[SQL]:\n", "output": "SELECT sum(Population) , avg(LifeExpectancy) , Continent FROM country GROUP BY Continent HAVING avg(LifeExpectancy) < 72", "db_id": "world_1", "query": "SELECT sum(Population) , avg(LifeExpectancy) , Continent FROM country GROUP BY Continent HAVING avg(LifeExpectancy) < 72", "question": "Find the average life expectancy and total population for each continent where the average life expectancy is shorter than 72?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the different continents and the total popuation and average life expectancy corresponding to each, for continents that have an average life expectancy less than 72?\n[SQL]:\n", "output": "SELECT sum(Population) , avg(LifeExpectancy) , Continent FROM country GROUP BY Continent HAVING avg(LifeExpectancy) < 72", "db_id": "world_1", "query": "SELECT sum(Population) , avg(LifeExpectancy) , Continent FROM country GROUP BY Continent HAVING avg(LifeExpectancy) < 72", "question": "What are the different continents and the total popuation and average life expectancy corresponding to each, for continents that have an average life expectancy less than 72?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names and areas of countries with the top 5 largest area?\n[SQL]:\n", "output": "SELECT Name , SurfaceArea FROM country ORDER BY SurfaceArea DESC LIMIT 5", "db_id": "world_1", "query": "SELECT Name , SurfaceArea FROM country ORDER BY SurfaceArea DESC LIMIT 5", "question": "What are the names and areas of countries with the top 5 largest area?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names and surface areas of the 5 largest countries.\n[SQL]:\n", "output": "SELECT Name , SurfaceArea FROM country ORDER BY SurfaceArea DESC LIMIT 5", "db_id": "world_1", "query": "SELECT Name , SurfaceArea FROM country ORDER BY SurfaceArea DESC LIMIT 5", "question": "Return the names and surface areas of the 5 largest countries.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are names of countries with the top 3 largest population?\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population DESC LIMIT 3", "db_id": "world_1", "query": "SELECT Name FROM country ORDER BY Population DESC LIMIT 3", "question": "What are names of countries with the top 3 largest population?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names of the 3 most populated countries.\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population DESC LIMIT 3", "db_id": "world_1", "query": "SELECT Name FROM country ORDER BY Population DESC LIMIT 3", "question": "Return the names of the 3 most populated countries.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of the nations with the 3 lowest populations?\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population ASC LIMIT 3", "db_id": "world_1", "query": "SELECT Name FROM country ORDER BY Population ASC LIMIT 3", "question": "What are the names of the nations with the 3 lowest populations?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names of the 3 countries with the fewest people.\n[SQL]:\n", "output": "SELECT Name FROM country ORDER BY Population ASC LIMIT 3", "db_id": "world_1", "query": "SELECT Name FROM country ORDER BY Population ASC LIMIT 3", "question": "Return the names of the 3 countries with the fewest people.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:how many countries are in Asia?\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE continent = \"Asia\"", "db_id": "world_1", "query": "SELECT count(*) FROM country WHERE continent = \"Asia\"", "question": "how many countries are in Asia?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Count the number of countries in Asia.\n[SQL]:\n", "output": "SELECT count(*) FROM country WHERE continent = \"Asia\"", "db_id": "world_1", "query": "SELECT count(*) FROM country WHERE continent = \"Asia\"", "question": "Count the number of countries in Asia.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the names of the countries that are in the continent of Europe and have a population of 80000?\n[SQL]:\n", "output": "SELECT Name FROM country WHERE continent = \"Europe\" AND Population = \"80000\"", "db_id": "world_1", "query": "SELECT Name FROM country WHERE continent = \"Europe\" AND Population = \"80000\"", "question": "What are the names of the countries that are in the continent of Europe and have a population of 80000?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the names of countries that are in Europe and have a population equal to 80000.\n[SQL]:\n", "output": "SELECT Name FROM country WHERE continent = \"Europe\" AND Population = \"80000\"", "db_id": "world_1", "query": "SELECT Name FROM country WHERE continent = \"Europe\" AND Population = \"80000\"", "question": "Give the names of countries that are in Europe and have a population equal to 80000.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total population and average area of countries in the continent of North America whose area is bigger than 3000 ?\n[SQL]:\n", "output": "select sum(population) , avg(surfacearea) from country where continent = \"north america\" and surfacearea > 3000", "db_id": "world_1", "query": "select sum(population) , avg(surfacearea) from country where continent = \"north america\" and surfacearea > 3000", "question": "What is the total population and average area of countries in the continent of North America whose area is bigger than 3000 ?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the total population and average surface area corresponding to countries in North America that have a surface area greater than 3000 .\n[SQL]:\n", "output": "select sum(population) , avg(surfacearea) from country where continent = \"north america\" and surfacearea > 3000", "db_id": "world_1", "query": "select sum(population) , avg(surfacearea) from country where continent = \"north america\" and surfacearea > 3000", "question": "Give the total population and average surface area corresponding to countries in North America that have a surface area greater than 3000 .", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the cities whose population is between 160000 and 900000?\n[SQL]:\n", "output": "SELECT name FROM city WHERE Population BETWEEN 160000 AND 900000", "db_id": "world_1", "query": "SELECT name FROM city WHERE Population BETWEEN 160000 AND 900000", "question": "What are the cities whose population is between 160000 and 900000?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the names of cities that have a population between 160000 and 900000 .\n[SQL]:\n", "output": "select name from city where population between 160000 and 900000", "db_id": "world_1", "query": "select name from city where population between 160000 and 900000", "question": "Return the names of cities that have a population between 160000 and 900000 .", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Which language is spoken by the largest number of countries?\n[SQL]:\n", "output": "SELECT LANGUAGE FROM countrylanguage GROUP BY LANGUAGE ORDER BY count(*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT LANGUAGE FROM countrylanguage GROUP BY LANGUAGE ORDER BY count(*) DESC LIMIT 1", "question": "Which language is spoken by the largest number of countries?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Give the language that is spoken in the most countries.\n[SQL]:\n", "output": "SELECT LANGUAGE FROM countrylanguage GROUP BY LANGUAGE ORDER BY count(*) DESC LIMIT 1", "db_id": "world_1", "query": "SELECT LANGUAGE FROM countrylanguage GROUP BY LANGUAGE ORDER BY count(*) DESC LIMIT 1", "question": "Give the language that is spoken in the most countries.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the language spoken by the largest percentage of people in each country?\n[SQL]:\n", "output": "SELECT LANGUAGE , CountryCode , max(Percentage) FROM countrylanguage GROUP BY CountryCode", "db_id": "world_1", "query": "SELECT LANGUAGE , CountryCode , max(Percentage) FROM countrylanguage GROUP BY CountryCode", "question": "What is the language spoken by the largest percentage of people in each country?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the country codes of the different countries, and what are the languages spoken by the greatest percentage of people for each?\n[SQL]:\n", "output": "SELECT LANGUAGE , CountryCode , max(Percentage) FROM countrylanguage GROUP BY CountryCode", "db_id": "world_1", "query": "SELECT LANGUAGE , CountryCode , max(Percentage) FROM countrylanguage GROUP BY CountryCode", "question": "What are the country codes of the different countries, and what are the languages spoken by the greatest percentage of people for each?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What is the total number of countries where Spanish is spoken by the largest percentage of people?\n[SQL]:\n", "output": "SELECT count(*) , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "db_id": "world_1", "query": "SELECT count(*) , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "question": "What is the total number of countries where Spanish is spoken by the largest percentage of people?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Count the number of countries for which Spanish is the predominantly spoken language.\n[SQL]:\n", "output": "SELECT count(*) , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "db_id": "world_1", "query": "SELECT count(*) , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "question": "Count the number of countries for which Spanish is the predominantly spoken language.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:What are the codes of countries where Spanish is spoken by the largest percentage of people?\n[SQL]:\n", "output": "SELECT CountryCode , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "db_id": "world_1", "query": "SELECT CountryCode , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "question": "What are the codes of countries where Spanish is spoken by the largest percentage of people?", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);\"\n[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode\"\n[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code\"\nAnswer the following question with a SQL Statement:Return the codes of countries for which Spanish is the predominantly spoken language.\n[SQL]:\n", "output": "SELECT CountryCode , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "db_id": "world_1", "query": "SELECT CountryCode , max(Percentage) FROM countrylanguage WHERE LANGUAGE = \"Spanish\" GROUP BY CountryCode", "question": "Return the codes of countries for which Spanish is the predominantly spoken language.", "schema": "[Schema (values) (types)]: | world_1 | city : id (text) , name (number) , countrycode (text) , district (text) , population (text) | sqlite_sequence : name (text) , seq (number) | country : code (text) , name (number) , continent (text) , region (text) , surfacearea (text) , indepyear (number) , population (text) , lifeexpectancy (text) , gnp (text) , gnpold (text) , localname (text) , governmentform (text) , headofstate (number) , capital (number) , code2 (number) | countrylanguage : countrycode (text) , language (number) , isofficial (text) , percentage (text);", "primary_keys": "[Primary Keys]: city : id, sqlite_sequence : code, country : countrycode", "foreign_keys": "[Foreign Keys]: city : countrycode = country : code | countrylanguage : countrycode = country : code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:How many conductors are there?\n[SQL]:\n", "output": "SELECT count(*) FROM conductor", "db_id": "orchestra", "query": "SELECT count(*) FROM conductor", "question": "How many conductors are there?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Count the number of conductors.\n[SQL]:\n", "output": "SELECT count(*) FROM conductor", "db_id": "orchestra", "query": "SELECT count(*) FROM conductor", "question": "Count the number of conductors.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the names of conductors in ascending order of age.\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Age ASC", "db_id": "orchestra", "query": "SELECT Name FROM conductor ORDER BY Age ASC", "question": "List the names of conductors in ascending order of age.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors, ordered by age?\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Age ASC", "db_id": "orchestra", "query": "SELECT Name FROM conductor ORDER BY Age ASC", "question": "What are the names of conductors, ordered by age?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors whose nationalities are not \"USA\"?\n[SQL]:\n", "output": "SELECT Name FROM conductor WHERE Nationality != 'USA'", "db_id": "orchestra", "query": "SELECT Name FROM conductor WHERE Nationality != 'USA'", "question": "What are the names of conductors whose nationalities are not \"USA\"?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the names of conductors that do not have the nationality \"USA\".\n[SQL]:\n", "output": "SELECT Name FROM conductor WHERE Nationality != 'USA'", "db_id": "orchestra", "query": "SELECT Name FROM conductor WHERE Nationality != 'USA'", "question": "Return the names of conductors that do not have the nationality \"USA\".", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the record companies of orchestras in descending order of years in which they were founded?\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra ORDER BY Year_of_Founded DESC", "db_id": "orchestra", "query": "SELECT Record_Company FROM orchestra ORDER BY Year_of_Founded DESC", "question": "What are the record companies of orchestras in descending order of years in which they were founded?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the record companies of orchestras, sorted descending by the years in which they were founded.\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra ORDER BY Year_of_Founded DESC", "db_id": "orchestra", "query": "SELECT Record_Company FROM orchestra ORDER BY Year_of_Founded DESC", "question": "Return the record companies of orchestras, sorted descending by the years in which they were founded.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the average attendance of shows?\n[SQL]:\n", "output": "SELECT avg(Attendance) FROM SHOW", "db_id": "orchestra", "query": "SELECT avg(Attendance) FROM SHOW", "question": "What is the average attendance of shows?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the average attendance across all shows.\n[SQL]:\n", "output": "SELECT avg(Attendance) FROM SHOW", "db_id": "orchestra", "query": "SELECT avg(Attendance) FROM SHOW", "question": "Return the average attendance across all shows.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the maximum and minimum share of performances whose type is not \"Live final\".\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM performance WHERE TYPE != \"Live final\"", "db_id": "orchestra", "query": "SELECT max(SHARE) , min(SHARE) FROM performance WHERE TYPE != \"Live final\"", "question": "What are the maximum and minimum share of performances whose type is not \"Live final\".", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Return the maximum and minimum shares for performances that do not have the type \"Live final\".\n[SQL]:\n", "output": "SELECT max(SHARE) , min(SHARE) FROM performance WHERE TYPE != \"Live final\"", "db_id": "orchestra", "query": "SELECT max(SHARE) , min(SHARE) FROM performance WHERE TYPE != \"Live final\"", "question": "Return the maximum and minimum shares for performances that do not have the type \"Live final\".", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:How many different nationalities do conductors have?\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM conductor", "db_id": "orchestra", "query": "SELECT count(DISTINCT Nationality) FROM conductor", "question": "How many different nationalities do conductors have?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Count the number of different nationalities of conductors.\n[SQL]:\n", "output": "SELECT count(DISTINCT Nationality) FROM conductor", "db_id": "orchestra", "query": "SELECT count(DISTINCT Nationality) FROM conductor", "question": "Count the number of different nationalities of conductors.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List names of conductors in descending order of years of work.\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC", "db_id": "orchestra", "query": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC", "question": "List names of conductors in descending order of years of work.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors, sorted descending by the number of years they have worked?\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC", "db_id": "orchestra", "query": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC", "question": "What are the names of conductors, sorted descending by the number of years they have worked?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the name of the conductor with the most years of work.\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC LIMIT 1", "db_id": "orchestra", "query": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC LIMIT 1", "question": "List the name of the conductor with the most years of work.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the name of the conductor who has worked the greatest number of years?\n[SQL]:\n", "output": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC LIMIT 1", "db_id": "orchestra", "query": "SELECT Name FROM conductor ORDER BY Year_of_Work DESC LIMIT 1", "question": "What is the name of the conductor who has worked the greatest number of years?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the names of conductors and the orchestras they have conducted.\n[SQL]:\n", "output": "SELECT T1.Name , T2.Orchestra FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID", "db_id": "orchestra", "query": "SELECT T1.Name , T2.Orchestra FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID", "question": "Show the names of conductors and the orchestras they have conducted.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors as well as the corresonding orchestras that they have conducted?\n[SQL]:\n", "output": "SELECT T1.Name , T2.Orchestra FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID", "db_id": "orchestra", "query": "SELECT T1.Name , T2.Orchestra FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID", "question": "What are the names of conductors as well as the corresonding orchestras that they have conducted?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the names of conductors that have conducted more than one orchestras.\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID HAVING COUNT(*) > 1", "db_id": "orchestra", "query": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID HAVING COUNT(*) > 1", "question": "Show the names of conductors that have conducted more than one orchestras.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors who have conducted at more than one orchestra?\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID HAVING COUNT(*) > 1", "db_id": "orchestra", "query": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID HAVING COUNT(*) > 1", "question": "What are the names of conductors who have conducted at more than one orchestra?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the name of the conductor that has conducted the most number of orchestras.\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "orchestra", "query": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID ORDER BY COUNT(*) DESC LIMIT 1", "question": "Show the name of the conductor that has conducted the most number of orchestras.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the name of the conductor who has conducted the most orchestras?\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "orchestra", "query": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID GROUP BY T2.Conductor_ID ORDER BY COUNT(*) DESC LIMIT 1", "question": "What is the name of the conductor who has conducted the most orchestras?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Please show the name of the conductor that has conducted orchestras founded after 2008.\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID WHERE Year_of_Founded > 2008", "db_id": "orchestra", "query": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID WHERE Year_of_Founded > 2008", "question": "Please show the name of the conductor that has conducted orchestras founded after 2008.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the names of conductors who have conducted orchestras founded after the year 2008?\n[SQL]:\n", "output": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID WHERE Year_of_Founded > 2008", "db_id": "orchestra", "query": "SELECT T1.Name FROM conductor AS T1 JOIN orchestra AS T2 ON T1.Conductor_ID = T2.Conductor_ID WHERE Year_of_Founded > 2008", "question": "What are the names of conductors who have conducted orchestras founded after the year 2008?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Please show the different record companies and the corresponding number of orchestras.\n[SQL]:\n", "output": "SELECT Record_Company , COUNT(*) FROM orchestra GROUP BY Record_Company", "db_id": "orchestra", "query": "SELECT Record_Company , COUNT(*) FROM orchestra GROUP BY Record_Company", "question": "Please show the different record companies and the corresponding number of orchestras.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:How many orchestras does each record company manage?\n[SQL]:\n", "output": "SELECT Record_Company , COUNT(*) FROM orchestra GROUP BY Record_Company", "db_id": "orchestra", "query": "SELECT Record_Company , COUNT(*) FROM orchestra GROUP BY Record_Company", "question": "How many orchestras does each record company manage?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Please show the record formats of orchestras in ascending order of count.\n[SQL]:\n", "output": "SELECT Major_Record_Format FROM orchestra GROUP BY Major_Record_Format ORDER BY COUNT(*) ASC", "db_id": "orchestra", "query": "SELECT Major_Record_Format FROM orchestra GROUP BY Major_Record_Format ORDER BY COUNT(*) ASC", "question": "Please show the record formats of orchestras in ascending order of count.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the major record formats of orchestras, sorted by their frequency?\n[SQL]:\n", "output": "SELECT Major_Record_Format FROM orchestra GROUP BY Major_Record_Format ORDER BY COUNT(*) ASC", "db_id": "orchestra", "query": "SELECT Major_Record_Format FROM orchestra GROUP BY Major_Record_Format ORDER BY COUNT(*) ASC", "question": "What are the major record formats of orchestras, sorted by their frequency?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the record company shared by the most number of orchestras.\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra GROUP BY Record_Company ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "orchestra", "query": "SELECT Record_Company FROM orchestra GROUP BY Record_Company ORDER BY COUNT(*) DESC LIMIT 1", "question": "List the record company shared by the most number of orchestras.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What is the record company used by the greatest number of orchestras?\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra GROUP BY Record_Company ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "orchestra", "query": "SELECT Record_Company FROM orchestra GROUP BY Record_Company ORDER BY COUNT(*) DESC LIMIT 1", "question": "What is the record company used by the greatest number of orchestras?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:List the names of orchestras that have no performance.\n[SQL]:\n", "output": "SELECT Orchestra FROM orchestra WHERE Orchestra_ID NOT IN (SELECT Orchestra_ID FROM performance)", "db_id": "orchestra", "query": "SELECT Orchestra FROM orchestra WHERE Orchestra_ID NOT IN (SELECT Orchestra_ID FROM performance)", "question": "List the names of orchestras that have no performance.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the orchestras that do not have any performances?\n[SQL]:\n", "output": "SELECT Orchestra FROM orchestra WHERE Orchestra_ID NOT IN (SELECT Orchestra_ID FROM performance)", "db_id": "orchestra", "query": "SELECT Orchestra FROM orchestra WHERE Orchestra_ID NOT IN (SELECT Orchestra_ID FROM performance)", "question": "What are the orchestras that do not have any performances?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the record companies shared by orchestras founded before 2003 and after 2003.\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra WHERE Year_of_Founded < 2003 INTERSECT SELECT Record_Company FROM orchestra WHERE Year_of_Founded > 2003", "db_id": "orchestra", "query": "SELECT Record_Company FROM orchestra WHERE Year_of_Founded < 2003 INTERSECT SELECT Record_Company FROM orchestra WHERE Year_of_Founded > 2003", "question": "Show the record companies shared by orchestras founded before 2003 and after 2003.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are the record companies that are used by both orchestras founded before 2003 and those founded after 2003?\n[SQL]:\n", "output": "SELECT Record_Company FROM orchestra WHERE Year_of_Founded < 2003 INTERSECT SELECT Record_Company FROM orchestra WHERE Year_of_Founded > 2003", "db_id": "orchestra", "query": "SELECT Record_Company FROM orchestra WHERE Year_of_Founded < 2003 INTERSECT SELECT Record_Company FROM orchestra WHERE Year_of_Founded > 2003", "question": "What are the record companies that are used by both orchestras founded before 2003 and those founded after 2003?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Find the number of orchestras whose record format is \"CD\" or \"DVD\".\n[SQL]:\n", "output": "SELECT COUNT(*) FROM orchestra WHERE Major_Record_Format = \"CD\" OR Major_Record_Format = \"DVD\"", "db_id": "orchestra", "query": "SELECT COUNT(*) FROM orchestra WHERE Major_Record_Format = \"CD\" OR Major_Record_Format = \"DVD\"", "question": "Find the number of orchestras whose record format is \"CD\" or \"DVD\".", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Count the number of orchestras that have CD or DVD as their record format.\n[SQL]:\n", "output": "SELECT COUNT(*) FROM orchestra WHERE Major_Record_Format = \"CD\" OR Major_Record_Format = \"DVD\"", "db_id": "orchestra", "query": "SELECT COUNT(*) FROM orchestra WHERE Major_Record_Format = \"CD\" OR Major_Record_Format = \"DVD\"", "question": "Count the number of orchestras that have CD or DVD as their record format.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:Show the years in which orchestras that have given more than one performance are founded.\n[SQL]:\n", "output": "SELECT Year_of_Founded FROM orchestra AS T1 JOIN performance AS T2 ON T1.Orchestra_ID = T2.Orchestra_ID GROUP BY T2.Orchestra_ID HAVING COUNT(*) > 1", "db_id": "orchestra", "query": "SELECT Year_of_Founded FROM orchestra AS T1 JOIN performance AS T2 ON T1.Orchestra_ID = T2.Orchestra_ID GROUP BY T2.Orchestra_ID HAVING COUNT(*) > 1", "question": "Show the years in which orchestras that have given more than one performance are founded.", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);\"\n[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id\"\n[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id\"\nAnswer the following question with a SQL Statement:What are years of founding for orchestras that have had more than a single performance?\n[SQL]:\n", "output": "SELECT Year_of_Founded FROM orchestra AS T1 JOIN performance AS T2 ON T1.Orchestra_ID = T2.Orchestra_ID GROUP BY T2.Orchestra_ID HAVING COUNT(*) > 1", "db_id": "orchestra", "query": "SELECT Year_of_Founded FROM orchestra AS T1 JOIN performance AS T2 ON T1.Orchestra_ID = T2.Orchestra_ID GROUP BY T2.Orchestra_ID HAVING COUNT(*) > 1", "question": "What are years of founding for orchestras that have had more than a single performance?", "schema": "[Schema (values) (types)]: | orchestra | conductor : conductor_id (text) , name (number) , age (text) , nationality (number) , year_of_work (text) | orchestra : orchestra_id (text) , orchestra (number) , conductor_id (text) , record_company (number) , year_of_founded (text) , major_record_format (number) | performance : performance_id (text) , orchestra_id (number) , type (text) , date (number) , official_ratings_(millions) (text) , weekly_rank (number) , share (number) | show : show_id (text) , performance_id (number) , if_first_show (text) , result (number) , attendance (text);", "primary_keys": "[Primary Keys]: conductor : conductor_id, orchestra : orchestra_id, performance : performance_id", "foreign_keys": "[Foreign Keys]: orchestra : conductor_id = conductor : conductor_id | performance : orchestra_id = orchestra : orchestra_id | show : performance_id = performance : performance_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many high schoolers are there?\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler", "db_id": "network_1", "query": "SELECT count(*) FROM Highschooler", "question": "How many high schoolers are there?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of high schoolers.\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler", "db_id": "network_1", "query": "SELECT count(*) FROM Highschooler", "question": "Count the number of high schoolers.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names and grades of each high schooler.\n[SQL]:\n", "output": "SELECT name , grade FROM Highschooler", "db_id": "network_1", "query": "SELECT name , grade FROM Highschooler", "question": "Show the names and grades of each high schooler.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names and grades for each high schooler?\n[SQL]:\n", "output": "SELECT name , grade FROM Highschooler", "db_id": "network_1", "query": "SELECT name , grade FROM Highschooler", "question": "What are the names and grades for each high schooler?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show all the grades of the high schoolers.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler", "db_id": "network_1", "query": "SELECT grade FROM Highschooler", "question": "Show all the grades of the high schoolers.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the grade of each high schooler?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler", "db_id": "network_1", "query": "SELECT grade FROM Highschooler", "question": "What is the grade of each high schooler?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What grade is Kyle in?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler WHERE name = \"Kyle\"", "db_id": "network_1", "query": "SELECT grade FROM Highschooler WHERE name = \"Kyle\"", "question": "What grade is Kyle in?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the grade for the high schooler named Kyle.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler WHERE name = \"Kyle\"", "db_id": "network_1", "query": "SELECT grade FROM Highschooler WHERE name = \"Kyle\"", "question": "Return the grade for the high schooler named Kyle.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of all high schoolers in grade 10.\n[SQL]:\n", "output": "SELECT name FROM Highschooler WHERE grade = 10", "db_id": "network_1", "query": "SELECT name FROM Highschooler WHERE grade = 10", "question": "Show the names of all high schoolers in grade 10.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of all high schoolers in grade 10?\n[SQL]:\n", "output": "SELECT name FROM Highschooler WHERE grade = 10", "db_id": "network_1", "query": "SELECT name FROM Highschooler WHERE grade = 10", "question": "What are the names of all high schoolers in grade 10?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the ID of the high schooler named Kyle.\n[SQL]:\n", "output": "SELECT ID FROM Highschooler WHERE name = \"Kyle\"", "db_id": "network_1", "query": "SELECT ID FROM Highschooler WHERE name = \"Kyle\"", "question": "Show the ID of the high schooler named Kyle.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is Kyle's id?\n[SQL]:\n", "output": "SELECT ID FROM Highschooler WHERE name = \"Kyle\"", "db_id": "network_1", "query": "SELECT ID FROM Highschooler WHERE name = \"Kyle\"", "question": "What is Kyle's id?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many high schoolers are there in grade 9 or 10?\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler WHERE grade = 9 OR grade = 10", "db_id": "network_1", "query": "SELECT count(*) FROM Highschooler WHERE grade = 9 OR grade = 10", "question": "How many high schoolers are there in grade 9 or 10?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of high schoolers in grades 9 or 10.\n[SQL]:\n", "output": "SELECT count(*) FROM Highschooler WHERE grade = 9 OR grade = 10", "db_id": "network_1", "query": "SELECT count(*) FROM Highschooler WHERE grade = 9 OR grade = 10", "question": "Count the number of high schoolers in grades 9 or 10.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the number of high schoolers for each grade.\n[SQL]:\n", "output": "SELECT grade , count(*) FROM Highschooler GROUP BY grade", "db_id": "network_1", "query": "SELECT grade , count(*) FROM Highschooler GROUP BY grade", "question": "Show the number of high schoolers for each grade.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many high schoolers are in each grade?\n[SQL]:\n", "output": "SELECT grade , count(*) FROM Highschooler GROUP BY grade", "db_id": "network_1", "query": "SELECT grade , count(*) FROM Highschooler GROUP BY grade", "question": "How many high schoolers are in each grade?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Which grade has the most high schoolers?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade ORDER BY count(*) DESC LIMIT 1", "db_id": "network_1", "query": "SELECT grade FROM Highschooler GROUP BY grade ORDER BY count(*) DESC LIMIT 1", "question": "Which grade has the most high schoolers?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the grade that has the greatest number of high schoolers.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade ORDER BY count(*) DESC LIMIT 1", "db_id": "network_1", "query": "SELECT grade FROM Highschooler GROUP BY grade ORDER BY count(*) DESC LIMIT 1", "question": "Return the grade that has the greatest number of high schoolers.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show me all grades that have at least 4 students.\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade HAVING count(*) >= 4", "db_id": "network_1", "query": "SELECT grade FROM Highschooler GROUP BY grade HAVING count(*) >= 4", "question": "Show me all grades that have at least 4 students.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Which grades have 4 or more high schoolers?\n[SQL]:\n", "output": "SELECT grade FROM Highschooler GROUP BY grade HAVING count(*) >= 4", "db_id": "network_1", "query": "SELECT grade FROM Highschooler GROUP BY grade HAVING count(*) >= 4", "question": "Which grades have 4 or more high schoolers?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the student IDs and numbers of friends corresponding to each.\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Friend GROUP BY student_id", "db_id": "network_1", "query": "SELECT student_id , count(*) FROM Friend GROUP BY student_id", "question": "Show the student IDs and numbers of friends corresponding to each.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many friends does each student have?\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Friend GROUP BY student_id", "db_id": "network_1", "query": "SELECT student_id , count(*) FROM Friend GROUP BY student_id", "question": "How many friends does each student have?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of high school students and their corresponding number of friends.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "db_id": "network_1", "query": "SELECT T2.name , count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "question": "Show the names of high school students and their corresponding number of friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of the high schoolers and how many friends does each have?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "db_id": "network_1", "query": "SELECT T2.name , count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "question": "What are the names of the high schoolers and how many friends does each have?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the name of the high schooler who has the greatest number of friends?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the name of the high schooler who has the greatest number of friends?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the name of the high school student with the most friends.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "question": "Return the name of the high school student with the most friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of high schoolers who have at least 3 friends.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 3", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 3", "question": "Show the names of high schoolers who have at least 3 friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who have 3 or more friends?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 3", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 3", "question": "What are the names of high schoolers who have 3 or more friends?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of all of the high schooler Kyle's friends.\n[SQL]:\n", "output": "SELECT T3.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id JOIN Highschooler AS T3 ON T1.friend_id = T3.id WHERE T2.name = \"Kyle\"", "db_id": "network_1", "query": "SELECT T3.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id JOIN Highschooler AS T3 ON T1.friend_id = T3.id WHERE T2.name = \"Kyle\"", "question": "Show the names of all of the high schooler Kyle's friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the names of friends of the high school student Kyle.\n[SQL]:\n", "output": "SELECT T3.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id JOIN Highschooler AS T3 ON T1.friend_id = T3.id WHERE T2.name = \"Kyle\"", "db_id": "network_1", "query": "SELECT T3.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id JOIN Highschooler AS T3 ON T1.friend_id = T3.id WHERE T2.name = \"Kyle\"", "question": "Return the names of friends of the high school student Kyle.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many friends does the high school student Kyle have?\n[SQL]:\n", "output": "SELECT count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "db_id": "network_1", "query": "SELECT count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "question": "How many friends does the high school student Kyle have?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of friends Kyle has.\n[SQL]:\n", "output": "SELECT count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "db_id": "network_1", "query": "SELECT count(*) FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "question": "Count the number of friends Kyle has.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show ids of all students who do not have any friends.\n[SQL]:\n", "output": "SELECT id FROM Highschooler EXCEPT SELECT student_id FROM Friend", "db_id": "network_1", "query": "SELECT id FROM Highschooler EXCEPT SELECT student_id FROM Friend", "question": "Show ids of all students who do not have any friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the ids of high school students who do not have friends?\n[SQL]:\n", "output": "SELECT id FROM Highschooler EXCEPT SELECT student_id FROM Friend", "db_id": "network_1", "query": "SELECT id FROM Highschooler EXCEPT SELECT student_id FROM Friend", "question": "What are the ids of high school students who do not have friends?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show names of all high school students who do not have any friends.\n[SQL]:\n", "output": "SELECT name FROM Highschooler EXCEPT SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id", "db_id": "network_1", "query": "SELECT name FROM Highschooler EXCEPT SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id", "question": "Show names of all high school students who do not have any friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of students who have no friends?\n[SQL]:\n", "output": "SELECT name FROM Highschooler EXCEPT SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id", "db_id": "network_1", "query": "SELECT name FROM Highschooler EXCEPT SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id", "question": "What are the names of students who have no friends?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the ids of high schoolers who have friends and are also liked by someone else.\n[SQL]:\n", "output": "SELECT student_id FROM Friend INTERSECT SELECT liked_id FROM Likes", "db_id": "network_1", "query": "SELECT student_id FROM Friend INTERSECT SELECT liked_id FROM Likes", "question": "Show the ids of high schoolers who have friends and are also liked by someone else.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the ids of students who both have friends and are liked?\n[SQL]:\n", "output": "SELECT student_id FROM Friend INTERSECT SELECT liked_id FROM Likes", "db_id": "network_1", "query": "SELECT student_id FROM Friend INTERSECT SELECT liked_id FROM Likes", "question": "What are the ids of students who both have friends and are liked?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show name of all students who have some friends and also are liked by someone else.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id INTERSECT SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.liked_id = T2.id", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id INTERSECT SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.liked_id = T2.id", "question": "Show name of all students who have some friends and also are liked by someone else.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who both have friends and are liked?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id INTERSECT SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.liked_id = T2.id", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id INTERSECT SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.liked_id = T2.id", "question": "What are the names of high schoolers who both have friends and are liked?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Count the number of likes for each student id.\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Likes GROUP BY student_id", "db_id": "network_1", "query": "SELECT student_id , count(*) FROM Likes GROUP BY student_id", "question": "Count the number of likes for each student id.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many likes correspond to each student id?\n[SQL]:\n", "output": "SELECT student_id , count(*) FROM Likes GROUP BY student_id", "db_id": "network_1", "query": "SELECT student_id , count(*) FROM Likes GROUP BY student_id", "question": "How many likes correspond to each student id?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of high schoolers who have likes, and numbers of likes for each.\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "db_id": "network_1", "query": "SELECT T2.name , count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "question": "Show the names of high schoolers who have likes, and numbers of likes for each.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who have likes, and how many likes does each have?\n[SQL]:\n", "output": "SELECT T2.name , count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "db_id": "network_1", "query": "SELECT T2.name , count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id", "question": "What are the names of high schoolers who have likes, and how many likes does each have?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the name of the high schooler who has the greatest number of likes?\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "db_id": "network_1", "query": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "question": "What is the name of the high schooler who has the greatest number of likes?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Give the name of the student with the most likes.\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "db_id": "network_1", "query": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1", "question": "Give the name of the student with the most likes.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of students who have at least 2 likes.\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 2", "db_id": "network_1", "query": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 2", "question": "Show the names of students who have at least 2 likes.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of students who have 2 or more likes?\n[SQL]:\n", "output": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 2", "db_id": "network_1", "query": "SELECT T2.name FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id GROUP BY T1.student_id HAVING count(*) >= 2", "question": "What are the names of students who have 2 or more likes?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Show the names of students who have a grade higher than 5 and have at least 2 friends.\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.grade > 5 GROUP BY T1.student_id HAVING count(*) >= 2", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.grade > 5 GROUP BY T1.student_id HAVING count(*) >= 2", "question": "Show the names of students who have a grade higher than 5 and have at least 2 friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What are the names of high schoolers who have a grade of over 5 and have 2 or more friends?\n[SQL]:\n", "output": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.grade > 5 GROUP BY T1.student_id HAVING count(*) >= 2", "db_id": "network_1", "query": "SELECT T2.name FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.grade > 5 GROUP BY T1.student_id HAVING count(*) >= 2", "question": "What are the names of high schoolers who have a grade of over 5 and have 2 or more friends?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:How many likes does Kyle have?\n[SQL]:\n", "output": "SELECT count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "db_id": "network_1", "query": "SELECT count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "question": "How many likes does Kyle have?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Return the number of likes that the high schooler named Kyle has.\n[SQL]:\n", "output": "SELECT count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "db_id": "network_1", "query": "SELECT count(*) FROM Likes AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id WHERE T2.name = \"Kyle\"", "question": "Return the number of likes that the high schooler named Kyle has.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Find the average grade of all students who have some friends.\n[SQL]:\n", "output": "SELECT avg(grade) FROM Highschooler WHERE id IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "db_id": "network_1", "query": "SELECT avg(grade) FROM Highschooler WHERE id IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "question": "Find the average grade of all students who have some friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the average grade of students who have friends?\n[SQL]:\n", "output": "SELECT avg(grade) FROM Highschooler WHERE id IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "db_id": "network_1", "query": "SELECT avg(grade) FROM Highschooler WHERE id IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "question": "What is the average grade of students who have friends?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:Find the minimum grade of students who have no friends.\n[SQL]:\n", "output": "SELECT min(grade) FROM Highschooler WHERE id NOT IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "db_id": "network_1", "query": "SELECT min(grade) FROM Highschooler WHERE id NOT IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "question": "Find the minimum grade of students who have no friends.", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);\"\n[Primary Keys]: highschooler : id, friend : student_id, likes : student_id\"\n[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id\"\nAnswer the following question with a SQL Statement:What is the lowest grade of students who do not have any friends?\n[SQL]:\n", "output": "SELECT min(grade) FROM Highschooler WHERE id NOT IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "db_id": "network_1", "query": "SELECT min(grade) FROM Highschooler WHERE id NOT IN (SELECT T1.student_id FROM Friend AS T1 JOIN Highschooler AS T2 ON T1.student_id = T2.id)", "question": "What is the lowest grade of students who do not have any friends?", "schema": "[Schema (values) (types)]: | network_1 | Highschooler : id (text) , name (number) , grade (text) | Friend : student_id (text) , friend_id (number) | Likes : student_id (text) , liked_id (number);", "primary_keys": "[Primary Keys]: highschooler : id, friend : student_id, likes : student_id", "foreign_keys": "[Foreign Keys]: friend : friend_id = highschooler : id | friend : student_id = highschooler : id | likes : student_id = highschooler : id | likes : liked_id = highschooler : id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which states have both owners and professionals living there?\n[SQL]:\n", "output": "SELECT state FROM Owners INTERSECT SELECT state FROM Professionals", "db_id": "dog_kennels", "query": "SELECT state FROM Owners INTERSECT SELECT state FROM Professionals", "question": "Which states have both owners and professionals living there?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the states where both owners and professionals live.\n[SQL]:\n", "output": "SELECT state FROM Owners INTERSECT SELECT state FROM Professionals", "db_id": "dog_kennels", "query": "SELECT state FROM Owners INTERSECT SELECT state FROM Professionals", "question": "Find the states where both owners and professionals live.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the average age of the dogs who have gone through any treatments?\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs WHERE dog_id IN ( SELECT dog_id FROM Treatments )", "db_id": "dog_kennels", "query": "SELECT avg(age) FROM Dogs WHERE dog_id IN ( SELECT dog_id FROM Treatments )", "question": "What is the average age of the dogs who have gone through any treatments?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the average age of the dogs who went through treatments.\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs WHERE dog_id IN ( SELECT dog_id FROM Treatments )", "db_id": "dog_kennels", "query": "SELECT avg(age) FROM Dogs WHERE dog_id IN ( SELECT dog_id FROM Treatments )", "question": "Find the average age of the dogs who went through treatments.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals live in the state of Indiana or have done treatment on more than 2 treatments? List his or her id, last name and cell phone.\n[SQL]:\n", "output": "SELECT professional_id , last_name , cell_number FROM Professionals WHERE state = 'Indiana' UNION SELECT T1.professional_id , T1.last_name , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) > 2", "db_id": "dog_kennels", "query": "SELECT professional_id , last_name , cell_number FROM Professionals WHERE state = 'Indiana' UNION SELECT T1.professional_id , T1.last_name , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) > 2", "question": "Which professionals live in the state of Indiana or have done treatment on more than 2 treatments? List his or her id, last name and cell phone.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the id, last name and cell phone of the professionals who live in the state of Indiana or have performed more than two treatments.\n[SQL]:\n", "output": "SELECT professional_id , last_name , cell_number FROM Professionals WHERE state = 'Indiana' UNION SELECT T1.professional_id , T1.last_name , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) > 2", "db_id": "dog_kennels", "query": "SELECT professional_id , last_name , cell_number FROM Professionals WHERE state = 'Indiana' UNION SELECT T1.professional_id , T1.last_name , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) > 2", "question": "Find the id, last name and cell phone of the professionals who live in the state of Indiana or have performed more than two treatments.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which dogs have not cost their owner more than 1000 for treatment ? List the dog names .\n[SQL]:\n", "output": "select name from dogs where dog_id not in ( select dog_id from treatments group by dog_id having sum(cost_of_treatment) > 1000 )", "db_id": "dog_kennels", "query": "select name from dogs where dog_id not in ( select dog_id from treatments group by dog_id having sum(cost_of_treatment) > 1000 )", "question": "Which dogs have not cost their owner more than 1000 for treatment ? List the dog names .", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the names of the dogs for which the owner has not spend more than 1000 for treatment ?\n[SQL]:\n", "output": "select name from dogs where dog_id not in ( select dog_id from treatments group by dog_id having sum(cost_of_treatment) > 1000 )", "db_id": "dog_kennels", "query": "select name from dogs where dog_id not in ( select dog_id from treatments group by dog_id having sum(cost_of_treatment) > 1000 )", "question": "What are the names of the dogs for which the owner has not spend more than 1000 for treatment ?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which first names are used for professionals or owners but are not used as dog names?\n[SQL]:\n", "output": "SELECT first_name FROM Professionals UNION SELECT first_name FROM Owners EXCEPT SELECT name FROM Dogs", "db_id": "dog_kennels", "query": "SELECT first_name FROM Professionals UNION SELECT first_name FROM Owners EXCEPT SELECT name FROM Dogs", "question": "Which first names are used for professionals or owners but are not used as dog names?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the first names that are used for professionals or owners but are not used as dog names.\n[SQL]:\n", "output": "SELECT first_name FROM Professionals UNION SELECT first_name FROM Owners EXCEPT SELECT name FROM Dogs", "db_id": "dog_kennels", "query": "SELECT first_name FROM Professionals UNION SELECT first_name FROM Owners EXCEPT SELECT name FROM Dogs", "question": "Find the first names that are used for professionals or owners but are not used as dog names.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professional did not operate any treatment on dogs? List the professional's id, role and email.\n[SQL]:\n", "output": "SELECT professional_id , role_code , email_address FROM Professionals EXCEPT SELECT T1.professional_id , T1.role_code , T1.email_address FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id", "db_id": "dog_kennels", "query": "SELECT professional_id , role_code , email_address FROM Professionals EXCEPT SELECT T1.professional_id , T1.role_code , T1.email_address FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id", "question": "Which professional did not operate any treatment on dogs? List the professional's id, role and email.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Give me the id, role and email of the professionals who did not perform any treatment on dogs.\n[SQL]:\n", "output": "SELECT professional_id , role_code , email_address FROM Professionals EXCEPT SELECT T1.professional_id , T1.role_code , T1.email_address FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id", "db_id": "dog_kennels", "query": "SELECT professional_id , role_code , email_address FROM Professionals EXCEPT SELECT T1.professional_id , T1.role_code , T1.email_address FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id", "question": "Give me the id, role and email of the professionals who did not perform any treatment on dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owner owns the most dogs? List the owner id, first name and last name.\n[SQL]:\n", "output": "SELECT T1.owner_id , T2.first_name , T2.last_name FROM Dogs AS T1 JOIN Owners AS T2 ON T1.owner_id = T2.owner_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.owner_id , T2.first_name , T2.last_name FROM Dogs AS T1 JOIN Owners AS T2 ON T1.owner_id = T2.owner_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "question": "Which owner owns the most dogs? List the owner id, first name and last name.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Return the owner id, first name and last name of the owner who has the most dogs.\n[SQL]:\n", "output": "SELECT T1.owner_id , T2.first_name , T2.last_name FROM Dogs AS T1 JOIN Owners AS T2 ON T1.owner_id = T2.owner_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.owner_id , T2.first_name , T2.last_name FROM Dogs AS T1 JOIN Owners AS T2 ON T1.owner_id = T2.owner_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "question": "Return the owner id, first name and last name of the owner who has the most dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals have done at least two treatments? List the professional's id, role, and first name.\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.role_code , T1.first_name FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "db_id": "dog_kennels", "query": "SELECT T1.professional_id , T1.role_code , T1.first_name FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "question": "Which professionals have done at least two treatments? List the professional's id, role, and first name.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the id, role, and first name of the professionals who have performed two or more treatments?\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.role_code , T1.first_name FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "db_id": "dog_kennels", "query": "SELECT T1.professional_id , T1.role_code , T1.first_name FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "question": "What are the id, role, and first name of the professionals who have performed two or more treatments?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the name of the breed with the most dogs?\n[SQL]:\n", "output": "SELECT T1.breed_name FROM Breeds AS T1 JOIN Dogs AS T2 ON T1.breed_code = T2.breed_code GROUP BY T1.breed_name ORDER BY count(*) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.breed_name FROM Breeds AS T1 JOIN Dogs AS T2 ON T1.breed_code = T2.breed_code GROUP BY T1.breed_name ORDER BY count(*) DESC LIMIT 1", "question": "What is the name of the breed with the most dogs?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which breed do the most dogs have? Give me the breed name.\n[SQL]:\n", "output": "SELECT T1.breed_name FROM Breeds AS T1 JOIN Dogs AS T2 ON T1.breed_code = T2.breed_code GROUP BY T1.breed_name ORDER BY count(*) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.breed_name FROM Breeds AS T1 JOIN Dogs AS T2 ON T1.breed_code = T2.breed_code GROUP BY T1.breed_name ORDER BY count(*) DESC LIMIT 1", "question": "Which breed do the most dogs have? Give me the breed name.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owner has paid for the most treatments on his or her dogs? List the owner id and last name.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.owner_id , T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "question": "Which owner has paid for the most treatments on his or her dogs? List the owner id and last name.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Tell me the owner id and last name of the owner who spent the most on treatments of his or her dogs.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.owner_id , T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY count(*) DESC LIMIT 1", "question": "Tell me the owner id and last name of the owner who spent the most on treatments of his or her dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the description of the treatment type that costs the least money in total?\n[SQL]:\n", "output": "SELECT T1.treatment_type_description FROM Treatment_types AS T1 JOIN Treatments AS T2 ON T1.treatment_type_code = T2.treatment_type_code GROUP BY T1.treatment_type_code ORDER BY sum(cost_of_treatment) ASC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.treatment_type_description FROM Treatment_types AS T1 JOIN Treatments AS T2 ON T1.treatment_type_code = T2.treatment_type_code GROUP BY T1.treatment_type_code ORDER BY sum(cost_of_treatment) ASC LIMIT 1", "question": "What is the description of the treatment type that costs the least money in total?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Give me the description of the treatment type whose total cost is the lowest.\n[SQL]:\n", "output": "SELECT T1.treatment_type_description FROM Treatment_types AS T1 JOIN Treatments AS T2 ON T1.treatment_type_code = T2.treatment_type_code GROUP BY T1.treatment_type_code ORDER BY sum(cost_of_treatment) ASC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.treatment_type_description FROM Treatment_types AS T1 JOIN Treatments AS T2 ON T1.treatment_type_code = T2.treatment_type_code GROUP BY T1.treatment_type_code ORDER BY sum(cost_of_treatment) ASC LIMIT 1", "question": "Give me the description of the treatment type whose total cost is the lowest.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owner has paid the largest amount of money in total for their dogs? Show the owner id and zip code.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.zip_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY sum(T3.cost_of_treatment) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.owner_id , T1.zip_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY sum(T3.cost_of_treatment) DESC LIMIT 1", "question": "Which owner has paid the largest amount of money in total for their dogs? Show the owner id and zip code.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the owner id and zip code of the owner who spent the most money in total for his or her dogs.\n[SQL]:\n", "output": "SELECT T1.owner_id , T1.zip_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY sum(T3.cost_of_treatment) DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT T1.owner_id , T1.zip_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id JOIN Treatments AS T3 ON T2.dog_id = T3.dog_id GROUP BY T1.owner_id ORDER BY sum(T3.cost_of_treatment) DESC LIMIT 1", "question": "Find the owner id and zip code of the owner who spent the most money in total for his or her dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals have done at least two types of treatments? List the professional id and cell phone.\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "db_id": "dog_kennels", "query": "SELECT T1.professional_id , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "question": "Which professionals have done at least two types of treatments? List the professional id and cell phone.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the id and cell phone of the professionals who operate two or more types of treatments.\n[SQL]:\n", "output": "SELECT T1.professional_id , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "db_id": "dog_kennels", "query": "SELECT T1.professional_id , T1.cell_number FROM Professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id GROUP BY T1.professional_id HAVING count(*) >= 2", "question": "Find the id and cell phone of the professionals who operate two or more types of treatments.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the first name and last name of the professionals who have done treatment with cost below average?\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.last_name FROM Professionals AS T1 JOIN Treatments AS T2 WHERE cost_of_treatment < ( SELECT avg(cost_of_treatment) FROM Treatments )", "db_id": "dog_kennels", "query": "SELECT DISTINCT T1.first_name , T1.last_name FROM Professionals AS T1 JOIN Treatments AS T2 WHERE cost_of_treatment < ( SELECT avg(cost_of_treatment) FROM Treatments )", "question": "What are the first name and last name of the professionals who have done treatment with cost below average?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals have operated a treatment that costs less than the average? Give me theor first names and last names.\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T1.last_name FROM Professionals AS T1 JOIN Treatments AS T2 WHERE cost_of_treatment < ( SELECT avg(cost_of_treatment) FROM Treatments )", "db_id": "dog_kennels", "query": "SELECT DISTINCT T1.first_name , T1.last_name FROM Professionals AS T1 JOIN Treatments AS T2 WHERE cost_of_treatment < ( SELECT avg(cost_of_treatment) FROM Treatments )", "question": "Which professionals have operated a treatment that costs less than the average? Give me theor first names and last names.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the date of each treatment, together with the first name of the professional who operated it.\n[SQL]:\n", "output": "SELECT T1.date_of_treatment , T2.first_name FROM Treatments AS T1 JOIN Professionals AS T2 ON T1.professional_id = T2.professional_id", "db_id": "dog_kennels", "query": "SELECT T1.date_of_treatment , T2.first_name FROM Treatments AS T1 JOIN Professionals AS T2 ON T1.professional_id = T2.professional_id", "question": "List the date of each treatment, together with the first name of the professional who operated it.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the date and the operating professional's first name of each treatment?\n[SQL]:\n", "output": "SELECT T1.date_of_treatment , T2.first_name FROM Treatments AS T1 JOIN Professionals AS T2 ON T1.professional_id = T2.professional_id", "db_id": "dog_kennels", "query": "SELECT T1.date_of_treatment , T2.first_name FROM Treatments AS T1 JOIN Professionals AS T2 ON T1.professional_id = T2.professional_id", "question": "What are the date and the operating professional's first name of each treatment?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the cost of each treatment and the corresponding treatment type description.\n[SQL]:\n", "output": "SELECT T1.cost_of_treatment , T2.treatment_type_description FROM Treatments AS T1 JOIN treatment_types AS T2 ON T1.treatment_type_code = T2.treatment_type_code", "db_id": "dog_kennels", "query": "SELECT T1.cost_of_treatment , T2.treatment_type_description FROM Treatments AS T1 JOIN treatment_types AS T2 ON T1.treatment_type_code = T2.treatment_type_code", "question": "List the cost of each treatment and the corresponding treatment type description.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the cost and treatment type description of each treatment?\n[SQL]:\n", "output": "SELECT T1.cost_of_treatment , T2.treatment_type_description FROM Treatments AS T1 JOIN treatment_types AS T2 ON T1.treatment_type_code = T2.treatment_type_code", "db_id": "dog_kennels", "query": "SELECT T1.cost_of_treatment , T2.treatment_type_description FROM Treatments AS T1 JOIN treatment_types AS T2 ON T1.treatment_type_code = T2.treatment_type_code", "question": "What are the cost and treatment type description of each treatment?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List each owner's first name, last name, and the size of his for her dog.\n[SQL]:\n", "output": "SELECT T1.first_name , T1.last_name , T2.size_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "db_id": "dog_kennels", "query": "SELECT T1.first_name , T1.last_name , T2.size_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "question": "List each owner's first name, last name, and the size of his for her dog.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are each owner's first name, last name, and the size of their dog?\n[SQL]:\n", "output": "SELECT T1.first_name , T1.last_name , T2.size_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "db_id": "dog_kennels", "query": "SELECT T1.first_name , T1.last_name , T2.size_code FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "question": "What are each owner's first name, last name, and the size of their dog?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List pairs of the owner's first name and the dogs's name.\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "db_id": "dog_kennels", "query": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "question": "List pairs of the owner's first name and the dogs's name.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are each owner's first name and their dogs's name?\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "db_id": "dog_kennels", "query": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id", "question": "What are each owner's first name and their dogs's name?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the names of the dogs of the rarest breed and the treatment dates of them.\n[SQL]:\n", "output": "SELECT T1.name , T2.date_of_treatment FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id WHERE T1.breed_code = ( SELECT breed_code FROM Dogs GROUP BY breed_code ORDER BY count(*) ASC LIMIT 1 )", "db_id": "dog_kennels", "query": "SELECT T1.name , T2.date_of_treatment FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id WHERE T1.breed_code = ( SELECT breed_code FROM Dogs GROUP BY breed_code ORDER BY count(*) ASC LIMIT 1 )", "question": "List the names of the dogs of the rarest breed and the treatment dates of them.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which dogs are of the rarest breed? Show their names and treatment dates.\n[SQL]:\n", "output": "SELECT T1.name , T2.date_of_treatment FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id WHERE T1.breed_code = ( SELECT breed_code FROM Dogs GROUP BY breed_code ORDER BY count(*) ASC LIMIT 1 )", "db_id": "dog_kennels", "query": "SELECT T1.name , T2.date_of_treatment FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id WHERE T1.breed_code = ( SELECT breed_code FROM Dogs GROUP BY breed_code ORDER BY count(*) ASC LIMIT 1 )", "question": "Which dogs are of the rarest breed? Show their names and treatment dates.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which dogs are owned by someone who lives in Virginia? List the owner's first name and the dog's name.\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T1.state = 'Virginia'", "db_id": "dog_kennels", "query": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T1.state = 'Virginia'", "question": "Which dogs are owned by someone who lives in Virginia? List the owner's first name and the dog's name.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the first names of owners living in Virginia and the names of dogs they own.\n[SQL]:\n", "output": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T1.state = 'Virginia'", "db_id": "dog_kennels", "query": "SELECT T1.first_name , T2.name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T1.state = 'Virginia'", "question": "Find the first names of owners living in Virginia and the names of dogs they own.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the arriving date and the departing date of the dogs who have gone through a treatment?\n[SQL]:\n", "output": "SELECT DISTINCT T1.date_arrived , T1.date_departed FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id", "db_id": "dog_kennels", "query": "SELECT DISTINCT T1.date_arrived , T1.date_departed FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id", "question": "What are the arriving date and the departing date of the dogs who have gone through a treatment?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the arriving date and the departing date of the dogs that received a treatment.\n[SQL]:\n", "output": "SELECT DISTINCT T1.date_arrived , T1.date_departed FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id", "db_id": "dog_kennels", "query": "SELECT DISTINCT T1.date_arrived , T1.date_departed FROM Dogs AS T1 JOIN Treatments AS T2 ON T1.dog_id = T2.dog_id", "question": "Find the arriving date and the departing date of the dogs that received a treatment.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the last name of the owner owning the youngest dog.\n[SQL]:\n", "output": "SELECT T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T2.age = ( SELECT max(age) FROM Dogs )", "db_id": "dog_kennels", "query": "SELECT T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T2.age = ( SELECT max(age) FROM Dogs )", "question": "List the last name of the owner owning the youngest dog.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Who owns the youngest dog? Give me his or her last name.\n[SQL]:\n", "output": "SELECT T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T2.age = ( SELECT max(age) FROM Dogs )", "db_id": "dog_kennels", "query": "SELECT T1.last_name FROM Owners AS T1 JOIN Dogs AS T2 ON T1.owner_id = T2.owner_id WHERE T2.age = ( SELECT max(age) FROM Dogs )", "question": "Who owns the youngest dog? Give me his or her last name.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the emails of the professionals who live in the state of Hawaii or the state of Wisconsin.\n[SQL]:\n", "output": "SELECT email_address FROM Professionals WHERE state = 'Hawaii' OR state = 'Wisconsin'", "db_id": "dog_kennels", "query": "SELECT email_address FROM Professionals WHERE state = 'Hawaii' OR state = 'Wisconsin'", "question": "List the emails of the professionals who live in the state of Hawaii or the state of Wisconsin.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the emails of the professionals living in either the state of Hawaii or the state of Wisconsin?\n[SQL]:\n", "output": "SELECT email_address FROM Professionals WHERE state = 'Hawaii' OR state = 'Wisconsin'", "db_id": "dog_kennels", "query": "SELECT email_address FROM Professionals WHERE state = 'Hawaii' OR state = 'Wisconsin'", "question": "What are the emails of the professionals living in either the state of Hawaii or the state of Wisconsin?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the arriving date and the departing date of all the dogs?\n[SQL]:\n", "output": "SELECT date_arrived , date_departed FROM Dogs", "db_id": "dog_kennels", "query": "SELECT date_arrived , date_departed FROM Dogs", "question": "What are the arriving date and the departing date of all the dogs?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the arrival date and the departure date for all the dogs.\n[SQL]:\n", "output": "SELECT date_arrived , date_departed FROM Dogs", "db_id": "dog_kennels", "query": "SELECT date_arrived , date_departed FROM Dogs", "question": "List the arrival date and the departure date for all the dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many dogs went through any treatments?\n[SQL]:\n", "output": "SELECT count(DISTINCT dog_id) FROM Treatments", "db_id": "dog_kennels", "query": "SELECT count(DISTINCT dog_id) FROM Treatments", "question": "How many dogs went through any treatments?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Count the number of dogs that went through a treatment.\n[SQL]:\n", "output": "SELECT count(DISTINCT dog_id) FROM Treatments", "db_id": "dog_kennels", "query": "SELECT count(DISTINCT dog_id) FROM Treatments", "question": "Count the number of dogs that went through a treatment.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many professionals have performed any treatment to dogs?\n[SQL]:\n", "output": "SELECT count(DISTINCT professional_id) FROM Treatments", "db_id": "dog_kennels", "query": "SELECT count(DISTINCT professional_id) FROM Treatments", "question": "How many professionals have performed any treatment to dogs?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the number of professionals who have ever treated dogs.\n[SQL]:\n", "output": "SELECT count(DISTINCT professional_id) FROM Treatments", "db_id": "dog_kennels", "query": "SELECT count(DISTINCT professional_id) FROM Treatments", "question": "Find the number of professionals who have ever treated dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which professionals live in a city containing the substring 'West'? List his or her role, street, city and state.\n[SQL]:\n", "output": "SELECT role_code , street , city , state FROM professionals WHERE city LIKE '%West%'", "db_id": "dog_kennels", "query": "SELECT role_code , street , city , state FROM professionals WHERE city LIKE '%West%'", "question": "Which professionals live in a city containing the substring 'West'? List his or her role, street, city and state.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the role, street, city and state of the professionals living in a city that contains the substring 'West'.\n[SQL]:\n", "output": "SELECT role_code , street , city , state FROM professionals WHERE city LIKE '%West%'", "db_id": "dog_kennels", "query": "SELECT role_code , street , city , state FROM professionals WHERE city LIKE '%West%'", "question": "Find the role, street, city and state of the professionals living in a city that contains the substring 'West'.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Which owners live in the state whose name contains the substring 'North'? List his first name, last name and email.\n[SQL]:\n", "output": "SELECT first_name , last_name , email_address FROM Owners WHERE state LIKE '%North%'", "db_id": "dog_kennels", "query": "SELECT first_name , last_name , email_address FROM Owners WHERE state LIKE '%North%'", "question": "Which owners live in the state whose name contains the substring 'North'? List his first name, last name and email.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Return the first name, last name and email of the owners living in a state whose name contains the substring 'North'.\n[SQL]:\n", "output": "SELECT first_name , last_name , email_address FROM Owners WHERE state LIKE '%North%'", "db_id": "dog_kennels", "query": "SELECT first_name , last_name , email_address FROM Owners WHERE state LIKE '%North%'", "question": "Return the first name, last name and email of the owners living in a state whose name contains the substring 'North'.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many dogs have an age below the average?\n[SQL]:\n", "output": "SELECT count(*) FROM Dogs WHERE age < ( SELECT avg(age) FROM Dogs )", "db_id": "dog_kennels", "query": "SELECT count(*) FROM Dogs WHERE age < ( SELECT avg(age) FROM Dogs )", "question": "How many dogs have an age below the average?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Count the number of dogs of an age below the average.\n[SQL]:\n", "output": "SELECT count(*) FROM Dogs WHERE age < ( SELECT avg(age) FROM Dogs )", "db_id": "dog_kennels", "query": "SELECT count(*) FROM Dogs WHERE age < ( SELECT avg(age) FROM Dogs )", "question": "Count the number of dogs of an age below the average.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How much does the most recent treatment cost?\n[SQL]:\n", "output": "SELECT cost_of_treatment FROM Treatments ORDER BY date_of_treatment DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT cost_of_treatment FROM Treatments ORDER BY date_of_treatment DESC LIMIT 1", "question": "How much does the most recent treatment cost?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Show me the cost of the most recently performed treatment.\n[SQL]:\n", "output": "SELECT cost_of_treatment FROM Treatments ORDER BY date_of_treatment DESC LIMIT 1", "db_id": "dog_kennels", "query": "SELECT cost_of_treatment FROM Treatments ORDER BY date_of_treatment DESC LIMIT 1", "question": "Show me the cost of the most recently performed treatment.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many dogs have not gone through any treatment?\n[SQL]:\n", "output": "SELECT count(*) FROM Dogs WHERE dog_id NOT IN ( SELECT dog_id FROM Treatments )", "db_id": "dog_kennels", "query": "SELECT count(*) FROM Dogs WHERE dog_id NOT IN ( SELECT dog_id FROM Treatments )", "question": "How many dogs have not gone through any treatment?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Tell me the number of dogs that have not received any treatment .\n[SQL]:\n", "output": "select count(*) from dogs where dog_id not in ( select dog_id from treatments )", "db_id": "dog_kennels", "query": "select count(*) from dogs where dog_id not in ( select dog_id from treatments )", "question": "Tell me the number of dogs that have not received any treatment .", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many owners temporarily do not have any dogs?\n[SQL]:\n", "output": "SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )", "db_id": "dog_kennels", "query": "SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )", "question": "How many owners temporarily do not have any dogs?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the number of owners who do not own any dogs at this moment.\n[SQL]:\n", "output": "SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )", "db_id": "dog_kennels", "query": "SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )", "question": "Find the number of owners who do not own any dogs at this moment.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How many professionals did not operate any treatment on dogs?\n[SQL]:\n", "output": "SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )", "db_id": "dog_kennels", "query": "SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )", "question": "How many professionals did not operate any treatment on dogs?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the number of professionals who have not treated any dogs.\n[SQL]:\n", "output": "SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )", "db_id": "dog_kennels", "query": "SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )", "question": "Find the number of professionals who have not treated any dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the dog name, age and weight of the dogs who have been abandoned? 1 stands for yes, and 0 stands for no.\n[SQL]:\n", "output": "SELECT name , age , weight FROM Dogs WHERE abandoned_yn = 1", "db_id": "dog_kennels", "query": "SELECT name , age , weight FROM Dogs WHERE abandoned_yn = 1", "question": "List the dog name, age and weight of the dogs who have been abandoned? 1 stands for yes, and 0 stands for no.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the dog name, age and weight of the dogs that were abandoned? Note that 1 stands for yes, and 0 stands for no in the tables.\n[SQL]:\n", "output": "SELECT name , age , weight FROM Dogs WHERE abandoned_yn = 1", "db_id": "dog_kennels", "query": "SELECT name , age , weight FROM Dogs WHERE abandoned_yn = 1", "question": "What are the dog name, age and weight of the dogs that were abandoned? Note that 1 stands for yes, and 0 stands for no in the tables.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the average age of all the dogs?\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs", "db_id": "dog_kennels", "query": "SELECT avg(age) FROM Dogs", "question": "What is the average age of all the dogs?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Compute the average age of all the dogs.\n[SQL]:\n", "output": "SELECT avg(age) FROM Dogs", "db_id": "dog_kennels", "query": "SELECT avg(age) FROM Dogs", "question": "Compute the average age of all the dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the age of the oldest dog?\n[SQL]:\n", "output": "SELECT max(age) FROM Dogs", "db_id": "dog_kennels", "query": "SELECT max(age) FROM Dogs", "question": "What is the age of the oldest dog?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Tell me the age of the oldest dog.\n[SQL]:\n", "output": "SELECT max(age) FROM Dogs", "db_id": "dog_kennels", "query": "SELECT max(age) FROM Dogs", "question": "Tell me the age of the oldest dog.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How much does each charge type costs? List both charge type and amount.\n[SQL]:\n", "output": "SELECT charge_type , charge_amount FROM Charges", "db_id": "dog_kennels", "query": "SELECT charge_type , charge_amount FROM Charges", "question": "How much does each charge type costs? List both charge type and amount.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List each charge type and its amount.\n[SQL]:\n", "output": "SELECT charge_type , charge_amount FROM Charges", "db_id": "dog_kennels", "query": "SELECT charge_type , charge_amount FROM Charges", "question": "List each charge type and its amount.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:How much does the most expensive charge type costs?\n[SQL]:\n", "output": "SELECT max(charge_amount) FROM Charges", "db_id": "dog_kennels", "query": "SELECT max(charge_amount) FROM Charges", "question": "How much does the most expensive charge type costs?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What is the charge amount of the most expensive charge type?\n[SQL]:\n", "output": "SELECT max(charge_amount) FROM Charges", "db_id": "dog_kennels", "query": "SELECT max(charge_amount) FROM Charges", "question": "What is the charge amount of the most expensive charge type?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the email, cell phone and home phone of all the professionals.\n[SQL]:\n", "output": "SELECT email_address , cell_number , home_phone FROM professionals", "db_id": "dog_kennels", "query": "SELECT email_address , cell_number , home_phone FROM professionals", "question": "List the email, cell phone and home phone of all the professionals.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are the email, cell phone and home phone of each professional?\n[SQL]:\n", "output": "SELECT email_address , cell_number , home_phone FROM professionals", "db_id": "dog_kennels", "query": "SELECT email_address , cell_number , home_phone FROM professionals", "question": "What are the email, cell phone and home phone of each professional?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are all the possible breed type and size type combinations?\n[SQL]:\n", "output": "SELECT DISTINCT breed_code , size_code FROM dogs", "db_id": "dog_kennels", "query": "SELECT DISTINCT breed_code , size_code FROM dogs", "question": "What are all the possible breed type and size type combinations?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:Find the distinct breed type and size type combinations for dogs.\n[SQL]:\n", "output": "SELECT DISTINCT breed_code , size_code FROM dogs", "db_id": "dog_kennels", "query": "SELECT DISTINCT breed_code , size_code FROM dogs", "question": "Find the distinct breed type and size type combinations for dogs.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:List the first name of all the professionals along with the description of the treatment they have done.\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T3.treatment_type_description FROM professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id JOIN Treatment_types AS T3 ON T2.treatment_type_code = T3.treatment_type_code", "db_id": "dog_kennels", "query": "SELECT DISTINCT T1.first_name , T3.treatment_type_description FROM professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id JOIN Treatment_types AS T3 ON T2.treatment_type_code = T3.treatment_type_code", "question": "List the first name of all the professionals along with the description of the treatment they have done.", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);\"\n[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id\"\n[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code\"\nAnswer the following question with a SQL Statement:What are each professional's first name and description of the treatment they have performed?\n[SQL]:\n", "output": "SELECT DISTINCT T1.first_name , T3.treatment_type_description FROM professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id JOIN Treatment_types AS T3 ON T2.treatment_type_code = T3.treatment_type_code", "db_id": "dog_kennels", "query": "SELECT DISTINCT T1.first_name , T3.treatment_type_description FROM professionals AS T1 JOIN Treatments AS T2 ON T1.professional_id = T2.professional_id JOIN Treatment_types AS T3 ON T2.treatment_type_code = T3.treatment_type_code", "question": "What are each professional's first name and description of the treatment they have performed?", "schema": "[Schema (values) (types)]: | dog_kennels | Breeds : breed_code (text) , breed_name (text) | Charges : charge_id (text) , charge_type (text) , charge_amount (text) | Sizes : size_code (text) , size_description (text) | Treatment_Types : treatment_type_code (text) , treatment_type_description (text) | Owners : owner_id (text) , first_name (text) , last_name (text) , street (number) , city (text) , state (number) , zip_code (text) , email_address (text) , home_phone (text) , cell_number (text) | Dogs : dog_id (text) , owner_id (text) , abandoned_yn (text) , breed_code (number) , size_code (text) , name (number) , age (text) , date_of_birth (text) , gender (text) , weight (text) , date_arrived (number) , date_adopted (text) , date_departed (text) | Professionals : professional_id (text) , role_code (text) , first_name (text) , street (number) , city (text) , state (number) , zip_code (text) , last_name (text) , email_address (text) , home_phone (text) , cell_number (number) | Treatments : treatment_id (text) , dog_id (text) , professional_id (text) , treatment_type_code (number) , date_of_treatment (text) , cost_of_treatment (number);", "primary_keys": "[Primary Keys]: breeds : breed_code, charges : charge_id, sizes : size_code, treatment_types : treatment_type_code, owners : owner_id, dogs : dog_id, professionals : professional_id, treatments : treatment_id", "foreign_keys": "[Foreign Keys]: dogs : owner_id = owners : owner_id | dogs : owner_id = owners : owner_id | dogs : size_code = sizes : size_code | dogs : breed_code = breeds : breed_code | treatments : dog_id = dogs : dog_id | treatments : professional_id = professionals : professional_id | treatments : treatment_type_code = treatment_types : treatment_type_code"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:How many singers are there?\n[SQL]:\n", "output": "SELECT count(*) FROM singer", "db_id": "singer", "query": "SELECT count(*) FROM singer", "question": "How many singers are there?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the count of singers?\n[SQL]:\n", "output": "SELECT count(*) FROM singer", "db_id": "singer", "query": "SELECT count(*) FROM singer", "question": "What is the count of singers?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:List the name of singers in ascending order of net worth.\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC", "db_id": "singer", "query": "SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC", "question": "List the name of singers in ascending order of net worth.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of singers ordered by ascending net worth?\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC", "db_id": "singer", "query": "SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC", "question": "What are the names of singers ordered by ascending net worth?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the birth year and citizenship of singers?\n[SQL]:\n", "output": "SELECT Birth_Year , Citizenship FROM singer", "db_id": "singer", "query": "SELECT Birth_Year , Citizenship FROM singer", "question": "What are the birth year and citizenship of singers?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the birth years and citizenships of the singers?\n[SQL]:\n", "output": "SELECT Birth_Year , Citizenship FROM singer", "db_id": "singer", "query": "SELECT Birth_Year , Citizenship FROM singer", "question": "What are the birth years and citizenships of the singers?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:List the name of singers whose citizenship is not \"France\".\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Citizenship != \"France\"", "db_id": "singer", "query": "SELECT Name FROM singer WHERE Citizenship != \"France\"", "question": "List the name of singers whose citizenship is not \"France\".", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers who are not French citizens?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Citizenship != \"France\"", "db_id": "singer", "query": "SELECT Name FROM singer WHERE Citizenship != \"France\"", "question": "What are the names of the singers who are not French citizens?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the name of singers whose birth year is either 1948 or 1949?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Birth_Year = 1948 OR Birth_Year = 1949", "db_id": "singer", "query": "SELECT Name FROM singer WHERE Birth_Year = 1948 OR Birth_Year = 1949", "question": "Show the name of singers whose birth year is either 1948 or 1949?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers whose birth years are either 1948 or 1949?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Birth_Year = 1948 OR Birth_Year = 1949", "db_id": "singer", "query": "SELECT Name FROM singer WHERE Birth_Year = 1948 OR Birth_Year = 1949", "question": "What are the names of the singers whose birth years are either 1948 or 1949?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the name of the singer with the largest net worth?\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1", "db_id": "singer", "query": "SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1", "question": "What is the name of the singer with the largest net worth?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the name of the singer who is worth the most?\n[SQL]:\n", "output": "SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1", "db_id": "singer", "query": "SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1", "question": "What is the name of the singer who is worth the most?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show different citizenship of singers and the number of singers of each citizenship.\n[SQL]:\n", "output": "SELECT Citizenship , COUNT(*) FROM singer GROUP BY Citizenship", "db_id": "singer", "query": "SELECT Citizenship , COUNT(*) FROM singer GROUP BY Citizenship", "question": "Show different citizenship of singers and the number of singers of each citizenship.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:For each citizenship, how many singers are from that country?\n[SQL]:\n", "output": "SELECT Citizenship , COUNT(*) FROM singer GROUP BY Citizenship", "db_id": "singer", "query": "SELECT Citizenship , COUNT(*) FROM singer GROUP BY Citizenship", "question": "For each citizenship, how many singers are from that country?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Please show the most common citizenship of singers.\n[SQL]:\n", "output": "SELECT Citizenship FROM singer GROUP BY Citizenship ORDER BY COUNT(*) DESC LIMIT 1", "db_id": "singer", "query": "SELECT Citizenship FROM singer GROUP BY Citizenship ORDER BY COUNT(*) DESC LIMIT 1", "question": "Please show the most common citizenship of singers.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the most common singer citizenship ?\n[SQL]:\n", "output": "select citizenship from singer group by citizenship order by count(*) desc limit 1", "db_id": "singer", "query": "select citizenship from singer group by citizenship order by count(*) desc limit 1", "question": "What is the most common singer citizenship ?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show different citizenships and the maximum net worth of singers of each citizenship.\n[SQL]:\n", "output": "SELECT Citizenship , max(Net_Worth_Millions) FROM singer GROUP BY Citizenship", "db_id": "singer", "query": "SELECT Citizenship , max(Net_Worth_Millions) FROM singer GROUP BY Citizenship", "question": "Show different citizenships and the maximum net worth of singers of each citizenship.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:For each citizenship, what is the maximum net worth?\n[SQL]:\n", "output": "SELECT Citizenship , max(Net_Worth_Millions) FROM singer GROUP BY Citizenship", "db_id": "singer", "query": "SELECT Citizenship , max(Net_Worth_Millions) FROM singer GROUP BY Citizenship", "question": "For each citizenship, what is the maximum net worth?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show titles of songs and names of singers.\n[SQL]:\n", "output": "SELECT T2.Title , T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID", "db_id": "singer", "query": "SELECT T2.Title , T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID", "question": "Show titles of songs and names of singers.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the song titles and singer names?\n[SQL]:\n", "output": "SELECT T2.Title , T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID", "db_id": "singer", "query": "SELECT T2.Title , T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID", "question": "What are the song titles and singer names?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show distinct names of singers that have songs with sales more than 300000.\n[SQL]:\n", "output": "SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID WHERE T2.Sales > 300000", "db_id": "singer", "query": "SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID WHERE T2.Sales > 300000", "question": "Show distinct names of singers that have songs with sales more than 300000.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:what are the different names of the singers that have sales more than 300000?\n[SQL]:\n", "output": "SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID WHERE T2.Sales > 300000", "db_id": "singer", "query": "SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID WHERE T2.Sales > 300000", "question": "what are the different names of the singers that have sales more than 300000?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the names of singers that have more than one song.\n[SQL]:\n", "output": "SELECT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name HAVING COUNT(*) > 1", "db_id": "singer", "query": "SELECT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name HAVING COUNT(*) > 1", "question": "Show the names of singers that have more than one song.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the names of the singers that have more than one songs?\n[SQL]:\n", "output": "SELECT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name HAVING COUNT(*) > 1", "db_id": "singer", "query": "SELECT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name HAVING COUNT(*) > 1", "question": "What are the names of the singers that have more than one songs?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the names of singers and the total sales of their songs.\n[SQL]:\n", "output": "SELECT T1.Name , sum(T2.Sales) FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name", "db_id": "singer", "query": "SELECT T1.Name , sum(T2.Sales) FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name", "question": "Show the names of singers and the total sales of their songs.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:For each singer name, what is the total sales for their songs?\n[SQL]:\n", "output": "SELECT T1.Name , sum(T2.Sales) FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name", "db_id": "singer", "query": "SELECT T1.Name , sum(T2.Sales) FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID = T2.Singer_ID GROUP BY T1.Name", "question": "For each singer name, what is the total sales for their songs?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:List the name of singers that do not have any song.\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)", "db_id": "singer", "query": "SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)", "question": "List the name of singers that do not have any song.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What is the sname of every sing that does not have any song?\n[SQL]:\n", "output": "SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)", "db_id": "singer", "query": "SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)", "question": "What is the sname of every sing that does not have any song?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:Show the citizenship shared by singers with birth year before 1945 and after 1955.\n[SQL]:\n", "output": "SELECT Citizenship FROM singer WHERE Birth_Year < 1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year > 1955", "db_id": "singer", "query": "SELECT Citizenship FROM singer WHERE Birth_Year < 1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year > 1955", "question": "Show the citizenship shared by singers with birth year before 1945 and after 1955.", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);\"\n[Primary Keys]: singer : singer_id, song : song_id\"\n[Foreign Keys]: song : singer_id = singer : singer_id\"\nAnswer the following question with a SQL Statement:What are the citizenships that are shared by singers with a birth year before 1945 and after 1955?\n[SQL]:\n", "output": "SELECT Citizenship FROM singer WHERE Birth_Year < 1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year > 1955", "db_id": "singer", "query": "SELECT Citizenship FROM singer WHERE Birth_Year < 1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year > 1955", "question": "What are the citizenships that are shared by singers with a birth year before 1945 and after 1955?", "schema": "[Schema (values) (types)]: | singer | singer : singer_id (text) , name (number) , birth_year (text) , net_worth_millions (number) , citizenship (number) | song : song_id (text) , title (number) , singer_id (text) , sales (number) , highest_position (number);", "primary_keys": "[Primary Keys]: singer : singer_id, song : song_id", "foreign_keys": "[Foreign Keys]: song : singer_id = singer : singer_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:How many available features are there in total?\n[SQL]:\n", "output": "SELECT count(*) FROM Other_Available_Features", "db_id": "real_estate_properties", "query": "SELECT count(*) FROM Other_Available_Features", "question": "How many available features are there in total?", "schema": "[Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);", "primary_keys": "[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id", "foreign_keys": "[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:What is the feature type name of feature AirCon?\n[SQL]:\n", "output": "SELECT T2.feature_type_name FROM Other_Available_Features AS T1 JOIN Ref_Feature_Types AS T2 ON T1.feature_type_code = T2.feature_type_code WHERE T1.feature_name = \"AirCon\"", "db_id": "real_estate_properties", "query": "SELECT T2.feature_type_name FROM Other_Available_Features AS T1 JOIN Ref_Feature_Types AS T2 ON T1.feature_type_code = T2.feature_type_code WHERE T1.feature_name = \"AirCon\"", "question": "What is the feature type name of feature AirCon?", "schema": "[Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);", "primary_keys": "[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id", "foreign_keys": "[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:Show the property type descriptions of properties belonging to that code.\n[SQL]:\n", "output": "SELECT T2.property_type_description FROM Properties AS T1 JOIN Ref_Property_Types AS T2 ON T1.property_type_code = T2.property_type_code GROUP BY T1.property_type_code", "db_id": "real_estate_properties", "query": "SELECT T2.property_type_description FROM Properties AS T1 JOIN Ref_Property_Types AS T2 ON T1.property_type_code = T2.property_type_code GROUP BY T1.property_type_code", "question": "Show the property type descriptions of properties belonging to that code.", "schema": "[Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);", "primary_keys": "[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id", "foreign_keys": "[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id"}
+{"input": "This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.\n [Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);\"\n[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id\"\n[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id\"\nAnswer the following question with a SQL Statement:What are the names of properties that are either houses or apartments with more than 1 room?\n[SQL]:\n", "output": "SELECT property_name FROM Properties WHERE property_type_code = \"House\" UNION SELECT property_name FROM Properties WHERE property_type_code = \"Apartment\" AND room_count > 1", "db_id": "real_estate_properties", "query": "SELECT property_name FROM Properties WHERE property_type_code = \"House\" UNION SELECT property_name FROM Properties WHERE property_type_code = \"Apartment\" AND room_count > 1", "question": "What are the names of properties that are either houses or apartments with more than 1 room?", "schema": "[Schema (values) (types)]: | real_estate_properties | Ref_Feature_Types : feature_type_code (text) , feature_type_name (text) | Ref_Property_Types : property_type_code (text) , property_type_description (text) | Other_Available_Features : feature_id (text) , feature_type_code (text) , feature_name (text) , feature_description (text) | Properties : property_id (text) , property_type_code (text) , date_on_market (text) , date_sold (text) , property_name (text) , property_address (number) , room_count (text) , vendor_requested_price (text) , buyer_offered_price (text) , agreed_selling_price (number) , apt_feature_1 (text) , apt_feature_2 (time) , apt_feature_3 (time) , fld_feature_1 (text) , fld_feature_2 (text) , fld_feature_3 (number) , hse_feature_1 (number) , hse_feature_2 (number) , hse_feature_3 (number) , oth_feature_1 (text) , oth_feature_2 (text) , oth_feature_3 (text) , shp_feature_1 (text) , shp_feature_2 (text) , shp_feature_3 (text) , other_property_details (text) | Other_Property_Features : property_id (text) , feature_id (text) , property_feature_description (text);", "primary_keys": "[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id", "foreign_keys": "[Foreign Keys]: other_available_features : feature_type_code = ref_feature_types : feature_type_code | properties : property_type_code = ref_property_types : property_type_code | other_property_features : property_id = properties : property_id | other_property_features : feature_id = other_available_features : feature_id"}
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