Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many dogs have not gone through any treatment?</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM Dogs WHERE dog_id NOT IN ( SELECT dog_id FROM Treatments )</SQL_QUERY>

Question: SELECT count(*) FROM Dogs WHERE dog_id NOT IN ( SELECT dog_id FROM Treatments )

Question: How many dogs have not gone through any treatment?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>Tell me the number of dogs that have not received any treatment .</question>
[SQL]:

Output: <SQL_QUERY>select count(*) from dogs where dog_id not in ( select dog_id from treatments )</SQL_QUERY>

Question: 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 .


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many owners temporarily do not have any dogs?</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )</SQL_QUERY>

Question: SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )

Question: How many owners temporarily do not have any 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.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of owners who do not own any dogs at this moment.</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM Owners WHERE owner_id NOT IN ( SELECT owner_id FROM Dogs )</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many professionals did not operate any treatment on dogs?</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of professionals who have not treated any dogs.</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM Professionals WHERE professional_id NOT IN ( SELECT professional_id FROM Treatments )</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the dog name, age and weight of the dogs who have been abandoned? 1 stands for yes, and 0 stands for no.</question>
[SQL]:

Output: <SQL_QUERY>SELECT name ,  age ,  weight FROM Dogs WHERE abandoned_yn  =  1</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<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.</question>
[SQL]:

Output: <SQL_QUERY>SELECT name ,  age ,  weight FROM Dogs WHERE abandoned_yn  =  1</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average age of all the dogs?</question>
[SQL]:

Output: <SQL_QUERY>SELECT avg(age) FROM Dogs</SQL_QUERY>

Question: SELECT avg(age) FROM Dogs

Question: What is the average age of all the 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.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>Compute the average age of all the dogs.</question>
[SQL]:

Output: <SQL_QUERY>SELECT avg(age) FROM Dogs</SQL_QUERY>

Question: SELECT avg(age) FROM Dogs

Question: Compute the average age of all the 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.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the age of the oldest dog?</question>
[SQL]:

Output: <SQL_QUERY>SELECT max(age) FROM Dogs</SQL_QUERY>

Question: SELECT max(age) FROM Dogs

Question: What is the age of the oldest 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.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>Tell me the age of the oldest dog.</question>
[SQL]:

Output: <SQL_QUERY>SELECT max(age) FROM Dogs</SQL_QUERY>

Question: SELECT max(age) FROM Dogs

Question: Tell me the age of the oldest 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.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>How much does each charge type costs? List both charge type and amount.</question>
[SQL]:

Output: <SQL_QUERY>SELECT charge_type ,  charge_amount FROM Charges</SQL_QUERY>

Question: SELECT charge_type ,  charge_amount FROM Charges

Question: How much does each charge type costs? List both charge type and amount.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>List each charge type and its amount.</question>
[SQL]:

Output: <SQL_QUERY>SELECT charge_type ,  charge_amount FROM Charges</SQL_QUERY>

Question: SELECT charge_type ,  charge_amount FROM Charges

Question: List each charge type and its amount.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>How much does the most expensive charge type costs?</question>
[SQL]:

Output: <SQL_QUERY>SELECT max(charge_amount) FROM Charges</SQL_QUERY>

Question: SELECT max(charge_amount) FROM Charges

Question: How much does the most expensive charge type costs?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the charge amount of the most expensive charge type?</question>
[SQL]:

Output: <SQL_QUERY>SELECT max(charge_amount) FROM Charges</SQL_QUERY>

Question: SELECT max(charge_amount) FROM Charges

Question: What is the charge amount of the most expensive charge type?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the email, cell phone and home phone of all the professionals.</question>
[SQL]:

Output: <SQL_QUERY>SELECT email_address ,  cell_number ,  home_phone FROM professionals</SQL_QUERY>

Question: SELECT email_address ,  cell_number ,  home_phone FROM professionals

Question: List the email, cell phone and home phone of all the 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.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the email, cell phone and home phone of each professional?</question>
[SQL]:

Output: <SQL_QUERY>SELECT email_address ,  cell_number ,  home_phone FROM professionals</SQL_QUERY>

Question: SELECT email_address ,  cell_number ,  home_phone FROM professionals

Question: What are the email, cell phone and home phone of each professional?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are all the possible breed type and size type combinations?</question>
[SQL]:

Output: <SQL_QUERY>SELECT DISTINCT breed_code ,  size_code FROM dogs</SQL_QUERY>

Question: SELECT DISTINCT breed_code ,  size_code FROM dogs

Question: What are all the possible breed type and size type combinations?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct breed type and size type combinations for dogs.</question>
[SQL]:

Output: <SQL_QUERY>SELECT DISTINCT breed_code ,  size_code FROM dogs</SQL_QUERY>

Question: SELECT DISTINCT breed_code ,  size_code FROM dogs

Question: Find the distinct breed type and size type combinations for 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.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the first name of all the professionals along with the description of the treatment they have done.</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<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</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are each professional's first name and description of the treatment they have performed?</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many singers are there?</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM singer</SQL_QUERY>

Question: SELECT count(*) FROM singer

Question: How many singers are there?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the count of singers?</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM singer</SQL_QUERY>

Question: SELECT count(*) FROM singer

Question: What is the count of singers?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of singers in ascending order of net worth.</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC</SQL_QUERY>

Question: SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC

Question: List the name of singers in ascending order of net worth.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of singers ordered by ascending net worth?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC</SQL_QUERY>

Question: SELECT Name FROM singer ORDER BY Net_Worth_Millions ASC

Question: What are the names of singers ordered by ascending net worth?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the birth year and citizenship of singers?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Birth_Year ,  Citizenship FROM singer</SQL_QUERY>

Question: SELECT Birth_Year ,  Citizenship FROM singer

Question: What are the birth year and citizenship of singers?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the birth years and citizenships of the singers?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Birth_Year ,  Citizenship FROM singer</SQL_QUERY>

Question: SELECT Birth_Year ,  Citizenship FROM singer

Question: What are the birth years and citizenships of the singers?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of singers whose citizenship is not "France".</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer WHERE Citizenship != "France"</SQL_QUERY>

Question: SELECT Name FROM singer WHERE Citizenship != "France"

Question: List the name of singers whose citizenship is not "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.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the singers who are not French citizens?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer WHERE Citizenship != "France"</SQL_QUERY>

Question: SELECT Name FROM singer WHERE Citizenship != "France"

Question: What are the names of the singers who are not French citizens?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of singers whose birth year is either 1948 or 1949?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer WHERE Birth_Year  =  1948 OR Birth_Year  =  1949</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the singers whose birth years are either 1948 or 1949?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer WHERE Birth_Year  =  1948 OR Birth_Year  =  1949</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the singer with the largest net worth?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the singer who is worth the most?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer ORDER BY Net_Worth_Millions DESC LIMIT 1</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show different citizenship of singers and the number of singers of each citizenship.</question>
[SQL]:

Output: <SQL_QUERY>SELECT Citizenship ,  COUNT(*) FROM singer GROUP BY Citizenship</SQL_QUERY>

Question: SELECT Citizenship ,  COUNT(*) FROM singer GROUP BY Citizenship

Question: Show different citizenship of singers and the number of singers of each 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.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each citizenship, how many singers are from that country?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Citizenship ,  COUNT(*) FROM singer GROUP BY Citizenship</SQL_QUERY>

Question: SELECT Citizenship ,  COUNT(*) FROM singer GROUP BY Citizenship

Question: For each citizenship, how many singers are from that 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.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show the most common citizenship of singers.</question>
[SQL]:

Output: <SQL_QUERY>SELECT Citizenship FROM singer GROUP BY Citizenship ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY>

Question: SELECT Citizenship FROM singer GROUP BY Citizenship ORDER BY COUNT(*) DESC LIMIT 1

Question: Please show the most common citizenship of singers.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the most common singer citizenship ?</question>
[SQL]:

Output: <SQL_QUERY>select citizenship from singer group by citizenship order by count(*) desc limit 1</SQL_QUERY>

Question: select citizenship from singer group by citizenship order by count(*) desc limit 1

Question: What is the most common singer 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.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show different citizenships and the maximum net worth of singers of each citizenship.</question>
[SQL]:

Output: <SQL_QUERY>SELECT Citizenship ,  max(Net_Worth_Millions) FROM singer GROUP BY Citizenship</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each citizenship, what is the maximum net worth?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Citizenship ,  max(Net_Worth_Millions) FROM singer GROUP BY Citizenship</SQL_QUERY>

Question: SELECT Citizenship ,  max(Net_Worth_Millions) FROM singer GROUP BY Citizenship

Question: For each citizenship, what is the maximum net worth?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show titles of songs and names of singers.</question>
[SQL]:

Output: <SQL_QUERY>SELECT T2.Title ,  T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID  =  T2.Singer_ID</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the song titles and singer names?</question>
[SQL]:

Output: <SQL_QUERY>SELECT T2.Title ,  T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID  =  T2.Singer_ID</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show distinct names of singers that have songs with sales more than 300000.</question>
[SQL]:

Output: <SQL_QUERY>SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID  =  T2.Singer_ID WHERE T2.Sales  >  300000</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>what are the different names of the singers that have sales more than 300000?</question>
[SQL]:

Output: <SQL_QUERY>SELECT DISTINCT T1.Name FROM singer AS T1 JOIN song AS T2 ON T1.Singer_ID  =  T2.Singer_ID WHERE T2.Sales  >  300000</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of singers that have more than one song.</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the singers that have more than one songs?</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of singers and the total sales of their songs.</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each singer name, what is the total sales for their songs?</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of singers that do not have any song.</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the sname of every sing that does not have any song?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Name FROM singer WHERE Singer_ID NOT IN (SELECT Singer_ID FROM song)</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the citizenship shared by singers with birth year before 1945 and after 1955.</question>
[SQL]:

Output: <SQL_QUERY>SELECT Citizenship FROM singer WHERE Birth_Year  <  1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year  >  1955</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: singer : singer_id, song : song_id</primary_keys>"
<foreign_keys>[Foreign Keys]: song : singer_id = singer : singer_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the citizenships that are shared by singers with a birth year before 1945 and after 1955?</question>
[SQL]:

Output: <SQL_QUERY>SELECT Citizenship FROM singer WHERE Birth_Year  <  1945 INTERSECT SELECT Citizenship FROM singer WHERE Birth_Year  >  1955</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many available features are there in total?</question>
[SQL]:

Output: <SQL_QUERY>SELECT count(*) FROM Other_Available_Features</SQL_QUERY>

Question: SELECT count(*) FROM Other_Available_Features

Question: How many available features are there in total?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the feature type name of feature AirCon?</question>
[SQL]:

Output: <SQL_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"</SQL_QUERY>

Question: 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?


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the property type descriptions of properties belonging to that code.</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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.


Input:
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
 <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);</schema>"
<primary_keys>[Primary Keys]: ref_feature_types : feature_type_code, ref_property_types : property_type_code, other_available_features : feature_id, properties : property_id</primary_keys>"
<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</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of properties that are either houses or apartments with more than 1 room?</question>
[SQL]:

Output: <SQL_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</SQL_QUERY>

Question: 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?