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[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\tinvoice_date DATETIME, \n\tinvoice_details VARCHAR(255), \n\tPRIMARY KEY (invoice_number)\n)\n/*\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 1987-11-15 15:41:40, 1998-07-30 15:39:12, 1974-07-27 16:18:49\ninvoice_details : doloremque, eveniet, earum\n*/\n\n \nCREATE TABLE \"Office_locations\" (\n\tbuilding_id INTEGER, \n\tcompany_id INTEGER, \n\tmove_in_year INTEGER, \n\tPRIMARY KEY (building_id, company_id), \n\tFOREIGN KEY(building_id) REFERENCES buildings (id), \n\tFOREIGN KEY(company_id) REFERENCES \"Companies\" (id)\n)\n/*\nColumns in Office_locations and 3 examples in each column for high cardinality columns :\nbuilding_id : 1, 11, 2\nmove_in_year : 2023, 2020, 2022\n*/\n/*\nColumns in Office_locations and all categories for low cardinality columns :\ncompany_id : 1, 11, 2, 5, 19, 7, 4, 3, 10, 9\n*/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/*\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n*/\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE submission (\n\t\"Submission_ID\" INTEGER, \n\t\"Scores\" REAL, \n\t\"Author\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\")\n)\n/*\nColumns in submission and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nScores : 89.0, 79.0, 82.0, 83.0, 92.0, 93.0, 72.0, 78.0\nAuthor : Rick Engles, Andy Bolton, Jeff Lloyd, Don Bitterlich, Steve Raible, Steve Niehaus, Sherman Smith, Randy Johnson, Sammy Green, Steve Myer\nCollege : Fisk, Georgia Tech, Tulsa, Georgia, Miami (OH), West Texas State, Temple, Notre Dame, Florida, New Mexico\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Claims\" (\n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"FNOL_ID\" INTEGER NOT NULL, \n\t\"Effective_Date\" DATE, \n\tPRIMARY KEY (\"Claim_ID\"), \n\tFOREIGN KEY(\"FNOL_ID\") REFERENCES \"First_Notification_of_Loss\" (\"FNOL_ID\"), \n\tUNIQUE (\"Claim_ID\")\n)\n/*\nColumns in Claims and all categories for low cardinality columns :\nClaim_ID : 428, 309, 717, 145, 228, 311, 360, 134, 641, 604\nFNOL_ID : 1611, 4226, 2543, 4525, 1722, 4323, 532\nEffective_Date : 1985-03-24, 1975-05-07, 1992-02-09, 2006-06-10, 1982-05-03, 1996-11-29, 1992-01-05, 1973-08-18, 2014-10-19, 2009-02-11\n*/\n \nCREATE TABLE \"Accounts\" (\n\taccount_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tdate_account_opened DATETIME, \n\taccount_name VARCHAR(50), \n\tother_account_details VARCHAR(255), \n\tPRIMARY KEY (account_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Accounts and 3 examples in each column for high cardinality columns :\naccount_id : 1, 13, 11\ndate_account_opened : 2016-07-30 22:22:24, 2016-04-25 21:49:17, 2017-05-29 16:45:17\naccount_name : 601, 398, 900\n*/\n/*\nColumns in Accounts and all categories for low cardinality columns :\ncustomer_id : 13, 8, 6, 12, 3, 15, 9\nother_account_details : VIP, Regular\n*/\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/*\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_address_id INTEGER NOT NULL, \n\tnickname VARCHAR(80), \n\tfirst_name VARCHAR(80), \n\tmiddle_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tdate_of_birth DATETIME, \n\tdate_joined_staff DATETIME, \n\tdate_left_staff DATETIME, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(staff_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/*\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nnickname : ymiller, weissnat.vincenzo, nicholaus92\nfirst_name : Jedidiah, Eulalia, Camylle\nmiddle_name : Clarabelle, Maiya, Ulices\nlast_name : Sawayn, Maggio, Kuphal\ndate_of_birth : 2005-05-02 06:23:36, 2003-01-16 06:29:11, 2007-06-11 20:03:28\ndate_joined_staff : 2017-08-27 19:19:44, 2017-04-27 03:21:26, 2016-06-06 08:54:28\ndate_left_staff : 2018-03-08 12:31:16, 2018-03-10 15:25:00, 2018-03-24 10:11:08\n*/\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_address_id : 1, 3, 13, 2, 5, 7, 4, 6, 12, 14\n*/\n \nCREATE TABLE \"Team\" (\n\tid INTEGER, \n\tteam_api_id INTEGER, \n\tteam_fifa_api_id INTEGER, \n\tteam_long_name TEXT, \n\tteam_short_name TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Team and 3 examples in each column for high cardinality columns :\nid : 9553, 14876, 9547\nteam_api_id : 9761, 9875, 9847\nteam_fifa_api_id : 65, 1907, 1926\nteam_long_name : Lecce, AS Saint-Étienne, Stade Rennais FC\nteam_short_name : SIE, NIC, BAS\n*/\n\n \nCREATE TABLE \"Ref_Document_Types\" (\n\tdocument_type_code CHAR(15) NOT NULL, \n\tdocument_type_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (document_type_code)\n)\n/*\nColumns in Ref_Document_Types and all categories for low cardinality columns :\ndocument_type_code : Hard Drive, CD, Paper\ndocument_type_description : f, u, b\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n" }, { "role": "user", "content": "Which customers have made at least two orders? Give me each customer name and number of orders made." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: orders, customers.\nFrom these tables, I'll be using the following columns: customers.customer_name, orders.customer_id, customers.customer_id.\nThe SQL query I'll be generating is:\nSELECT T2.customer_name , count(*) FROM orders AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T2.customer_id HAVING count(*) >= 2" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE jobs (\n\t\"JOB_ID\" VARCHAR(10) DEFAULT '' NOT NULL, \n\t\"JOB_TITLE\" VARCHAR(35) NOT NULL, \n\t\"MIN_SALARY\" DECIMAL(6, 0) DEFAULT NULL, \n\t\"MAX_SALARY\" DECIMAL(6, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"JOB_ID\")\n)\n/*\nColumns in jobs and 3 examples in each column for high cardinality columns :\nJOB_ID : HR_REP, ST_MAN, AD_PRES\nJOB_TITLE : Purchasing Clerk, Stock Clerk, Marketing Manager\nMIN_SALARY : 20000, 8000, 3000\nMAX_SALARY : 20000, 8500, 40000\n*/\n\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\tinvoice_date DATETIME, \n\tinvoice_details VARCHAR(255), \n\tPRIMARY KEY (invoice_number)\n)\n/*\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 1987-11-15 15:41:40, 1998-07-30 15:39:12, 1974-07-27 16:18:49\ninvoice_details : doloremque, eveniet, earum\n*/\n\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Membership_card\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Time_of_purchase\" INTEGER, \n\t\"Level_of_membership\" INTEGER, \n\t\"Address\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Peeler, Russell, Rizzo, Todd, Campbell, Jessie, Breton, Robert, Komisarjevsky, Joshua, Webb, Daniel, Ashby, Lazale, Hayes, Steven, Reynolds, Richard, Cobb, Sedrick\nMembership_card : White, Black\nAge : 67, 45, 33, 50, 34, 42, 29, 51, 35\nTime_of_purchase : 26, 20, 44, 24, 18, 27, 41\nLevel_of_membership : 1, 2, 5, 4, 6, 3, 22\nAddress : Hartford, Bridgeport, Cheshire, Waterbury\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE \"Clients\" (\n\t\"Client_ID\" INTEGER NOT NULL, \n\t\"Address_ID\" INTEGER NOT NULL, \n\t\"Customer_Email_Address\" VARCHAR(255), \n\t\"Customer_Name\" VARCHAR(255), \n\t\"Customer_Phone\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Client_ID\"), \n\tFOREIGN KEY(\"Address_ID\") REFERENCES \"Addresses\" (\"Address_ID\"), \n\tUNIQUE (\"Client_ID\")\n)\n/*\nColumns in Clients and 3 examples in each column for high cardinality columns :\nClient_ID : 768, 887, 628\nAddress_ID : 201, 110, 180\nCustomer_Email_Address : strosin.keara@example.com, lacy92@example.com, westley30@example.net\nCustomer_Name : Krista, Marquis, Tevin\nCustomer_Phone : (745)818-8559x747, (042)912-3404x5135, (995)964-6385\n*/\n/*\nColumns in Clients and all categories for low cardinality columns :\nOther_Details : VIP, Super VIP, None\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n*/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n*/\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE \"Ref_Budget_Codes\" (\n\t\"Budget_Type_Code\" CHAR(15) NOT NULL, \n\t\"Budget_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Budget_Type_Code\")\n)\n/*\nColumns in Ref_Budget_Codes and all categories for low cardinality columns :\nBudget_Type_Code : GV, SF, ORG\nBudget_Type_Description : Self founded, Government, Organisation\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE party (\n\t\"Party_ID\" INTEGER, \n\t\"Minister\" TEXT, \n\t\"Took_office\" TEXT, \n\t\"Left_office\" TEXT, \n\t\"Region_ID\" INTEGER, \n\t\"Party_name\" TEXT, \n\tPRIMARY KEY (\"Party_ID\"), \n\tFOREIGN KEY(\"Region_ID\") REFERENCES region (\"Region_ID\")\n)\n/*\nColumns in party and all categories for low cardinality columns :\nParty_ID : 1, 2, 5, 4, 3\nMinister : Kojo Botsio (MP), Ebenezer Ako-Adjei (MP), Dr. Kwame Nkrumah (MP), Imoru Egala (MP)\nTook_office : 1958, 1961, 1959, 1960, 1957\nLeft_office : 1962, 1958, 1961, 1959, 1960\nRegion_ID : 1, 2, 5, 4, 3\nParty_name : Convention Peoples Party, Sinefine Party, Convention Union Party, 3, Progress Party\n*/\n" }, { "role": "user", "content": "Find the name of the customers who have at most two orders." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: orders, customers.\nFrom these tables, I'll be using the following columns: customers.customer_name, orders.customer_id, customers.customer_id.\nThe SQL query I'll be generating is:\nSELECT T2.customer_name FROM orders AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T2.customer_id HAVING count(*) <= 2" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/*\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n*/\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_date DATETIME NOT NULL, \n\torder_status_code VARCHAR(15), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\norder_date : 1979-03-29 02:47:13, 1985-01-03 05:22:09, 1992-04-19 21:42:58\n*/\n/*\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 1, 13, 2, 5, 4, 6, 3, 10, 9\norder_status_code : Completed, Part\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Ref_Address_Types\" (\n\taddress_type_code VARCHAR(15), \n\taddress_type_description VARCHAR(80), \n\tPRIMARY KEY (address_type_code)\n)\n/*\nColumns in Ref_Address_Types and all categories for low cardinality columns :\naddress_type_code : BILL, HOME\naddress_type_description : Billing, Home or Residence\n*/\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\tinvoice_date DATETIME, \n\tinvoice_details VARCHAR(255), \n\tPRIMARY KEY (invoice_number)\n)\n/*\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 1987-11-15 15:41:40, 1998-07-30 15:39:12, 1974-07-27 16:18:49\ninvoice_details : doloremque, eveniet, earum\n*/\n\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE schedule (\n\t\"Cinema_ID\" INTEGER, \n\t\"Film_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Show_times_per_day\" INTEGER, \n\t\"Price\" FLOAT, \n\tPRIMARY KEY (\"Cinema_ID\", \"Film_ID\"), \n\tFOREIGN KEY(\"Cinema_ID\") REFERENCES cinema (\"Cinema_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\")\n)\n/*\nColumns in schedule and all categories for low cardinality columns :\nCinema_ID : 1, 2, 6, 10, 9\nFilm_ID : 1, 2, 5, 4, 3\nDate : 20 May, 2 Aug, 11 July, 21 May, 19 May, 21 Jun\nShow_times_per_day : 2, 5, 4, 3\nPrice : 9.99, 8.99, 12.99, 15.99\n*/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\tname TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" TEXT, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/*\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nname : AIB, IFG, HGS2, HSBIF, BK Slide, ASC\nRegion : Japan, UK, China, Brazil, England, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n*/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE invoices (\n\tid INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tinvoice_date TIMESTAMP NOT NULL, \n\tbilling_address VARCHAR(70), \n\tbilling_city VARCHAR(40), \n\tbilling_state VARCHAR(40), \n\tbilling_country VARCHAR(40), \n\tbilling_postal_code VARCHAR(10), \n\ttotal NUMERIC(10, 2) NOT NULL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(customer_id) REFERENCES customers (id)\n)\n/*\nColumns in invoices and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\ncustomer_id : 53, 56, 49\ninvoice_date : 2008-09-13 00:00:00, 2007-07-11 00:00:00, 2007-10-08 00:00:00\nbilling_address : 696 Osborne Street, 796 Dundas Street West, Grétrystraat 63\nbilling_city : Oslo, Lisbon, Mountain View\nbilling_state : AZ, NSW, Dublin\nbilling_country : Sweden, Australia, India\nbilling_postal_code : B3S 1C5, 85719, 1106\ntotal : 3.96, 17.91, 15.86\n*/\n\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE climber (\n\t\"Climber_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Time\" TEXT, \n\t\"Points\" REAL, \n\t\"Mountain_ID\" INTEGER, \n\tPRIMARY KEY (\"Climber_ID\"), \n\tFOREIGN KEY(\"Mountain_ID\") REFERENCES mountain (\"Mountain_ID\")\n)\n/*\nColumns in climber and all categories for low cardinality columns :\nClimber_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Hans Luthringhauser, Charlie Freedman, Georg Auerbacher, Klaus Enders, Arseneus Butscher, Horst Owesle, Jean Claude Castella, Mick Horsepole, Siegfried Schauzu, L Currie\nCountry : West Germany, Switzerland, United Kingdom\nTime : 1:17.22.0, 1:25.02.8, 1:25.40.6, 1:27.28.8, 1:13.05.6, 1:18.14.6, 1:21.35.6, 1:17.16.0, 1:16.58.0, 1:14.56.4\nPoints : 8.0, 3.0, 12.0, 15.0, 10.0, 1.0, 6.0, 2.0, 4.0, 5.0\nMountain_ID : 1, 2, 5, 7, 3\n*/\n" }, { "role": "user", "content": "What are the names of the customers who have made two or less orders?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: orders, customers.\nFrom these tables, I'll be using the following columns: customers.customer_name, orders.customer_id, customers.customer_id.\nThe SQL query I'll be generating is:\nSELECT T2.customer_name FROM orders AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T2.customer_id HAVING count(*) <= 2" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcoupon_id INTEGER NOT NULL, \n\tgood_or_bad_customer VARCHAR(4), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tgender_mf VARCHAR(1), \n\tdate_became_customer DATETIME, \n\tdate_last_hire DATETIME, \n\tPRIMARY KEY (customer_id), \n\tFOREIGN KEY(coupon_id) REFERENCES \"Discount_Coupons\" (coupon_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\nfirst_name : Bridget, Marilou, Jailyn\nlast_name : Little, Greenholt, Schroeder\ndate_became_customer : 2017-02-28 14:40:25, 2015-05-05 20:29:01, 2015-07-21 09:24:57\ndate_last_hire : 2018-03-04 08:59:40, 2018-03-18 17:35:43, 2018-03-13 21:20:05\n*/\n/*\nColumns in Customers and all categories for low cardinality columns :\ncoupon_id : 1, 3, 11, 2, 7, 6, 14, 12, 10\ngood_or_bad_customer : bad, good\ngender_mf : 1, 0\n*/\n \nCREATE TABLE school_performance (\n\t\"School_Id\" INTEGER, \n\t\"School_Year\" TEXT, \n\t\"Class_A\" TEXT, \n\t\"Class_AA\" TEXT, \n\tPRIMARY KEY (\"School_Id\", \"School_Year\"), \n\tFOREIGN KEY(\"School_Id\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in school_performance and 3 examples in each column for high cardinality columns :\nSchool_Year : 1998-99, 2002-03, 1994-95\nClass_A : Skidmore-Tynan, Lindsay, Anton\nClass_AA : Buffalo, Henrietta, S&S Consolidated\n*/\n/*\nColumns in school_performance and all categories for low cardinality columns :\nSchool_Id : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE channel (\n\t\"Channel_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Owner\" TEXT, \n\t\"Share_in_percent\" REAL, \n\t\"Rating_in_percent\" REAL, \n\tPRIMARY KEY (\"Channel_ID\")\n)\n/*\nColumns in channel and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Shandong Satellite TV, CCTV-8, Hunan Satellite TV, CCTV-3, CCTV-14, CCTV-6, CCTV-13, CCTV-1, Anhui Satellite TV, CCTV-4\nOwner : HBS, Shandong Television, CCTV, Anhui Television\nShare_in_percent : 4.9, 2.33, 1.74, 2.91, 4.81, 2.6, 2.86, 3.76, 1.78, 2.73\nRating_in_percent : 0.53, 0.41, 0.32, 0.19, 0.54, 0.3, 0.31, 0.2, 0.29, 0.26\n*/\n \nCREATE TABLE teachers (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/*\nColumns in teachers and 3 examples in each column for high cardinality columns :\nLastName : MOYER, NIBLER, ONDERSMA\nFirstName : CHARMAINE, JEROME, KIRK\nClassroom : 109, 108, 106\n*/\n\n \nCREATE TABLE \"Street_Markets\" (\n\t\"Market_ID\" INTEGER NOT NULL, \n\t\"Market_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Market_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/*\nColumns in Street_Markets and all categories for low cardinality columns :\nMarket_ID : 6852, 7067\nMarket_Details : Broadway, Fish Farm Market\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/*\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n*/\n \nCREATE TABLE \"Genre\" (\n\t\"GenreId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(120) DEFAULT NULL, \n\tPRIMARY KEY (\"GenreId\")\n)\n/*\nColumns in Genre and 3 examples in each column for high cardinality columns :\nGenreId : 17, 21, 9\nName : Bossa Nova, Comedy, Opera\n*/\n\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\tinvoice_date DATETIME, \n\tinvoice_details VARCHAR(255), \n\tPRIMARY KEY (invoice_number)\n)\n/*\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 1987-11-15 15:41:40, 1998-07-30 15:39:12, 1974-07-27 16:18:49\ninvoice_details : doloremque, eveniet, earum\n*/\n\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Card_Number\" TEXT, \n\t\"Name\" TEXT, \n\t\"Hometown\" TEXT, \n\t\"Level\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nCard_Number : LT98, RE95, LCB7, FS10, MLB4, SLB51, RCB32, OLB56, LE99, RT91\nName : Trevard Lindley, Jeremy Jarmon, Corey Peters, David Jones, Myron Pryor, Matt Lentz, Johnny Williams, Ventrell Jenkins, Braxton Kelley, Micah Johnson\nHometown : Jacksonville, Florida, Collierville, Tennessee, Columbia, South Carolina, Red Jacket, West Virginia, Fort Campbell, Kentucky, LaGrange, Georgia, Louisville, Kentucky, Simpsonville, South Carolina, Hiram, Georgia\nLevel : 2, 4, 6\n*/\n \nCREATE TABLE climber (\n\t\"Climber_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Time\" TEXT, \n\t\"Points\" REAL, \n\t\"Mountain_ID\" INTEGER, \n\tPRIMARY KEY (\"Climber_ID\"), \n\tFOREIGN KEY(\"Mountain_ID\") REFERENCES mountain (\"Mountain_ID\")\n)\n/*\nColumns in climber and all categories for low cardinality columns :\nClimber_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Hans Luthringhauser, Charlie Freedman, Georg Auerbacher, Klaus Enders, Arseneus Butscher, Horst Owesle, Jean Claude Castella, Mick Horsepole, Siegfried Schauzu, L Currie\nCountry : West Germany, Switzerland, United Kingdom\nTime : 1:17.22.0, 1:25.02.8, 1:25.40.6, 1:27.28.8, 1:13.05.6, 1:18.14.6, 1:21.35.6, 1:17.16.0, 1:16.58.0, 1:14.56.4\nPoints : 8.0, 3.0, 12.0, 15.0, 10.0, 1.0, 6.0, 2.0, 4.0, 5.0\nMountain_ID : 1, 2, 5, 7, 3\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Player\" (\n\tid INTEGER, \n\tplayer_api_id INTEGER, \n\tplayer_name TEXT, \n\tplayer_fifa_api_id INTEGER, \n\tbirthday TEXT, \n\theight INTEGER, \n\tweight INTEGER, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Player and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\nplayer_api_id : 148827, 38423, 176301\nplayer_name : Adam Ounas, Abdelmalek Cherrad, Adrian\nplayer_fifa_api_id : 197081, 211185, 184410\nbirthday : 1988-08-25 00:00:00, 1986-12-02 00:00:00, 1978-12-22 00:00:00\nheight : 172.72, 175.26, 187.96\nweight : 185, 187, 163\n*/\n\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n" }, { "role": "user", "content": "List the names of the customers who have once bought product \"food\"." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: customers, orders, order_items, products.\nFrom these tables, I'll be using the following columns: customers.customer_name, customers.customer_id, orders.customer_id, orders.order_id, order_items.order_id, order_items.product_id, products.product_id, products.product_name, food.\nThe SQL query I'll be generating is:\nSELECT T1.customer_name FROM customers AS T1 JOIN orders AS T2 JOIN order_items AS T3 JOIN products AS T4 ON T1.customer_id = T2.customer_id AND T2.order_id = T3.order_id AND T3.product_id = T4.product_id WHERE T4.product_name = \"food\" GROUP BY T1.customer_id HAVING count(*) >= 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/*\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\tline_1 VARCHAR(80), \n\tline_2 VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode CHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/*\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 45, 5, 55\nline_1 : 83706 Ana Trafficway Apt. 992\nWest Jarret, MI 01112, 67831 Lavonne Lodge\nOlsontown, DC 20894, 801 Modesto Island Suite 306\nLacyville, VT 34059\nline_2 : Apt. 617, Apt. 163, Apt. 756\ncity : O'Connellview, Boyleshire, Linnealand\nzip_postcode : 431, 244, 514\nstate_province_county : Michigan, SouthDakota, Kansas\n*/\n/*\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Acceptance\" (\n\t\"Submission_ID\" INTEGER, \n\t\"Workshop_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\", \"Workshop_ID\"), \n\tFOREIGN KEY(\"Workshop_ID\") REFERENCES workshop (\"Workshop_ID\"), \n\tFOREIGN KEY(\"Submission_ID\") REFERENCES submission (\"Submission_ID\")\n)\n/*\nColumns in Acceptance and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 4, 3\nWorkshop_ID : 1, 2, 5, 6, 3\nResult : Accepted, Rejected\n*/\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, *BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n*/\n/*\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n*/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Representative_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Votes\" REAL, \n\t\"Vote_Percent\" REAL, \n\t\"Seats\" REAL, \n\t\"Place\" REAL, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"Representative_ID\") REFERENCES representative (\"Representative_ID\")\n)\n/*\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 4, 3\nRepresentative_ID : 1, 2, 5, 7, 4\nDate : 1946, 1949, July 1942, October 1942, 1953\nVotes : 11059.0, 9423.0, 13049.0, 12422.0, 14077.0\nVote_Percent : 16.0, 19.5, 16.2, 18.5\nSeats : 10.0, 6.0, 7.0, 9.0\nPlace : 3.0, 1.0, 2.0\n*/\n \nCREATE TABLE \"Accounts\" (\n\taccount_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\taccount_name VARCHAR(50), \n\tother_account_details VARCHAR(255), \n\tPRIMARY KEY (account_id)\n)\n/*\nColumns in Accounts and 3 examples in each column for high cardinality columns :\naccount_id : 1, 13, 11\naccount_name : 866, 725, 858\n*/\n/*\nColumns in Accounts and all categories for low cardinality columns :\ncustomer_id : 13, 2, 8, 4, 6, 12, 14, 10, 9\nother_account_details : VIP, Regular\n*/\n \nCREATE TABLE manager (\n\t\"Manager_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Working_year_starts\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Level\" INTEGER, \n\tPRIMARY KEY (\"Manager_ID\")\n)\n/*\nColumns in manager and all categories for low cardinality columns :\nManager_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ben Curtis, Sandy Lyle, Todd Hamilton, David Duval, Tiger Woods, Greg Norman, Nick Faldo\nCountry : United States, Australia, Scotland, England\nWorking_year_starts : 2004, 1993, 2001, 1985, 1999, 2006, 2003\nAge : 46, 45, 55, 48, 52, 47, 51\nLevel : 11, 5, 7, 8, 12\n*/\n \nCREATE TABLE nomination (\n\t\"Artwork_ID\" INTEGER, \n\t\"Festival_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\", \"Festival_ID\"), \n\tFOREIGN KEY(\"Festival_ID\") REFERENCES festival_detail (\"Festival_ID\"), \n\tFOREIGN KEY(\"Artwork_ID\") REFERENCES artwork (\"Artwork_ID\")\n)\n/*\nColumns in nomination and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 8, 4, 3, 9\nFestival_ID : 1, 2, 5\nResult : Nominated, Won\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\tinvoice_date DATETIME, \n\tinvoice_details VARCHAR(255), \n\tPRIMARY KEY (invoice_number)\n)\n/*\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 1987-11-15 15:41:40, 1998-07-30 15:39:12, 1974-07-27 16:18:49\ninvoice_details : doloremque, eveniet, earum\n*/\n\n \nCREATE TABLE grapes (\n\t\"ID\" INTEGER, \n\t\"Grape\" TEXT, \n\t\"Color\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tUNIQUE (\"Grape\")\n)\n/*\nColumns in grapes and 3 examples in each column for high cardinality columns :\nID : 17, 9, 16\nGrape : Marsanne, Tempranillo, Malbec\n*/\n/*\nColumns in grapes and all categories for low cardinality columns :\nColor : Red, White\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n" }, { "role": "user", "content": "What are the names of the customers who bought product \"food\" at least once?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: customers, orders, order_items, products.\nFrom these tables, I'll be using the following columns: customers.customer_name, customers.customer_id, orders.customer_id, orders.order_id, order_items.order_id, order_items.product_id, products.product_id, products.product_name, food.\nThe SQL query I'll be generating is:\nSELECT T1.customer_name FROM customers AS T1 JOIN orders AS T2 JOIN order_items AS T3 JOIN products AS T4 ON T1.customer_id = T2.customer_id AND T2.order_id = T3.order_id AND T3.product_id = T4.product_id WHERE T4.product_name = \"food\" GROUP BY T1.customer_id HAVING count(*) >= 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n*/\n \nCREATE TABLE \"Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResName\" VARCHAR(100), \n\t\"Address\" VARCHAR(100), \n\t\"Rating\" INTEGER, \n\tPRIMARY KEY (\"ResID\")\n)\n/*\nColumns in Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResName : Subway, Honeygrow\nAddress : 3212 St Paul St, Baltimore, MD 21218, 3233 St Paul St, Baltimore, MD 21218\nRating : 4, 3\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Documents\" (\n\tdocument_id INTEGER NOT NULL, \n\tdocument_status_code CHAR(15) NOT NULL, \n\tdocument_type_code CHAR(15) NOT NULL, \n\tshipping_agent_code CHAR(15), \n\treceipt_date DATETIME, \n\treceipt_number VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (document_id), \n\tFOREIGN KEY(document_type_code) REFERENCES \"Ref_Document_Types\" (document_type_code), \n\tFOREIGN KEY(document_status_code) REFERENCES \"Ref_Document_Status\" (document_status_code), \n\tFOREIGN KEY(shipping_agent_code) REFERENCES \"Ref_Shipping_Agents\" (shipping_agent_code)\n)\n/*\nColumns in Documents and 3 examples in each column for high cardinality columns :\ndocument_id : 1, 13, 20\nreceipt_date : 2014-12-25 17:22:44, 2008-04-21 20:42:25, 2015-04-03 09:36:19\nreceipt_number : 79, 114, 69\nother_details : m, q, b\n*/\n/*\nColumns in Documents and all categories for low cardinality columns :\ndocument_status_code : done, overdue, working\ndocument_type_code : Hard Drive, CD, Paper\nshipping_agent_code : FE, UP, US, AL, SH\n*/\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\tinvoice_date DATETIME, \n\tinvoice_details VARCHAR(255), \n\tPRIMARY KEY (invoice_number)\n)\n/*\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 1987-11-15 15:41:40, 1998-07-30 15:39:12, 1974-07-27 16:18:49\ninvoice_details : doloremque, eveniet, earum\n*/\n\n \nCREATE TABLE \"Services\" (\n\tservice_id INTEGER NOT NULL, \n\torganization_id INTEGER NOT NULL, \n\tservice_type_code CHAR(15) NOT NULL, \n\tservice_details VARCHAR(255), \n\tPRIMARY KEY (service_id), \n\tFOREIGN KEY(organization_id) REFERENCES \"Organizations\" (organization_id)\n)\n/*\nColumns in Services and 3 examples in each column for high cardinality columns :\nservice_id : 87, 41, 65\n*/\n/*\nColumns in Services and all categories for low cardinality columns :\norganization_id : 7, 10, 8\nservice_type_code : Cleanning, Moving Out, Check, Pay bills\nservice_details : Satisfied, Unsatisfied\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Years_Played\" TEXT, \n\t\"Total_WL\" TEXT, \n\t\"Singles_WL\" TEXT, \n\t\"Doubles_WL\" TEXT, \n\t\"Team\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\")\n)\n/*\nColumns in player and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nPlayer : Seol Jae-Min (none), An Jae-Sung, Kim Young-Jun (474), Cho Soong-Jae (630), Jeong Suk-Young (793), Lim Yong-Kyu (288), Im Kyu-tae (492), Bae Nam-Ju, Kim Hyun-Joon (908), Chung Hong (717)\nYears_Played : 8 (2003–2005, 2007–2011), 2 (1988, 1990), 3 (2005, 2007–2008), 1 (2011), 2 (2010–2011), 2 (2010-2011), 3 (2009–2011), 4 (2003–2004, 2010–2011)\nTotal_WL : 1–3, 2–2, 0–0, 6–9, 2–0, 3–4, 4–3, 6–4, 7–6, 1–2\nSingles_WL : 6–3, 5–6, 0–0, 1–0, 2–1, 0–2, 5–7, 3–2, 1–2\nDoubles_WL : 1–3, 2–2, 0–0, 1–0, 1–1, 2–0, 0–1, 1–2\nTeam : 1, 2, 8, 4, 6\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE debate (\n\t\"Debate_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Debate_ID\")\n)\n/*\nColumns in debate and all categories for low cardinality columns :\nDebate_ID : 1, 2, 5, 4, 6, 3\nDate : October 21, 2011, December 17, 2014, August 3, 2015, January 21, 2017, October 27, 2015, January 12, 2017\nVenue : Abu Dhabi , UAE, Doha , Qatar, Dubai , UAE, Manama , Bahrain\nNum_of_Audience : 342, 159, 90, 209, 313, 134\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE pilot (\n\t\"Pilot_ID\" INTEGER, \n\t\"Pilot_name\" TEXT, \n\t\"Rank\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Nationality\" TEXT, \n\t\"Position\" TEXT, \n\t\"Join_Year\" INTEGER, \n\t\"Team\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\")\n)\n/*\nColumns in pilot and all categories for low cardinality columns :\nPilot_ID : 1, 2, 5, 4, 3\nPilot_name : Patrick O'Bryant, Charles Oakley, Dan O'Sullivan, Hakeem Olajuwon, Jermaine O'Neal\nRank : 34, 13, 45, 6\nAge : 37, 33, 40, 32, 22\nNationality : United States, Nigeria, United Kindom\nPosition : Center Team, Forward Team, Forward-Center Team\nJoin_Year : 2009, 2001, 2008, 1999, 2010\nTeam : Fordham, Eau Claire High School, Bradley, Virginia Union, Houston\n*/\n" }, { "role": "user", "content": "List the names of customers who have once canceled the purchase of the product \"food\" (the item status is \"Cancel\")." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: customers, orders, order_items, products.\nFrom these tables, I'll be using the following columns: customers.customer_name, customers.customer_id, orders.customer_id, orders.order_id, order_items.order_id, order_items.product_id, products.product_id, order_items.order_item_status, Cancel, products.product_name, food.\nThe SQL query I'll be generating is:\nSELECT T1.customer_name FROM customers AS T1 JOIN orders AS T2 JOIN order_items AS T3 JOIN products AS T4 ON T1.customer_id = T2.customer_id AND T2.order_id = T3.order_id AND T3.product_id = T4.product_id WHERE T3.order_item_status = \"Cancel\" AND T4.product_name = \"food\" GROUP BY T1.customer_id HAVING count(*) >= 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/*\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n*/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/*\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n*/\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/*\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n*/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n*/\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, *BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n*/\n/*\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\tinvoice_date DATETIME, \n\tinvoice_details VARCHAR(255), \n\tPRIMARY KEY (invoice_number)\n)\n/*\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 1987-11-15 15:41:40, 1998-07-30 15:39:12, 1974-07-27 16:18:49\ninvoice_details : doloremque, eveniet, earum\n*/\n\n \nCREATE TABLE shop (\n\t\"Shop_ID\" INTEGER, \n\t\"Address\" TEXT, \n\t\"Num_of_staff\" TEXT, \n\t\"Score\" REAL, \n\t\"Open_Year\" TEXT, \n\tPRIMARY KEY (\"Shop_ID\")\n)\n/*\nColumns in shop and all categories for low cardinality columns :\nShop_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAddress : 414 E. 12th Street, 324 E. 11th Street, 1330 Baltimore Street, 1201 Walnut Street, 909 Main Street, 1111 Main Street, 2345 McGee Street, 1200 Main Street, 1100 Main Street, 909 Walnut Street\nNum_of_staff : 16, 13, 28, 24, 34, 23, 19, 42, 27, 425\nScore : 36.0, 30.0, 42.0, 28.0, 38.0, 40.0, 32.0\nOpen_Year : 2008, 2010, 2011, 2006\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(10) NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ndate_order_placed : 1974-06-24 22:10:26, 2002-09-13 07:38:09, 1982-12-09 09:42:23\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\ncustomer_id : 11, 10, 2, 5, 7, 8, 4, 3, 15, 9\norder_status : On Road, Packing, Shipped\norder_details : None\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_name : music, food, clothes, book, phone\nproduct_details : None\n*/\n" }, { "role": "user", "content": "Which customers have ever canceled the purchase of the product \"food\" (the item status is \"Cancel\")?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: customers, orders, order_items, products.\nFrom these tables, I'll be using the following columns: customers.customer_name, customers.customer_id, orders.customer_id, orders.order_id, order_items.order_id, order_items.product_id, products.product_id, order_items.order_item_status, Cancel, products.product_name, food.\nThe SQL query I'll be generating is:\nSELECT T1.customer_name FROM customers AS T1 JOIN orders AS T2 JOIN order_items AS T3 JOIN products AS T4 ON T1.customer_id = T2.customer_id AND T2.order_id = T3.order_id AND T3.product_id = T4.product_id WHERE T3.order_item_status = \"Cancel\" AND T4.product_name = \"food\" GROUP BY T1.customer_id HAVING count(*) >= 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/*\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n*/\n \nCREATE TABLE device (\n\t\"Device_ID\" INTEGER, \n\t\"Device\" TEXT, \n\t\"Carrier\" TEXT, \n\t\"Package_Version\" TEXT, \n\t\"Applications\" TEXT, \n\t\"Software_Platform\" TEXT, \n\tPRIMARY KEY (\"Device_ID\")\n)\n/*\nColumns in device and all categories for low cardinality columns :\nDevice_ID : 1, 2, 5, 4, 6, 3\nDevice : Huawei, Galaxy, Apple, Xiaomi, BlackBerry Storm 9530, Samsung\nCarrier : MTS Mobility, Bell Mobility, Telus Mobility, Vodafone AU, Verizon Wireless, Iusacell\nPackage_Version : 4.7.0.208, 5.0.0.742, 5.0.0.808, 5.0.0.328, 5.0.0.419\nApplications : 4.7.0.151, 5.0.0.451, 5.0.0.328, 5.0.0.419\nSoftware_Platform : iOS, Android\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Years_Played\" TEXT, \n\t\"Total_WL\" TEXT, \n\t\"Singles_WL\" TEXT, \n\t\"Doubles_WL\" TEXT, \n\t\"Team\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\")\n)\n/*\nColumns in player and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nPlayer : Seol Jae-Min (none), An Jae-Sung, Kim Young-Jun (474), Cho Soong-Jae (630), Jeong Suk-Young (793), Lim Yong-Kyu (288), Im Kyu-tae (492), Bae Nam-Ju, Kim Hyun-Joon (908), Chung Hong (717)\nYears_Played : 8 (2003–2005, 2007–2011), 2 (1988, 1990), 3 (2005, 2007–2008), 1 (2011), 2 (2010–2011), 2 (2010-2011), 3 (2009–2011), 4 (2003–2004, 2010–2011)\nTotal_WL : 1–3, 2–2, 0–0, 6–9, 2–0, 3–4, 4–3, 6–4, 7–6, 1–2\nSingles_WL : 6–3, 5–6, 0–0, 1–0, 2–1, 0–2, 5–7, 3–2, 1–2\nDoubles_WL : 1–3, 2–2, 0–0, 1–0, 1–1, 2–0, 0–1, 1–2\nTeam : 1, 2, 8, 4, 6\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE happy_hour_member (\n\t\"HH_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Total_amount\" REAL, \n\tPRIMARY KEY (\"HH_ID\", \"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/*\nColumns in happy_hour_member and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4\nMember_ID : 5, 9, 3\nTotal_amount : 4.9, 4.2, 20.9, 16.9, 16.92, 20.92\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE affected_region (\n\t\"Region_id\" INTEGER, \n\t\"Storm_ID\" INTEGER, \n\t\"Number_city_affected\" REAL, \n\tPRIMARY KEY (\"Region_id\", \"Storm_ID\"), \n\tFOREIGN KEY(\"Storm_ID\") REFERENCES storm (\"Storm_ID\"), \n\tFOREIGN KEY(\"Region_id\") REFERENCES region (\"Region_id\")\n)\n/*\nColumns in affected_region and all categories for low cardinality columns :\nRegion_id : 1, 2, 12, 3\nStorm_ID : 1, 5, 4, 3\nNumber_city_affected : 12.0, 30.0, 15.0, 10.0, 22.0, 37.0\n*/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tnetwork_name TEXT, \n\tservices TEXT, \n\tlocal_authority TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nnetwork_name : Chalfont & Latimer, Chorleywood, Brentwood\n*/\n/*\nColumns in station and all categories for low cardinality columns :\nservices : Greater Anglia, Metropolitan line and Chiltern Railways, Metropolitan line, c2c, London Overground and London Midland, London Overground\nlocal_authority : Three Rivers, Brentwood, Broxbourne, Thurrock, Watford, Chiltern\n*/\n \nCREATE TABLE wrestler (\n\t\"Wrestler_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Reign\" TEXT, \n\t\"Days_held\" TEXT, \n\t\"Location\" TEXT, \n\t\"Event\" TEXT, \n\tPRIMARY KEY (\"Wrestler_ID\")\n)\n/*\nColumns in wrestler and all categories for low cardinality columns :\nWrestler_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Fishman, El Samurai §, Rey Misterio Sr., Último Dragón §, Shinjiro Otani §, Gran Hamada, Jushin Liger §, Villaño IV, The Great Sasuke §, El Samurai\nReign : 1, 2\nDays_held : 1, 113, 35, 56, 183, 1285, 960, 344, 99, 54\nLocation : Nagoya , Japan, Tijuana , Mexico, Sapporo , Japan, Tokyo , Japan, Osaka , Japan\nEvent : Wrestling World 1997, Live event\n*/\n \nCREATE TABLE workshop (\n\t\"Workshop_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Workshop_ID\")\n)\n/*\nColumns in workshop and all categories for low cardinality columns :\nWorkshop_ID : 1, 2, 5, 4, 6, 3\nDate : July 5, 2011, August 21, 2007, October 8, 2007, January 14, 2008, August 25, 2007, August 18, 2007\nVenue : London UK, New York USA, Istanbul Turkey, New Jersey USA\nName : Workshop 2007, 2008 qualification, Anual Workshop 2011, ABC 2007, 2007 qualification, Conference 2007\n*/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n*/\n/*\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n*/\n \nCREATE TABLE coach (\n\t\"Coach_ID\" INTEGER, \n\t\"Coach_name\" TEXT, \n\t\"Gender\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Coach_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/*\nColumns in coach and all categories for low cardinality columns :\nCoach_ID : 1, 2, 5, 4, 3\nCoach_name : Robert Chen, James Wong, Smith Brown, Jameson Tomas, Joe Fabbri\nGender : F, M\nClub_ID : 1, 3\nRank : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Club\" (\n\t\"ClubID\" INTEGER, \n\t\"ClubName\" VARCHAR(40), \n\t\"ClubDesc\" VARCHAR(1024), \n\t\"ClubLocation\" VARCHAR(40), \n\tPRIMARY KEY (\"ClubID\")\n)\n/*\nColumns in Club and all categories for low cardinality columns :\nClubID : 1, 2, 4, 3\nClubName : Bootup Baltimore, Pen and Paper Gaming, Tennis Club, Hopkins Student Enterprises\nClubDesc : Venture capital fund for student business., A competitive tennis club., Refurbish computers; teach kids and adults about computer basics., Play pen and paper games on campus.\nClubLocation : HHH, AKW\n*/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\tname TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" TEXT, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/*\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nname : AIB, IFG, HGS2, HSBIF, BK Slide, ASC\nRegion : Japan, UK, China, Brazil, England, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n*/\n \nCREATE TABLE protein (\n\tcommon_name TEXT, \n\tprotein_name TEXT, \n\tdivergence_from_human_lineage REAL, \n\taccession_number TEXT, \n\tsequence_length REAL, \n\tsequence_identity_to_human_protein TEXT, \n\t\"Institution_id\" TEXT, \n\tPRIMARY KEY (common_name), \n\tFOREIGN KEY(\"Institution_id\") REFERENCES \"Institution\" (\"Institution_id\")\n)\n/*\nColumns in protein and all categories for low cardinality columns :\ncommon_name : Tropical Clawed Frog, porkworm, body louse, southern house mosquito, purple sea urchin\nprotein_name : uncharacterized protein LOC578090, conserved hypothetical protein, Centromeric protein E, putative, surface antigen repeat family protein, uncharacterized protein C20orf117-like\ndivergence_from_human_lineage : 937.5, 742.9, 782.7, 371.2\naccession_number : XP_003380263.1, XP_002942331.1, XP_783370.2, XP_002429877.1, XP_001843754.1\nsequence_length : 2030.0, 1587.0, 2086.0, 1584.0, 1878.0\nsequence_identity_to_human_protein : 30%, 47%, 36%, 39%, 32%\nInstitution_id : 1, 5, 9, 3\n*/\n" }, { "role": "user", "content": "How many architects are female?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: architect.\nFrom these tables, I'll be using the following columns: gender.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM architect WHERE gender = 'female'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Minor_in\" (\n\t\"StuID\" INTEGER, \n\t\"DNO\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"DNO\") REFERENCES \"Department\" (\"DNO\")\n)\n/*\nColumns in Minor_in and all categories for low cardinality columns :\nStuID : 1006, 1007, 1008, 1014, 1027, 1005, 1004, 1031, 1015, 1016\nDNO : 520, 90, 190, 140, 50, 540, 550, 530\n*/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n*/\n \nCREATE TABLE \"Document_Locations\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Location_Code\" CHAR(15) NOT NULL, \n\t\"Date_in_Location_From\" DATETIME NOT NULL, \n\t\"Date_in_Locaton_To\" DATETIME, \n\tPRIMARY KEY (\"Document_ID\", \"Location_Code\", \"Date_in_Location_From\"), \n\tFOREIGN KEY(\"Location_Code\") REFERENCES \"Ref_Locations\" (\"Location_Code\"), \n\tFOREIGN KEY(\"Date_in_Location_From\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Date_in_Locaton_To\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"All_Documents\" (\"Document_ID\")\n)\n/*\nColumns in Document_Locations and all categories for low cardinality columns :\nDocument_ID : 230, 11, 252, 170, 7, 119, 260, 111, 166, 81\nLocation_Code : b, e, c, n, x\nDate_in_Location_From : 2009-08-18 03:29:08, 1972-03-31 09:47:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1985-05-13 12:19:43, 2008-06-08 12:45:38\nDate_in_Locaton_To : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1987-11-05 06:11:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1976-06-15 03:40:06, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1995-01-01 03:52:11, 2008-06-08 12:45:38\n*/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Counties_Represented\" TEXT, \n\t\"District\" INTEGER, \n\t\"Delegate\" TEXT, \n\t\"Party\" INTEGER, \n\t\"First_Elected\" REAL, \n\t\"Committee\" TEXT, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"District\") REFERENCES county (\"County_Id\"), \n\tFOREIGN KEY(\"Party\") REFERENCES party (\"Party_ID\")\n)\n/*\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 7, 8, 4, 6, 3\nCounties_Represented : 09.1 9A, 13, 12.1 12A, 12.2 12B\nDistrict : 1, 2, 4, 3\nDelegate : Miller, Warren E. Warren E. Miller, Bobo, Elizabeth Elizabeth Bobo, Pendergrass, Shane E. Shane Pendergrass, Bates, Gail H. Gail H. Bates, DeBoy, Steven J. Sr. Steven J. DeBoy, Sr., Guzzone, Guy Guy Guzzone, Turner, Frank S. Frank S. Turner, Malone, James E. Jr. James E. Malone, Jr.\nParty : 1, 2, 7, 4, 3\nFirst_Elected : 2002.0, 2006.0, 1994.0, 2003.0\nCommittee : Environmental Matters, Economic Matters, Ways and Means, Environmental Matters (Vice-Chair), Health and Government Operations, Appropriations\n*/\n \nCREATE TABLE \"Employees\" (\n\t\"Employee_ID\" INTEGER NOT NULL, \n\t\"Role_Code\" CHAR(15) NOT NULL, \n\t\"Employee_Name\" VARCHAR(255), \n\t\"Gender_MFU\" CHAR(1) NOT NULL, \n\t\"Date_of_Birth\" DATETIME NOT NULL, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Employee_ID\"), \n\tFOREIGN KEY(\"Role_Code\") REFERENCES \"Roles\" (\"Role_Code\")\n)\n/*\nColumns in Employees and 3 examples in each column for high cardinality columns :\nEmployee_ID : 173, 159, 38\nEmployee_Name : Harley, Armani, Leo\nDate_of_Birth : 1973-04-04 21:41:22, 1977-07-04 16:25:21, 1979-09-20 12:50:15\n*/\n/*\nColumns in Employees and all categories for low cardinality columns :\nRole_Code : PR, HR, PT, MG, ED\nGender_MFU : , 1\nOther_Details : None\n*/\n \nCREATE TABLE debate_people (\n\t\"Debate_ID\" INTEGER, \n\t\"Affirmative\" INTEGER, \n\t\"Negative\" INTEGER, \n\t\"If_Affirmative_Win\" BOOLEAN, \n\tPRIMARY KEY (\"Debate_ID\", \"Affirmative\", \"Negative\"), \n\tFOREIGN KEY(\"Negative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Affirmative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Debate_ID\") REFERENCES debate (\"Debate_ID\")\n)\n/*\nColumns in debate_people and all categories for low cardinality columns :\nDebate_ID : 1, 5, 4, 6, 3\nAffirmative : 1, 2, 4, 5\nNegative : 7, 10, 8, 6\nIf_Affirmative_Win : True\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Member_Name\" TEXT, \n\t\"Party_ID\" TEXT, \n\t\"In_office\" TEXT, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/*\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 13, 11\nMember_Name : Hon Bob Baldwin, Hon Kim Beazley, Kerry Bartlett\nIn_office : 1980–2007, 1996–2007, 1990–2010\n*/\n/*\nColumns in member and all categories for low cardinality columns :\nParty_ID : 1, 2, 3\n*/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Years_Played\" TEXT, \n\t\"Total_WL\" TEXT, \n\t\"Singles_WL\" TEXT, \n\t\"Doubles_WL\" TEXT, \n\t\"Team\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\")\n)\n/*\nColumns in player and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nPlayer : Seol Jae-Min (none), An Jae-Sung, Kim Young-Jun (474), Cho Soong-Jae (630), Jeong Suk-Young (793), Lim Yong-Kyu (288), Im Kyu-tae (492), Bae Nam-Ju, Kim Hyun-Joon (908), Chung Hong (717)\nYears_Played : 8 (2003–2005, 2007–2011), 2 (1988, 1990), 3 (2005, 2007–2008), 1 (2011), 2 (2010–2011), 2 (2010-2011), 3 (2009–2011), 4 (2003–2004, 2010–2011)\nTotal_WL : 1–3, 2–2, 0–0, 6–9, 2–0, 3–4, 4–3, 6–4, 7–6, 1–2\nSingles_WL : 6–3, 5–6, 0–0, 1–0, 2–1, 0–2, 5–7, 3–2, 1–2\nDoubles_WL : 1–3, 2–2, 0–0, 1–0, 1–1, 2–0, 0–1, 1–2\nTeam : 1, 2, 8, 4, 6\n*/\n \nCREATE TABLE \"Ref_Transaction_Types\" (\n\ttransaction_type_code VARCHAR(10), \n\ttransaction_type_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (transaction_type_code)\n)\n/*\nColumns in Ref_Transaction_Types and all categories for low cardinality columns :\ntransaction_type_code : PUR, SALE\ntransaction_type_description : Sale, Purchase\n*/\n \nCREATE TABLE volume (\n\t\"Volume_ID\" INTEGER, \n\t\"Volume_Issue\" TEXT, \n\t\"Issue_Date\" TEXT, \n\t\"Weeks_on_Top\" REAL, \n\t\"Song\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\tPRIMARY KEY (\"Volume_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in volume and all categories for low cardinality columns :\nVolume_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nVolume_Issue : 46:5, 46:16, 46:14-15, 45:15, 45:21-22, 45:16, 46:6-8, 45:14 §, 46:10, 46:9\nIssue_Date : 16 May - 30 May, 6 June, 27 December 1986 - 10 January, 28 February - 7 March, 13 June, 24 January, 9 May, 17 January, 11 July - 18 July, 25 July\nWeeks_on_Top : 3.0, 1.0, 2.0\nSong : Head to Toe , Always , With or Without You , Looking for a New Love, La Isla Bonita , The Way, Everybody Have Fun Tonight , Touch Me (I Want Your Body) , (I Just) Died in Your Arms , Walk Like an Egyptian \nArtist_ID : 1, 2, 5, 4, 6\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Time\" TEXT, \n\t\"Service\" TEXT, \n\tPRIMARY KEY (\"Train_ID\")\n)\n/*\nColumns in train and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\nTime : 10:38, 16:59, 11:15\n*/\n/*\nColumns in train and all categories for low cardinality columns :\nName : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\nService : Daily\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n" }, { "role": "user", "content": "List the name, nationality and id of all male architects ordered by their names lexicographically." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: architect.\nFrom these tables, I'll be using the following columns: name, nationality, id, gender.\nThe SQL query I'll be generating is:\nSELECT name , nationality , id FROM architect WHERE gender = 'male' ORDER BY name" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n*/\n/*\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n*/\n \nCREATE TABLE competition_record (\n\t\"Competition_ID\" INTEGER, \n\t\"Farm_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Competition_ID\", \"Farm_ID\"), \n\tFOREIGN KEY(\"Farm_ID\") REFERENCES farm (\"Farm_ID\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES farm_competition (\"Competition_ID\")\n)\n/*\nColumns in competition_record and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 3\nFarm_ID : 1, 2, 5, 7, 8, 4, 3\nRank : 1, 2, 4, 3\n*/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/*\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n*/\n \nCREATE TABLE item (\n\ti_id INTEGER NOT NULL, \n\ttitle VARCHAR(20) DEFAULT NULL, \n\tPRIMARY KEY (i_id)\n)\n/*\nColumns in item and all categories for low cardinality columns :\ni_id : 1, 2, 5, 7, 4, 6, 3, 0\ntitle : pear, shampoo, blue hoodie, orange, comb, cup, avocado, apple\n*/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/*\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n*/\n \nCREATE TABLE \"Roles\" (\n\trole_code CHAR(15) NOT NULL, \n\trole_description VARCHAR(255), \n\tPRIMARY KEY (role_code)\n)\n/*\nColumns in Roles and all categories for low cardinality columns :\nrole_code : MG, ED, PR, PT\nrole_description : Editor, Proof Manager, Manager, Photo\n*/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/*\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n*/\n \nCREATE TABLE pilot_record (\n\t\"Record_ID\" INTEGER, \n\t\"Pilot_ID\" INTEGER, \n\t\"Aircraft_ID\" INTEGER, \n\t\"Date\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\", \"Aircraft_ID\", \"Date\"), \n\tFOREIGN KEY(\"Aircraft_ID\") REFERENCES aircraft (\"Aircraft_ID\"), \n\tFOREIGN KEY(\"Pilot_ID\") REFERENCES pilot (\"Pilot_ID\")\n)\n/*\nColumns in pilot_record and all categories for low cardinality columns :\nRecord_ID : 1, 2, 5, 4, 6, 3\nPilot_ID : 1, 2, 4, 3\nAircraft_ID : 1, 2, 5, 4, 6\nDate : 2006/01/04, 2005/01/04, 2008/01/04, 2004/01/04, 2007/01/04, 2003/01/04\n*/\n \nCREATE TABLE \"Hotels\" (\n\thotel_id INTEGER NOT NULL, \n\tstar_rating_code CHAR(15) NOT NULL, \n\tpets_allowed_yn CHAR(1), \n\tprice_range REAL, \n\tother_hotel_details VARCHAR(255), \n\tPRIMARY KEY (hotel_id), \n\tFOREIGN KEY(star_rating_code) REFERENCES \"Ref_Hotel_Star_Ratings\" (star_rating_code)\n)\n/*\nColumns in Hotels and 3 examples in each column for high cardinality columns :\nhotel_id : 514, 123, 420\nprice_range : , 250548014.90329, 2914989.571\n*/\n/*\nColumns in Hotels and all categories for low cardinality columns :\nstar_rating_code : 1, 2, 5, 4, 3\npets_allowed_yn : 1, \nother_hotel_details : None\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n*/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n*/\n \nCREATE TABLE countries (\n\t\"COUNTRY_ID\" VARCHAR(2) NOT NULL, \n\t\"COUNTRY_NAME\" VARCHAR(40) DEFAULT NULL, \n\t\"REGION_ID\" DECIMAL(10, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"COUNTRY_ID\"), \n\tFOREIGN KEY(\"REGION_ID\") REFERENCES regions (\"REGION_ID\")\n)\n/*\nColumns in countries and 3 examples in each column for high cardinality columns :\nCOUNTRY_ID : AR, JP, DE\nCOUNTRY_NAME : Israel, Australia, India\n*/\n/*\nColumns in countries and all categories for low cardinality columns :\nREGION_ID : 1, 2, 4, 3\n*/\n \nCREATE TABLE team (\n\t\"Team_id\" INTEGER, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Team_id\")\n)\n/*\nColumns in team and all categories for low cardinality columns :\nTeam_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Enrique Osinski, Berneice Hand, Columbus Crew, Evalyn Feil, D.C. United, Anais VonRueden, Ryley Goldner, Miami Fusion, Los Angeles Galaxy, Brown Erdman\n*/\n \nCREATE TABLE \"Vocals\" (\n\t\"SongId\" INTEGER, \n\t\"Bandmate\" INTEGER, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"SongId\", \"Bandmate\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"Bandmate\") REFERENCES \"Band\" (\"Id\")\n)\n/*\nColumns in Vocals and all categories for low cardinality columns :\nSongId : \nBandmate : \nType : \n*/\n \nCREATE TABLE debate_people (\n\t\"Debate_ID\" INTEGER, \n\t\"Affirmative\" INTEGER, \n\t\"Negative\" INTEGER, \n\t\"If_Affirmative_Win\" BOOLEAN, \n\tPRIMARY KEY (\"Debate_ID\", \"Affirmative\", \"Negative\"), \n\tFOREIGN KEY(\"Negative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Affirmative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Debate_ID\") REFERENCES debate (\"Debate_ID\")\n)\n/*\nColumns in debate_people and all categories for low cardinality columns :\nDebate_ID : 1, 5, 4, 6, 3\nAffirmative : 1, 2, 4, 5\nNegative : 7, 10, 8, 6\nIf_Affirmative_Win : True\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Visits\" (\n\t\"Visit_ID\" INTEGER NOT NULL, \n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Tourist_ID\" INTEGER NOT NULL, \n\t\"Visit_Date\" DATETIME NOT NULL, \n\t\"Visit_Details\" VARCHAR(40) NOT NULL, \n\tPRIMARY KEY (\"Visit_ID\"), \n\tFOREIGN KEY(\"Tourist_Attraction_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\"), \n\tFOREIGN KEY(\"Tourist_ID\") REFERENCES \"Visitors\" (\"Tourist_ID\")\n)\n/*\nColumns in Visits and 3 examples in each column for high cardinality columns :\nVisit_ID : 563, 479, 937\nTourist_ID : 610, 439, 204\nVisit_Date : 1974-12-31 23:18:24, 2007-09-17 10:12:45, 1998-05-12 00:50:20\n*/\n/*\nColumns in Visits and all categories for low cardinality columns :\nTourist_Attraction_ID : 5076, 6653, 8429, 9360, 6852, 8698, 6476, 2701, 9919, 6523\nVisit_Details : \n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"Purchases\" (\n\tpurchase_transaction_id INTEGER NOT NULL, \n\tpurchase_details VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(purchase_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/*\nColumns in Purchases and 3 examples in each column for high cardinality columns :\npurchase_transaction_id : 1, 13, 11\npurchase_details : t, i, o\n*/\n\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n" }, { "role": "user", "content": "What is the maximum length in meters for the bridges and what are the architects' names?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: bridge, architect.\nFrom these tables, I'll be using the following columns: bridge.length_meters, architect.name, bridge.architect_id, architect.id.\nThe SQL query I'll be generating is:\nSELECT max(T1.length_meters) , T2.name FROM bridge AS T1 JOIN architect AS T2 ON T1.architect_id = T2.id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE repair_assignment (\n\ttechnician_id INTEGER, \n\t\"repair_ID\" INTEGER, \n\t\"Machine_ID\" INTEGER, \n\tPRIMARY KEY (technician_id, \"repair_ID\", \"Machine_ID\"), \n\tFOREIGN KEY(\"Machine_ID\") REFERENCES machine (\"Machine_ID\"), \n\tFOREIGN KEY(\"repair_ID\") REFERENCES repair (\"repair_ID\"), \n\tFOREIGN KEY(technician_id) REFERENCES technician (technician_id)\n)\n/*\nColumns in repair_assignment and all categories for low cardinality columns :\ntechnician_id : 1, 2, 5, 7, 3\nrepair_ID : 1, 2, 5, 8, 4, 3\nMachine_ID : 1, 2, 7, 4, 6, 3\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n*/\n \nCREATE TABLE \"Draft_Copies\" (\n\tdocument_id INTEGER NOT NULL, \n\tdraft_number INTEGER NOT NULL, \n\tcopy_number INTEGER NOT NULL, \n\tPRIMARY KEY (document_id, draft_number, copy_number), \n\tFOREIGN KEY(document_id, draft_number) REFERENCES \"Document_Drafts\" (document_id, draft_number)\n)\n/*\nColumns in Draft_Copies and all categories for low cardinality columns :\ndocument_id : 1, 20, 2, 23, 4, 12, 10\ndraft_number : 1, 20, 2, 8, 17, 12, 9\ncopy_number : 5, 15, 4, 6, 10\n*/\n \nCREATE TABLE actor (\n\tactor_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(45) NOT NULL, \n\tlast_name VARCHAR(45) NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (actor_id)\n)\n/*\nColumns in actor and 3 examples in each column for high cardinality columns :\nactor_id : 87, 56, 65\nfirst_name : WALTER, KIM, REESE\nlast_name : WITHERSPOON, OLIVIER, ALLEN\n*/\n/*\nColumns in actor and all categories for low cardinality columns :\nlast_update : 2006-02-15 04:34:33\n*/\n \nCREATE TABLE \"Individuals\" (\n\tindividual_id INTEGER, \n\tindividual_first_name VARCHAR(80), \n\tindividual_middle_name VARCHAR(80), \n\tinidividual_phone VARCHAR(80), \n\tindividual_email VARCHAR(80), \n\tindividual_address VARCHAR(255), \n\tindividual_last_name VARCHAR(80), \n\tPRIMARY KEY (individual_id)\n)\n/*\nColumns in Individuals and 3 examples in each column for high cardinality columns :\nindividual_id : 1, 13, 11\nindividual_first_name : Daniella, Guy, Allene\nindividual_middle_name : Hosea, Tommie, Colleen\ninidividual_phone : (121)788-2928, 1-727-057-0382x999, 1-818-062-2837\nindividual_email : zlehner@example.net, hickle.ewell@example.com, mbahringer@example.com\nindividual_address : 69578 Baylee Prairie, 104 Bernier Loop, 640 Johns Branch\nindividual_last_name : Rau, Hand, Maggio\n*/\n\n \nCREATE TABLE \"Roles\" (\n\t\"Role_Code\" CHAR(15) NOT NULL, \n\t\"Role_Name\" VARCHAR(255), \n\t\"Role_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Role_Code\")\n)\n/*\nColumns in Roles and all categories for low cardinality columns :\nRole_Code : PR, HR, PT, MG, ED\nRole_Name : Proof Reader, Human Resource, Editor, Photo, Manager\nRole_Description : Itaque dolor ut nemo rerum vitae provident. Vel laborum ipsum velit sint. Et est omnis dignissimos., Ut sed quae eaque mollitia qui hic. Natus ea expedita et odio illum fugiat qui natus. Consequatur velit ut dolorem cum ullam esse deserunt dignissimos. Enim non non rem officiis quis., Aut modi nihil molestias temporibus sit rerum. Sit neque eaque odio omnis incidunt., Vero harum corrupti odit ipsa vero et odio. Iste et recusandae temporibus maxime. Magni aspernatur fugit quis explicabo totam esse corrupti., Et totam est quibusdam aspernatur ut. Vitae perferendis eligendi voluptatem molestiae rem ut enim. Ipsum expedita quae earum unde est. Repellendus ut ipsam nihil accusantium sit. Magni accusantium numquam quod et.\n*/\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/*\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n*/\n \nCREATE TABLE buildings (\n\tid INTEGER, \n\tname TEXT, \n\t\"City\" TEXT, \n\t\"Height\" INTEGER, \n\t\"Stories\" INTEGER, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in buildings and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Torre Mitikah, Residencial Vidalta Torre Altaire 2, Reforma 90\nStories : 67, 100, 20\n*/\n/*\nColumns in buildings and all categories for low cardinality columns :\nCity : Monterrey, Mexico City\nHeight : 330, 300, 150, 100, 210, 200, 50, 220, 73\nStatus : on-hold, under construction, proposed\n*/\n \nCREATE TABLE \"Plays_Games\" (\n\t\"StuID\" INTEGER, \n\t\"GameID\" INTEGER, \n\t\"Hours_Played\" INTEGER, \n\tFOREIGN KEY(\"GameID\") REFERENCES \"Video_Games\" (\"GameID\"), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/*\nColumns in Plays_Games and all categories for low cardinality columns :\nStuID : 1007, 1008, 1032, 1010, 1001\nGameID : 1, 2, 5, 4, 6, 3\nHours_Played : 1, 100, 10, 1000, 50, 47, 15, 1337, 35\n*/\n \nCREATE TABLE \"Movie\" (\n\t\"mID\" INTEGER, \n\ttitle TEXT, \n\tyear INTEGER, \n\tdirector TEXT, \n\tPRIMARY KEY (\"mID\")\n)\n/*\nColumns in Movie and all categories for low cardinality columns :\nmID : 108, 106, 103, 102, 101, 104, 107, 105\ntitle : Avatar, Raiders of the Lost Ark, Titanic, E.T., Gone with the Wind, Snow White, Star Wars, The Sound of Music\nyear : 1937, 2009, 1982, 1997, 1939, 1965, 1981, 1977\ndirector : Robert Wise, James Cameron, George Lucas, Victor Fleming, Steven Spielberg, None\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Assets\" (\n\tasset_id INTEGER, \n\tmaintenance_contract_id INTEGER NOT NULL, \n\tsupplier_company_id INTEGER NOT NULL, \n\tasset_details VARCHAR(255), \n\tasset_make VARCHAR(20), \n\tasset_model VARCHAR(20), \n\tasset_acquired_date DATETIME, \n\tasset_disposed_date DATETIME, \n\tother_asset_details VARCHAR(255), \n\tPRIMARY KEY (asset_id), \n\tFOREIGN KEY(supplier_company_id) REFERENCES \"Third_Party_Companies\" (company_id), \n\tFOREIGN KEY(maintenance_contract_id) REFERENCES \"Maintenance_Contracts\" (maintenance_contract_id)\n)\n/*\nColumns in Assets and 3 examples in each column for high cardinality columns :\nasset_id : 1, 13, 11\nasset_details : dell laptop3, system3, system1\nasset_model : 63 ok, 35 xt, 91 ub\nasset_acquired_date : 2017-06-12 17:37:19, 2017-12-25 00:31:27, 2017-10-19 02:54:52\nasset_disposed_date : 2018-03-17 00:51:14, 2018-02-27 23:12:03, 2018-03-08 20:50:40\n*/\n/*\nColumns in Assets and all categories for low cardinality columns :\nmaintenance_contract_id : 13, 11, 10, 2, 7, 8, 6, 14, 12, 15\nsupplier_company_id : 1, 13, 11, 2, 5, 7, 8, 6, 12, 14\nasset_make : FR, PT, IT, IN, GB, DE, CN, IE, RU\nother_asset_details : None, Bad condition\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/*\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/*\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n*/\n/*\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n*/\n" }, { "role": "user", "content": "What is the average length in feet of the bridges?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: bridge.\nFrom these tables, I'll be using the following columns: length_feet.\nThe SQL query I'll be generating is:\nSELECT avg(length_feet) FROM bridge" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Accounts\" (\n\taccount_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\taccount_name VARCHAR(50), \n\tother_account_details VARCHAR(255), \n\tPRIMARY KEY (account_id)\n)\n/*\nColumns in Accounts and 3 examples in each column for high cardinality columns :\naccount_id : 1, 13, 11\naccount_name : 866, 725, 858\n*/\n/*\nColumns in Accounts and all categories for low cardinality columns :\ncustomer_id : 13, 2, 8, 4, 6, 12, 14, 10, 9\nother_account_details : VIP, Regular\n*/\n \nCREATE TABLE \"Settlements\" (\n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER, \n\t\"Effective_Date\" DATE, \n\t\"Settlement_Amount\" REAL, \n\tPRIMARY KEY (\"Settlement_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claims\" (\"Claim_ID\"), \n\tUNIQUE (\"Settlement_ID\")\n)\n/*\nColumns in Settlements and all categories for low cardinality columns :\nSettlement_ID : 616, 543, 205, 544, 628, 393, 161, 208, 176, 604\nClaim_ID : 428, 309, 717, 145, 228, 311, 360, 134, 641, 604\nEffective_Date : 2009-11-20, 1978-09-09, 1973-10-27, 1971-06-29, 1995-04-02, 2006-04-19, 2014-12-09, 2001-07-02, 2003-12-28, 1972-03-02\nSettlement_Amount : 8013.95, 8827.06, 9164.1, 2138.96, 2722.67, 1721.17, 1588.45, 9814.39, 3101.3, 6451.65\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE roller_coaster (\n\t\"Roller_Coaster_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Park\" TEXT, \n\t\"Country_ID\" INTEGER, \n\t\"Length\" REAL, \n\t\"Height\" REAL, \n\t\"Speed\" TEXT, \n\t\"Opened\" TEXT, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (\"Roller_Coaster_ID\"), \n\tFOREIGN KEY(\"Country_ID\") REFERENCES country (\"Country_ID\")\n)\n/*\nColumns in roller_coaster and all categories for low cardinality columns :\nRoller_Coaster_ID : 1, 2, 5, 4, 6, 3\nName : The Voyage, Twister, Boardwalk Bullet, Hades 360, Dauling Dragon, Ravine Flyer II\nPark : Waldameer, Happy Valley, Mt. Olympus, Gröna Lund, Kemah Boardwalk, Holiday World\nCountry_ID : 1, 2, 3\nLength : 6442.0, 4726.0, 3236.0, 1574.0, 2900.0, 3914.0\nHeight : 96.0, 105.0, 136.0, 50.0, 120.0, 163.0\nSpeed : 67, 55, 37.9, 70, 57, 51\nOpened : May 14, 2005, 2012, August 31, 2007, 2011, May 6, 2006, May 17, 2008\nStatus : Operating\n*/\n \nCREATE TABLE playlists (\n\tid INTEGER, \n\tname VARCHAR(120), \n\tPRIMARY KEY (id)\n)\n/*\nColumns in playlists and 3 examples in each column for high cardinality columns :\nid : 1, 16, 13\nname : Heavy Metal Classic, 90’s Music, Classical 101 - Deep Cuts\n*/\n\n \nCREATE TABLE competition (\n\t\"Competition_ID\" INTEGER, \n\t\"Year\" REAL, \n\t\"Competition_type\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\")\n)\n/*\nColumns in competition and 3 examples in each column for high cardinality columns :\nCompetition_ID : 1, 11, 2\n*/\n/*\nColumns in competition and all categories for low cardinality columns :\nYear : 2006.0, 2007.0\nCompetition_type : Tournament, Friendly\nCountry : Italy, Slovenia, Spain, Australia, Russia, Ireland\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Customers_Cards\" (\n\tcard_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tcard_type_code VARCHAR(15) NOT NULL, \n\tcard_number VARCHAR(80), \n\tdate_valid_from DATETIME, \n\tdate_valid_to DATETIME, \n\tother_card_details VARCHAR(255), \n\tPRIMARY KEY (card_id)\n)\n/*\nColumns in Customers_Cards and 3 examples in each column for high cardinality columns :\ncard_id : 1, 13, 11\ncustomer_id : 3, 13, 10\ncard_number : 4560596484842, 4716674779726, 348237249146948\ndate_valid_from : 2013-05-23 07:55:36, 2012-05-22 02:05:41, 2013-11-17 02:58:22\ndate_valid_to : 2018-03-14 14:00:07, 2018-03-12 02:16:45, 2018-03-24 00:38:54\nother_card_details : 6011771512810699, 4916493714393, 5428692691195935\n*/\n/*\nColumns in Customers_Cards and all categories for low cardinality columns :\ncard_type_code : Credit, Debit\n*/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Founded\" REAL, \n\t\"Denomination\" TEXT, \n\t\"Boys_or_Girls\" TEXT, \n\t\"Day_or_Boarding\" TEXT, \n\t\"Year_Entered_Competition\" REAL, \n\t\"School_Colors\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nSchool : St Aloysius' College, Cranbrook School, Waverley College, Knox Grammar School, Barker College, Trinity Grammar School\nLocation : Hornsby, Summer Hill, Waverley, Bellevue Hill, Milsons Point, Wahroonga\nEnrollment : 1000.0, 1850.0, 2200.0, 1200.0, 2300.0, 1430.0\nFounded : 1918.0, 1924.0, 1913.0, 1879.0, 1903.0, 1890.0\nDenomination : Catholic, Uniting Church, Anglican\nBoys_or_Girls : Boys only to Yr 9 Co-ed Year 10 to 12, Boys\nDay_or_Boarding : Day, Day & Boarding\nYear_Entered_Competition : 1944.0, 1929.0\nSchool_Colors : Royal Blue and Gold, Black & Blue, Red, White & Blue, Red & Blue, Green and White\n*/\n \nCREATE TABLE \"Financial_Transactions\" (\n\ttransaction_id INTEGER NOT NULL, \n\taccount_id INTEGER NOT NULL, \n\tinvoice_number INTEGER, \n\ttransaction_type VARCHAR(15) NOT NULL, \n\ttransaction_date DATETIME, \n\ttransaction_amount DECIMAL(19, 4), \n\ttransaction_comment VARCHAR(255), \n\tother_transaction_details VARCHAR(255), \n\tFOREIGN KEY(account_id) REFERENCES \"Accounts\" (account_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number)\n)\n/*\nColumns in Financial_Transactions and 3 examples in each column for high cardinality columns :\ntransaction_id : 1, 13, 11\ntransaction_date : 2018-03-10 13:46:48, 2018-03-11 21:57:47, 2018-03-13 03:51:59\ntransaction_amount : 540.7300, 368.4600, 1214.2200\n*/\n/*\nColumns in Financial_Transactions and all categories for low cardinality columns :\naccount_id : 13, 11, 8, 4, 6, 14, 12, 9\ninvoice_number : 1, 3, 13, 2, 5, 6, 14, 12, 15\ntransaction_type : Refund, Payment\ntransaction_comment : None\nother_transaction_details : None\n*/\n \nCREATE TABLE \"Catalog_Structure\" (\n\tcatalog_level_number INTEGER, \n\tcatalog_id INTEGER NOT NULL, \n\tcatalog_level_name VARCHAR(50), \n\tPRIMARY KEY (catalog_level_number), \n\tFOREIGN KEY(catalog_id) REFERENCES \"Catalogs\" (catalog_id)\n)\n/*\nColumns in Catalog_Structure and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\ncatalog_id : 1, 8, 2\ncatalog_level_name : Product, Category, Sub-Category\n*/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tname TEXT, \n\tlat NUMERIC, \n\tlong NUMERIC, \n\tdock_count INTEGER, \n\tcity TEXT, \n\tinstallation_date TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 56, 65, 75\nname : Howard at 2nd, 2nd at Folsom, Market at 10th\nlat : 37.7954250000, 37.7863050000, 37.3297320000\nlong : -122.2362340000, -122.2274240000, -122.4182350000\ninstallation_date : 8/20/2013, 1/22/2014, 8/15/2013\n*/\n/*\nColumns in station and all categories for low cardinality columns :\ndock_count : 11, 25, 23, 19, 15, 27\ncity : San Jose, Mountain View, Palo Alto, Redwood City, San Francisco\n*/\n \nCREATE TABLE \"Project_Outcomes\" (\n\tproject_id INTEGER NOT NULL, \n\toutcome_code VARCHAR(10) NOT NULL, \n\toutcome_details VARCHAR(255), \n\tFOREIGN KEY(outcome_code) REFERENCES \"Research_Outcomes\" (outcome_code), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/*\nColumns in Project_Outcomes and all categories for low cardinality columns :\nproject_id : 13, 11, 5, 7, 4, 6, 14, 3, 12, 9\noutcome_code : Patent, Paper\noutcome_details : None\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/*\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n*/\n" }, { "role": "user", "content": "What are the names and year of construction for the mills of 'Grondzeiler' type?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: mill.\nFrom these tables, I'll be using the following columns: name, built_year.\nThe SQL query I'll be generating is:\nSELECT name , built_year FROM mill WHERE TYPE = 'Grondzeiler'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE media_types (\n\tid INTEGER, \n\tname VARCHAR(120), \n\tPRIMARY KEY (id)\n)\n/*\nColumns in media_types and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Protected AAC audio file, Protected MPEG-4 video file, Purchased AAC audio file, AAC audio file, MPEG audio file\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE train_station (\n\t\"Train_ID\" INTEGER, \n\t\"Station_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\", \"Station_ID\"), \n\tFOREIGN KEY(\"Train_ID\") REFERENCES train (\"Train_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES station (\"Station_ID\")\n)\n/*\nColumns in train_station and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\n*/\n/*\nColumns in train_station and all categories for low cardinality columns :\nStation_ID : 1, 2, 5, 8, 3, 10, 9\n*/\n \nCREATE TABLE \"Complaints\" (\n\tcomplaint_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tcomplaint_outcome_code VARCHAR(20) NOT NULL, \n\tcomplaint_status_code VARCHAR(20) NOT NULL, \n\tcomplaint_type_code VARCHAR(20) NOT NULL, \n\tdate_complaint_raised DATETIME, \n\tdate_complaint_closed DATETIME, \n\tstaff_id INTEGER NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/*\nColumns in Complaints and 3 examples in each column for high cardinality columns :\ncomplaint_id : 1, 11, 2\n*/\n/*\nColumns in Complaints and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\ncustomer_id : 120, 114, 113, 116, 117, 115, 118\ncomplaint_outcome_code : OK\ncomplaint_status_code : Open, Closed, New\ncomplaint_type_code : Product Failure, Product Unusable\ndate_complaint_raised : 2006-10-29 07:08:46, 2002-07-18 10:59:35, 1977-08-06 00:31:19, 1987-07-11 14:40:30, 1973-02-10 22:55:56, 2007-10-14 21:50:43\ndate_complaint_closed : 2013-09-14 02:59:10, 1975-10-11 05:54:30, 1970-10-14 00:57:25, 1976-04-19 11:03:06, 1995-09-11 14:48:46, 2000-08-17 17:02:48\nstaff_id : 120, 114, 116, 117, 115, 118\n*/\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/*\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n*/\n \nCREATE TABLE \"Video_Games\" (\n\t\"GameID\" INTEGER, \n\t\"GName\" VARCHAR(40), \n\t\"GType\" VARCHAR(40), \n\tPRIMARY KEY (\"GameID\")\n)\n/*\nColumns in Video_Games and all categories for low cardinality columns :\nGameID : 1, 2, 5, 4, 6, 3\nGName : Call of Destiny, Grand Term Assignment, The Vanishing of Eric Calder, Europe is the Universe, Works of Widenius, RNG Stone\nGType : Role-playing game, Collectible card game, Frist-person shooter, Walking Simulator, Grand strategy, Massively multiplayer online game\n*/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/*\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n*/\n \nCREATE TABLE \"Accounts\" (\n\taccount_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tdate_account_opened DATETIME, \n\taccount_name VARCHAR(50), \n\tother_account_details VARCHAR(255), \n\tPRIMARY KEY (account_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Accounts and 3 examples in each column for high cardinality columns :\naccount_id : 1, 13, 11\ndate_account_opened : 2016-07-30 22:22:24, 2016-04-25 21:49:17, 2017-05-29 16:45:17\naccount_name : 601, 398, 900\n*/\n/*\nColumns in Accounts and all categories for low cardinality columns :\ncustomer_id : 13, 8, 6, 12, 3, 15, 9\nother_account_details : VIP, Regular\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, *BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n*/\n/*\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE manufacturer (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Open_Year\" REAL, \n\t\"Name\" TEXT, \n\t\"Num_of_Factories\" INTEGER, \n\t\"Num_of_Shops\" INTEGER, \n\tPRIMARY KEY (\"Manufacturer_ID\")\n)\n/*\nColumns in manufacturer and all categories for low cardinality columns :\nManufacturer_ID : 1, 2, 5, 7, 4, 6, 3\nOpen_Year : 2001.0, 2008.0, 2000.0, 1980.0, 1992.0, 1991.0, 1990.0\nName : Tomorrow, Chevrolet, Chevrolet House, Jiaju, Ford Make, IKEA, Dodge\nNum_of_Factories : 1, 38, 36, 21, 12, 3\nNum_of_Shops : 2, 7, 8, 24, 4, 19, 35\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Documents_with_Expenses\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Budget_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Budget_Type_Code\") REFERENCES \"Ref_Budget_Codes\" (\"Budget_Type_Code\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/*\nColumns in Documents_with_Expenses and all categories for low cardinality columns :\nDocument_ID : 300, 240, 309, 226, 367, 371, 383, 227, 192, 57\nBudget_Type_Code : GV, SF, ORG\nDocument_Details : government, safety, organization\n*/\n \nCREATE TABLE \"Investors\" (\n\tinvestor_id INTEGER, \n\t\"Investor_details\" VARCHAR(255), \n\tPRIMARY KEY (investor_id)\n)\n/*\nColumns in Investors and 3 examples in each column for high cardinality columns :\ninvestor_id : 17, 9, 16\nInvestor_details : d, t, b\n*/\n\n \nCREATE TABLE files (\n\tf_id NUMERIC(10) NOT NULL, \n\tartist_name TEXT(50), \n\tfile_size TEXT(20), \n\tduration TEXT(20), \n\tformats TEXT(20), \n\tPRIMARY KEY (f_id), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE\n)\n/*\nColumns in files and all categories for low cardinality columns :\nf_id : 1.0000000000, 5.0000000000, 6.0000000000, 3.0000000000, 2.0000000000, 4.0000000000\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\nfile_size : 4.58 MB, 5.10 MB, 4.10 MB, 3.69 MB, 3.78 MB, 4.12 MB\nduration : 4:30, 5:23, 2:56, 4:34, 3:45, 4:12\nformats : mp3, mp4\n*/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\taddress_content VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tother_address_details VARCHAR(255), \n\tPRIMARY KEY (address_id)\n)\n/*\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\naddress_content : 92865 Margaretta Streets Suite 467, 78614 Maybell Alley Suite 057, 9443 Boyle Route Suite 857\ncity : South Meghanview, South Bellaland, Gleasonmouth\nzip_postcode : 721, 255, 416\nstate_province_county : RhodeIsland, Arizona, Mississippi\n*/\n/*\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\nother_address_details : None\n*/\n \nCREATE TABLE \"CHECKING\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/*\nColumns in CHECKING and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nbalance : 3000.0, 10000.0, 2000.0, 7.0, 7000.0, 77.0\n*/\n \nCREATE TABLE event (\n\t\"Event_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\t\"Event_Attendance\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\")\n)\n/*\nColumns in event and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 4, 3\nDate : 9 April 2014, 7 October 2010, 11 October 2007, 13 October 2008, 20 June 2018\nVenue : Motagua, Platense, Hispano, Victoria, Marathon\nName : Global Awarding, Public Debating, Special Exhibition, Government Hearing, Olympia Games Openning\nEvent_Attendance : 369, 1675, 2356, 6650, 225\n*/\n" }, { "role": "user", "content": "What are the distinct names and nationalities of the architects who have ever built a mill?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: architect, mill.\nFrom these tables, I'll be using the following columns: architect.name, architect.nationality, architect.id, T2.architect_id.\nThe SQL query I'll be generating is:\nSELECT DISTINCT T1.name , T1.nationality FROM architect AS T1 JOIN mill AS t2 ON T1.id = T2.architect_id" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"First_Notification_of_Loss\" (\n\t\"FNOL_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Service_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"FNOL_ID\"), \n\tFOREIGN KEY(\"Service_ID\") REFERENCES \"Services\" (\"Service_ID\"), \n\tFOREIGN KEY(\"Customer_ID\", \"Policy_ID\") REFERENCES \"Customers_Policies\" (\"Customer_ID\", \"Policy_ID\"), \n\tUNIQUE (\"FNOL_ID\")\n)\n/*\nColumns in First_Notification_of_Loss and all categories for low cardinality columns :\nFNOL_ID : 1611, 4226, 2543, 4525, 1722, 4323, 532\nCustomer_ID : 582, 892, 826, 214, 996\nPolicy_ID : 586, 630, 257, 927, 366, 879, 993\nService_ID : 1, 9, 4, 6\n*/\n \nCREATE TABLE airport_aircraft (\n\t\"ID\" INTEGER, \n\t\"Airport_ID\" INTEGER, \n\t\"Aircraft_ID\" INTEGER, \n\tPRIMARY KEY (\"Airport_ID\", \"Aircraft_ID\"), \n\tFOREIGN KEY(\"Aircraft_ID\") REFERENCES aircraft (\"Aircraft_ID\"), \n\tFOREIGN KEY(\"Airport_ID\") REFERENCES airport (\"Airport_ID\")\n)\n/*\nColumns in airport_aircraft and all categories for low cardinality columns :\nID : 1, 2, 4, 3\nAirport_ID : 1, 9, 2, 6\nAircraft_ID : 1, 2, 5, 3\n*/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Founded\" REAL, \n\t\"Denomination\" TEXT, \n\t\"Boys_or_Girls\" TEXT, \n\t\"Day_or_Boarding\" TEXT, \n\t\"Year_Entered_Competition\" REAL, \n\t\"School_Colors\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nSchool : St Aloysius' College, Cranbrook School, Waverley College, Knox Grammar School, Barker College, Trinity Grammar School\nLocation : Hornsby, Summer Hill, Waverley, Bellevue Hill, Milsons Point, Wahroonga\nEnrollment : 1000.0, 1850.0, 2200.0, 1200.0, 2300.0, 1430.0\nFounded : 1918.0, 1924.0, 1913.0, 1879.0, 1903.0, 1890.0\nDenomination : Catholic, Uniting Church, Anglican\nBoys_or_Girls : Boys only to Yr 9 Co-ed Year 10 to 12, Boys\nDay_or_Boarding : Day, Day & Boarding\nYear_Entered_Competition : 1944.0, 1929.0\nSchool_Colors : Royal Blue and Gold, Black & Blue, Red, White & Blue, Red & Blue, Green and White\n*/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/*\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"SAVINGS\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/*\nColumns in SAVINGS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 4, 6, 3\nbalance : 80000.0, 230000.0, 999999999.0, 60.0, 240.0, 200000.0\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Parties_in_Events\" (\n\t\"Party_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Role_Code\" CHAR(15), \n\tPRIMARY KEY (\"Party_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES \"Parties\" (\"Party_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/*\nColumns in Parties_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 1, 13, 15\n*/\n/*\nColumns in Parties_in_Events and all categories for low cardinality columns :\nParty_ID : 5, 4, 6, 3, 9\nRole_Code : Organizer, Participant\n*/\n \nCREATE TABLE manufacturer (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Open_Year\" REAL, \n\t\"Name\" TEXT, \n\t\"Num_of_Factories\" INTEGER, \n\t\"Num_of_Shops\" INTEGER, \n\tPRIMARY KEY (\"Manufacturer_ID\")\n)\n/*\nColumns in manufacturer and all categories for low cardinality columns :\nManufacturer_ID : 1, 2, 5, 7, 4, 6, 3\nOpen_Year : 2001.0, 2008.0, 2000.0, 1980.0, 1992.0, 1991.0, 1990.0\nName : Tomorrow, Chevrolet, Chevrolet House, Jiaju, Ford Make, IKEA, Dodge\nNum_of_Factories : 1, 38, 36, 21, 12, 3\nNum_of_Shops : 2, 7, 8, 24, 4, 19, 35\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE appellations (\n\t\"No\" INTEGER, \n\t\"Appelation\" TEXT, \n\t\"County\" TEXT, \n\t\"State\" TEXT, \n\t\"Area\" TEXT, \n\t\"isAVA\" TEXT, \n\tPRIMARY KEY (\"No\"), \n\tUNIQUE (\"Appelation\")\n)\n/*\nColumns in appellations and 3 examples in each column for high cardinality columns :\nNo : 53, 56, 49\nAppelation : Anderson Valley, Fiddletown, Mendocino County\nCounty : Monterey, Solano, Santa Barbara\n*/\n/*\nColumns in appellations and all categories for low cardinality columns :\nState : California\nArea : Sierra Foothills, Central Valley, North Coast, Central Coast, N/A, California, Santa Cruz Mountains\nisAVA : Yes, No\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Birth_Date\" TEXT, \n\t\"Birth_Place\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 4, 6, 3\nName : Ty Conklin, Jake Gardiner, Al Montoya, Mark Fayne, Jack Campbell, Cam Fowler\nHeight : 215.0, 182.0, 195.0, 205.0, 192.0, 196.0\nWeight : 89.0, 100.0, 90.0, 102.0, 80.0, 92.0\nBirth_Date : December 5, 1991, May 5, 1987, July 4, 1990, February 13, 1985, March 30, 1976, January 1, 1992\nBirth_Place : Farmington Hills, Michigan, Anchorage, Alaska, Glenview, Illinois, Nashua, New Hampshire, Minnetonka, Minnesota, Port Huron, Michigan\n*/\n \nCREATE TABLE \"Teachers\" (\n\tteacher_id INTEGER, \n\taddress_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(80), \n\tmiddle_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tgender VARCHAR(1), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (teacher_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/*\nColumns in Teachers and 3 examples in each column for high cardinality columns :\nteacher_id : 1, 13, 11\naddress_id : 16, 13, 10\nfirst_name : Camren, Trystan, Alvis\nmiddle_name : Keanu, Michel, Kailyn\nlast_name : Goldner, Becker, Heller\ncell_mobile_number : 952.821.3392, 07928511102, 017.636.7409\nemail_address : hilll.kitty@example.com, paula.abbott@example.org, kozey.adeline@example.org\n*/\n/*\nColumns in Teachers and all categories for low cardinality columns :\ngender : 1, 0\nother_details : None, Dean\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"View_Product_Availability\" (\n\tproduct_id INTEGER NOT NULL, \n\tbooking_id INTEGER NOT NULL, \n\tstatus_date DATETIME, \n\tavailable_yn VARCHAR(1), \n\tPRIMARY KEY (status_date), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/*\nColumns in View_Product_Availability and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 3\nbooking_id : 11, 5\nstatus_date : 2018-03-18 05:25:55, 2018-03-25 10:20:15, 2018-03-21 15:20:32, 2018-03-22 00:16:58\navailable_yn : 1, 0\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Birth_Date\" TEXT, \n\t\"Birth_Place\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 4, 6, 3\nName : Ty Conklin, Jake Gardiner, Al Montoya, Mark Fayne, Jack Campbell, Cam Fowler\nHeight : 215.0, 182.0, 195.0, 205.0, 192.0, 196.0\nWeight : 89.0, 100.0, 90.0, 102.0, 80.0, 92.0\nBirth_Date : December 5, 1991, May 5, 1987, July 4, 1990, February 13, 1985, March 30, 1976, January 1, 1992\nBirth_Place : Farmington Hills, Michigan, Anchorage, Alaska, Glenview, Illinois, Nashua, New Hampshire, Minnetonka, Minnesota, Port Huron, Michigan\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Sex\" TEXT, \n\t\"Name\" TEXT, \n\t\"Date_of_Birth\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nSex : F, M\nName : Vincent Montméat, Frantz Granvorka, Loïc De Kergret, Philippe Barça-Cysique, Guillaume Samica, Stéphane Antiga, Dominique Daquin, Laurent Capet, Hubert Henno\nDate_of_Birth : 20.08.1970, 10.03.1976, 05.05.1972, 28.09.1981, 22.04.1977, 01.09.1977, 10.11.1972, 06.10.1976, 03.02.1976\nHeight : 196.0, 195.0, 197.0, 188.0, 193.0, 200.0, 202.0, 194.0\nWeight : 89.0, 82.0, 85.0, 88.0, 90.0, 92.0, 83.0, 94.0\n*/\n" }, { "role": "user", "content": "What are the names of the mills which are not located in 'Donceel'?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: mill.\nFrom these tables, I'll be using the following columns: name.\nThe SQL query I'll be generating is:\nSELECT name FROM mill WHERE LOCATION != 'Donceel'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"Characteristics\" (\n\tcharacteristic_id INTEGER, \n\tcharacteristic_type_code VARCHAR(15) NOT NULL, \n\tcharacteristic_data_type VARCHAR(10), \n\tcharacteristic_name VARCHAR(80), \n\tother_characteristic_details VARCHAR(255), \n\tPRIMARY KEY (characteristic_id), \n\tFOREIGN KEY(characteristic_type_code) REFERENCES \"Ref_Characteristic_Types\" (characteristic_type_code)\n)\n/*\nColumns in Characteristics and 3 examples in each column for high cardinality columns :\ncharacteristic_id : 1, 13, 11\ncharacteristic_data_type : placeat, dolores, mollitia\n*/\n/*\nColumns in Characteristics and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_name : hot, error, cool, fast, warm, slow\nother_characteristic_details : None\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Order_Items\" (\n\titem_id INTEGER NOT NULL, \n\torder_item_status_code VARCHAR(15) NOT NULL, \n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\titem_status_code VARCHAR(15), \n\titem_delivered_datetime DATETIME, \n\titem_order_quantity VARCHAR(80), \n\tFOREIGN KEY(order_id) REFERENCES \"Customer_Orders\" (order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\nitem_id : 1, 13, 11\nitem_delivered_datetime : 2018-03-16 15:58:27, 2018-03-04 18:19:12, 2018-03-12 20:01:38\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\norder_item_status_code : Paid, Delivered, Cancelled\norder_id : 13, 11, 2, 15, 7, 8, 6, 14, 10\nproduct_id : 1, 13, 11, 5, 7, 6, 14, 3, 10, 9\nitem_status_code : good\nitem_order_quantity : 1, 2, 5, 7, 4, 6, 3, 9\n*/\n \nCREATE TABLE competition_result (\n\t\"Competition_ID\" INTEGER, \n\t\"Club_ID_1\" INTEGER, \n\t\"Club_ID_2\" INTEGER, \n\t\"Score\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\", \"Club_ID_1\", \"Club_ID_2\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES competition (\"Competition_ID\"), \n\tFOREIGN KEY(\"Club_ID_2\") REFERENCES club (\"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID_1\") REFERENCES club (\"Club_ID\")\n)\n/*\nColumns in competition_result and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 6, 10\nClub_ID_1 : 1, 4, 3\nClub_ID_2 : 2, 4, 6\nScore : 11:10, 10:11, 10:3, 13:10, 12:9, 25:2\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Card_Number\" TEXT, \n\t\"Name\" TEXT, \n\t\"Hometown\" TEXT, \n\t\"Level\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nCard_Number : LT98, RE95, LCB7, FS10, MLB4, SLB51, RCB32, OLB56, LE99, RT91\nName : Trevard Lindley, Jeremy Jarmon, Corey Peters, David Jones, Myron Pryor, Matt Lentz, Johnny Williams, Ventrell Jenkins, Braxton Kelley, Micah Johnson\nHometown : Jacksonville, Florida, Collierville, Tennessee, Columbia, South Carolina, Red Jacket, West Virginia, Fort Campbell, Kentucky, LaGrange, Georgia, Louisville, Kentucky, Simpsonville, South Carolina, Hiram, Georgia\nLevel : 2, 4, 6\n*/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/*\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Train_Num\" TEXT, \n\t\"Name\" TEXT, \n\t\"From\" TEXT, \n\t\"Arrival\" TEXT, \n\t\"Railway_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/*\nColumns in train and all categories for low cardinality columns :\nTrain_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nTrain_Num : 57136, 57135, 16032, 12140, 51195, 12139, 16031, 11401, 16094\nName : Wardha-Ballarshah Pass, Nagpur-Kazipet Pass, Ballarshah-Mumbai Pass, Nandigram Exp, Lucknow-Chennai Exp, Sewagram Exp, Andaman Exp, Kazipet-Nagpur Pass\nFrom : Lucknow, Ballarshah, Nagpur, Kazipet, Mumbai CST, Jammu Tawi, Wardha, Chennai\nArrival : 23:39, 08:54, 23:44, 05:09, 09:48, 13:28, 13:04, 09:08\nRailway_ID : 1, 2, 5, 7, 3, 10, 9\n*/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n*/\n \nCREATE TABLE \"Addresses\" (\n\t\"Address_ID\" VARCHAR(100) NOT NULL, \n\t\"Line_1\" VARCHAR(255), \n\t\"Line_2\" VARCHAR(255), \n\t\"City_Town\" VARCHAR(255), \n\t\"State_County\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Address_ID\"), \n\tUNIQUE (\"Address_ID\")\n)\n/*\nColumns in Addresses and 3 examples in each column for high cardinality columns :\nAddress_ID : 98, 74, 192\nLine_1 : 77667 Nathan Union Apt. 606, 8835 Boehm Greens, 2893 Jenkins Station Suite 815\nLine_2 : Suite 226, Apt. 861, Suite 271\nCity_Town : New Jaquelinmouth, Port Maximeview, South Eugenia\nState_County : Pennsylvania, Delaware, SouthDakota\n*/\n/*\nColumns in Addresses and all categories for low cardinality columns :\nOther_Details : None\n*/\n \nCREATE TABLE \"Problem_Status_Codes\" (\n\tproblem_status_code VARCHAR(20), \n\tproblem_status_description VARCHAR(80), \n\tPRIMARY KEY (problem_status_code)\n)\n/*\nColumns in Problem_Status_Codes and all categories for low cardinality columns :\nproblem_status_code : Solved, Reported\nproblem_status_description : Solved, Reported\n*/\n \nCREATE TABLE list (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Grade\" INTEGER, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/*\nColumns in list and 3 examples in each column for high cardinality columns :\nLastName : HOUTCHENS, GELL, FLACHS\nFirstName : RAY, EMILE, PATRINA\nClassroom : 109, 110, 106\n*/\n/*\nColumns in list and all categories for low cardinality columns :\nGrade : 1, 2, 5, 4, 6, 3, 0\n*/\n \nCREATE TABLE mountain (\n\t\"Mountain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Mountain_ID\")\n)\n/*\nColumns in mountain and all categories for low cardinality columns :\nMountain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ngaliema / Mt Stanley (Margherita Pk), Mount Kenya (Lenana), Kibo (Uhuru Pk), Ngaliema / Mt Stanley (Savoia Pk), Mount Kenya (Batian), Duwoni / Mt Speke (Vittorio Emanuele Pk), Mawenzi (Hans Meyer Pk)\nHeight : 5109.0, 5199.0, 5895.0, 4890.0, 4985.0, 4977.0, 5148.0\nProminence : 720.0, 850.0, 3951.0, 3825.0, 130.0, 5885.0, 110.0\nRange : Kilimanjaro, Mount Kenya, Rwenzori\nCountry : DR Congo Uganda, Uganda, Tanzania, Kenya\n*/\n \nCREATE TABLE teachers (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/*\nColumns in teachers and 3 examples in each column for high cardinality columns :\nLastName : MOYER, NIBLER, ONDERSMA\nFirstName : CHARMAINE, JEROME, KIRK\nClassroom : 109, 108, 106\n*/\n\n \nCREATE TABLE head (\n\t\"head_ID\" INTEGER, \n\tname TEXT, \n\tborn_state TEXT, \n\tage REAL, \n\tPRIMARY KEY (\"head_ID\")\n)\n/*\nColumns in head and all categories for low cardinality columns :\nhead_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nname : Jeff Maggert, Pádraig Harrington, Billy Mayfair, K. J. Choi, Dudley Hart, Sergio García, Stewart Cink, Tiger Woods, Nick Faldo, Franklin Langham\nborn_state : Delaware, Connecticut, Alabama, California, Florida\nage : 69.0, 67.0, 68.0, 53.0, 56.0, 52.0, 50.0, 43.0\n*/\n \nCREATE TABLE stock (\n\t\"Shop_ID\" INTEGER, \n\t\"Device_ID\" INTEGER, \n\t\"Quantity\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\", \"Device_ID\"), \n\tFOREIGN KEY(\"Device_ID\") REFERENCES device (\"Device_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in stock and all categories for low cardinality columns :\nShop_ID : 1, 11, 2, 4, 3, 9\nDevice_ID : 4, 6\nQuantity : 110, 56, 124, 100, 200, 112, 134, 51\n*/\n \nCREATE TABLE \"Rating\" (\n\t\"rID\" INTEGER, \n\t\"mID\" INTEGER, \n\tstars INTEGER, \n\t\"ratingDate\" DATE, \n\tFOREIGN KEY(\"mID\") REFERENCES \"Movie\" (\"mID\"), \n\tFOREIGN KEY(\"rID\") REFERENCES \"Reviewer\" (\"rID\")\n)\n/*\nColumns in Rating and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nmID : 108, 106, 103, 101, 104, 107\nstars : 2, 4, 5, 3\nratingDate : 2011-01-20, 2011-01-09, 2011-01-30, 2011-01-22, 2011-01-27, 2011-01-19, 2011-01-02, None, 2011-01-12, 2011-01-15\n*/\n" }, { "role": "user", "content": "What are the distinct types of mills that are built by American or Canadian architects?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: mill, architect.\nFrom these tables, I'll be using the following columns: mill.type, mill.architect_id, T2.id, T2.nationality.\nThe SQL query I'll be generating is:\nSELECT DISTINCT T1.type FROM mill AS T1 JOIN architect AS t2 ON T1.architect_id = T2.id WHERE T2.nationality = 'American' OR T2.nationality = 'Canadian'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE useracct (\n\tu_id INTEGER NOT NULL, \n\tname VARCHAR(128) DEFAULT NULL, \n\tPRIMARY KEY (u_id)\n)\n/*\nColumns in useracct and all categories for low cardinality columns :\nu_id : 1, 2, 5, 7, 4, 6, 3\nname : Rosie, Emily, Roxi, Helen, Terry, Mark, Nancy\n*/\n \nCREATE TABLE browser (\n\tid INTEGER, \n\tname TEXT, \n\tmarket_share REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in browser and all categories for low cardinality columns :\nid : 1, 2, 4, 3\nname : Opera, Internet Explorer, Safari, Firefox\nmarket_share : 18.11, 8.54, 28.96, 1.2\n*/\n \nCREATE TABLE \"Financial_Transactions\" (\n\ttransaction_id INTEGER NOT NULL, \n\tprevious_transaction_id INTEGER, \n\taccount_id INTEGER NOT NULL, \n\tcard_id INTEGER NOT NULL, \n\ttransaction_type VARCHAR(15) NOT NULL, \n\ttransaction_date DATETIME, \n\ttransaction_amount DOUBLE, \n\ttransaction_comment VARCHAR(255), \n\tother_transaction_details VARCHAR(255), \n\tFOREIGN KEY(account_id) REFERENCES \"Accounts\" (account_id), \n\tFOREIGN KEY(card_id) REFERENCES \"Customers_Cards\" (card_id)\n)\n/*\nColumns in Financial_Transactions and 3 examples in each column for high cardinality columns :\ntransaction_id : 1, 13, 11\nprevious_transaction_id : 925, 947, 986\naccount_id : 1, 13, 11\ntransaction_date : 2018-03-24 10:39:09, 2018-03-23 21:59:28, 2018-03-24 05:45:57\ntransaction_amount : 486.56, 1336.21, 945.43\n*/\n/*\nColumns in Financial_Transactions and all categories for low cardinality columns :\ncard_id : 1, 11, 2, 5, 7, 4, 6, 12, 3, 9\ntransaction_type : Refund, Payment\ntransaction_comment : None\nother_transaction_details : None\n*/\n \nCREATE TABLE \"Research_Staff\" (\n\tstaff_id INTEGER, \n\temployer_organisation_id INTEGER NOT NULL, \n\tstaff_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(employer_organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/*\nColumns in Research_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_details : aspernatur, dicta, ab\n*/\n/*\nColumns in Research_Staff and all categories for low cardinality columns :\nemployer_organisation_id : 1, 2, 5, 8, 4, 6, 3, 10, 9\n*/\n \nCREATE TABLE \"Regular_Orders\" (\n\tregular_order_id INTEGER, \n\tdistributer_id INTEGER NOT NULL, \n\tPRIMARY KEY (regular_order_id), \n\tFOREIGN KEY(distributer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Regular_Orders and 3 examples in each column for high cardinality columns :\nregular_order_id : 1, 13, 11\n*/\n/*\nColumns in Regular_Orders and all categories for low cardinality columns :\ndistributer_id : 1, 10, 2, 7, 8, 6, 12, 3, 14, 15\n*/\n \nCREATE TABLE \"CLASS\" (\n\t\"CLASS_CODE\" VARCHAR(5), \n\t\"CRS_CODE\" VARCHAR(10), \n\t\"CLASS_SECTION\" VARCHAR(2), \n\t\"CLASS_TIME\" VARCHAR(20), \n\t\"CLASS_ROOM\" VARCHAR(8), \n\t\"PROF_NUM\" INTEGER, \n\tPRIMARY KEY (\"CLASS_CODE\"), \n\tFOREIGN KEY(\"CRS_CODE\") REFERENCES \"COURSE\" (\"CRS_CODE\"), \n\tFOREIGN KEY(\"PROF_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\")\n)\n/*\nColumns in CLASS and 3 examples in each column for high cardinality columns :\nCLASS_CODE : 10013, 10024, 10016\n*/\n/*\nColumns in CLASS and all categories for low cardinality columns :\nCRS_CODE : ACCT-212, QM-362, QM-261, CIS-420, CIS-220, ACCT-211\nCLASS_SECTION : 1, 2, 3\nCLASS_TIME : TTh 2:30-3:45 p.m., MWF 10:00-10:50 a.m., MWF 9:00-9:50 a.m., MWF 8:00-8:50 a.m., W 6:00-8:40 p.m., Th 6:00-8:40 p.m., TTh 1:00-2:15 p.m., MWF 11:00-11:50 a.m.\nCLASS_ROOM : KLR209, KLR211, BUS252, BUS311, KLR200, BUS200\nPROF_NUM : 114, 342, 301, 228, 105, 162\n*/\n \nCREATE TABLE \"Products\" (\n\t\"Product_ID\" INTEGER NOT NULL, \n\t\"Product_Type_Code\" CHAR(15), \n\t\"Product_Name\" VARCHAR(255), \n\t\"Product_Price\" DECIMAL(20, 4), \n\tPRIMARY KEY (\"Product_ID\"), \n\tUNIQUE (\"Product_ID\")\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nProduct_ID : 1, 26, 20\nProduct_Price : 932.2500, 970.7700, 3228.4900\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nProduct_Type_Code : Food, Books, Electronics, Clothes\nProduct_Name : Conference Equipments, Men suits, Dinning, TV Equipments, Trading Policy B, Special Dinning, Business Policy B, Trading Policy, Business Policy\n*/\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/*\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n*/\n \nCREATE TABLE \"Course_Authors_and_Tutors\" (\n\tauthor_id INTEGER, \n\t\"author_tutor_ATB\" VARCHAR(3), \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(40), \n\tpersonal_name VARCHAR(80), \n\tmiddle_name VARCHAR(80), \n\tfamily_name VARCHAR(80), \n\tgender_mf VARCHAR(1), \n\taddress_line_1 VARCHAR(80), \n\tPRIMARY KEY (author_id)\n)\n/*\nColumns in Course_Authors_and_Tutors and 3 examples in each column for high cardinality columns :\nauthor_id : 1, 13, 11\nauthor_tutor_ATB : 388, 782, 159\nlogin_name : heidenreich.ara, qking, fiona77\npassword : 2c196efe8aee23a1b9a7e752fe63029c5879af6f, cdaf6c3483f19e2253659a40a3aab786a3390f78, 120ac8a5744f5b710ecaebbd8dd1633e3e33886e\npersonal_name : Dusty, Cathrine, Shakira\nmiddle_name : Kennith, Ruthie, Joyce\nfamily_name : Treutel, Zboncak, Rowe\naddress_line_1 : 644 Montana Hill Suite 489\nDaijamouth, CA 19587-4254, 139 O'Conner Circles\nVirginieland, KS 23365, 92220 Hellen Skyway Apt. 635\nRennerview, MS 81036\n*/\n/*\nColumns in Course_Authors_and_Tutors and all categories for low cardinality columns :\ngender_mf : 1, 0\n*/\n \nCREATE TABLE train (\n\tid INTEGER, \n\ttrain_number INTEGER, \n\tname TEXT, \n\torigin TEXT, \n\tdestination TEXT, \n\ttime TEXT, \n\tinterval TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in train and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\ntrain_number : 16526, 56700, 56701\ntime : 10:38, 16:59, 11:15\n*/\n/*\nColumns in train and all categories for low cardinality columns :\nname : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\norigin : Quilon, Mumbai, Bangalore, Madurai, Nagercoil, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ndestination : Mumbai, Mangalore, Bangalore, Madurai, Quilon Junction, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ninterval : Daily\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/*\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n*/\n/*\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n*/\n \nCREATE TABLE cinema (\n\t\"Cinema_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Openning_year\" INTEGER, \n\t\"Capacity\" INTEGER, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"Cinema_ID\")\n)\n/*\nColumns in cinema and all categories for low cardinality columns :\nCinema_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Glenmore, Oriel, Codling, Dublin Array, Glenough, Grouse Lodge, Carrowleagh, Gortahile, Mount Callan, Moneypoint\nOpenning_year : 2009, 2013, 2015, 2012, 2011, 2010\nCapacity : 330, 305, 368, 364, 325, 203, 908, 208, 1100, 225\nLocation : County Cork, County Louth, County Laois, County Tipperary, County Clare, County Dublin, County Wicklow\n*/\n \nCREATE TABLE competition (\n\t\"Competition_ID\" INTEGER, \n\t\"Year\" REAL, \n\t\"Competition_type\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\")\n)\n/*\nColumns in competition and 3 examples in each column for high cardinality columns :\nCompetition_ID : 1, 11, 2\n*/\n/*\nColumns in competition and all categories for low cardinality columns :\nYear : 2006.0, 2007.0\nCompetition_type : Tournament, Friendly\nCountry : Italy, Slovenia, Spain, Australia, Russia, Ireland\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Documents\" (\n\tdocument_id INTEGER NOT NULL, \n\tdocument_status_code CHAR(15) NOT NULL, \n\tdocument_type_code CHAR(15) NOT NULL, \n\tshipping_agent_code CHAR(15), \n\treceipt_date DATETIME, \n\treceipt_number VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (document_id), \n\tFOREIGN KEY(document_type_code) REFERENCES \"Ref_Document_Types\" (document_type_code), \n\tFOREIGN KEY(document_status_code) REFERENCES \"Ref_Document_Status\" (document_status_code), \n\tFOREIGN KEY(shipping_agent_code) REFERENCES \"Ref_Shipping_Agents\" (shipping_agent_code)\n)\n/*\nColumns in Documents and 3 examples in each column for high cardinality columns :\ndocument_id : 1, 13, 20\nreceipt_date : 2014-12-25 17:22:44, 2008-04-21 20:42:25, 2015-04-03 09:36:19\nreceipt_number : 79, 114, 69\nother_details : m, q, b\n*/\n/*\nColumns in Documents and all categories for low cardinality columns :\ndocument_status_code : done, overdue, working\ndocument_type_code : Hard Drive, CD, Paper\nshipping_agent_code : FE, UP, US, AL, SH\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Authorship\" (\n\t\"authID\" INTEGER, \n\t\"instID\" INTEGER, \n\t\"paperID\" INTEGER, \n\t\"authOrder\" INTEGER, \n\tPRIMARY KEY (\"authID\", \"instID\", \"paperID\"), \n\tFOREIGN KEY(\"authID\") REFERENCES \"Authors\" (\"authID\"), \n\tFOREIGN KEY(\"instID\") REFERENCES \"Inst\" (\"instID\"), \n\tFOREIGN KEY(\"paperID\") REFERENCES \"Papers\" (\"paperID\")\n)\n/*\nColumns in Authorship and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\n*/\n/*\nColumns in Authorship and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\npaperID : 201, 204, 205, 200, 206, 203, 202\nauthOrder : 1, 2, 3\n*/\n \nCREATE TABLE \"Ref_Attraction_Types\" (\n\t\"Attraction_Type_Code\" CHAR(15) NOT NULL, \n\t\"Attraction_Type_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Attraction_Type_Code\"), \n\tUNIQUE (\"Attraction_Type_Code\")\n)\n/*\nColumns in Ref_Attraction_Types and all categories for low cardinality columns :\nAttraction_Type_Code : 2, 5, 6, 3, 9\nAttraction_Type_Description : park, gallery, adventure, garden, museum\n*/\n" }, { "role": "user", "content": "What are the ids and names of the architects who built at least 3 bridges ?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: architect, bridge.\nFrom these tables, I'll be using the following columns: architect.id, architect.name, bridge.architect_id.\nThe SQL query I'll be generating is:\nSELECT T1.id , T1.name FROM architect AS T1 JOIN bridge AS T2 ON T1.id = T2.architect_id GROUP BY T1.id HAVING count(*) >= 3" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE user_profiles (\n\tuid INTEGER NOT NULL, \n\tname VARCHAR(255) DEFAULT NULL, \n\temail VARCHAR(255) DEFAULT NULL, \n\tpartitionid INTEGER DEFAULT NULL, \n\tfollowers INTEGER DEFAULT NULL, \n\tPRIMARY KEY (uid)\n)\n/*\nColumns in user_profiles and all categories for low cardinality columns :\nuid : 1, 2, 5, 7, 4, 6, 3\nname : Natalie Portman, Mary, Black Widow\n, Tyler Swift, Celine Dion, Iron Man, Susan\nemail : susan@gmail.com\n, ts@superstar.com\n, cd@superstar.com, np@superstar.com, ts@richest.com, bw@superhero.com, Mary@yale.edu\npartitionid : 1, 2, 5, 23, 10\nfollowers : 23927492, 100, 94375428, 35425845, 890, 99999998, 6662425\n*/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n*/\n/*\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE discipline_enrollments (\n\t\"Campus\" INTEGER, \n\t\"Discipline\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Undergraduate\" INTEGER, \n\t\"Graduate\" INTEGER, \n\tPRIMARY KEY (\"Campus\", \"Discipline\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/*\nColumns in discipline_enrollments and 3 examples in each column for high cardinality columns :\nCampus : 1, 13, 11\nDiscipline : 19, 17, 21\nUndergraduate : 986, 65, 815\nGraduate : 56, 377, 187\n*/\n/*\nColumns in discipline_enrollments and all categories for low cardinality columns :\nYear : 2004\n*/\n \nCREATE TABLE exhibition (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Theme\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\t\"Ticket_Price\" REAL, \n\tPRIMARY KEY (\"Exhibition_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in exhibition and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 6, 3\nYear : 2004, 2009, 2005, 2008, 2006, 2007\nTheme : Christmas Tree, Santa Claus and Rudolph the Red-Nosed Reindeer, Summer, Christmas stocking, Spring, Santa Claus\nArtist_ID : 1, 2, 4, 6, 3\nTicket_Price : 19.95, 9.95, 29.95, 14.95, 16.95\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE performance (\n\t\"Performance_ID\" REAL, \n\t\"Date\" TEXT, \n\t\"Host\" TEXT, \n\t\"Location\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Performance_ID\")\n)\n/*\nColumns in performance and all categories for low cardinality columns :\nPerformance_ID : 3.0, 1.0, 2.0, 6.0, 4.0, 5.0\nDate : February 7, February 4, February 2, February 5, February 10, February 11\nHost : Ottawa Senators, New York Rangers, Pittsburgh Penguins, Atlanta Thrashers, Montreal Canadiens, Boston Bruins\nLocation : Madison Square Garden, Scotiabank Place, Verizon Center, TD Garden, Bell Centre\nAttendance : 2173, 1878, 1877, 1820, 1982, 165\n*/\n \nCREATE TABLE browser (\n\tid INTEGER, \n\tname TEXT, \n\tmarket_share REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in browser and all categories for low cardinality columns :\nid : 1, 2, 4, 3\nname : Opera, Internet Explorer, Safari, Firefox\nmarket_share : 18.11, 8.54, 28.96, 1.2\n*/\n \nCREATE TABLE phone_market (\n\t\"Market_ID\" INTEGER, \n\t\"Phone_ID\" TEXT, \n\t\"Num_of_stock\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\", \"Phone_ID\"), \n\tFOREIGN KEY(\"Phone_ID\") REFERENCES phone (\"Phone_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/*\nColumns in phone_market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 6\nPhone_ID : 1, 2, 4, 3\nNum_of_stock : 2232, 874, 4324, 682, 908, 1632\n*/\n \nCREATE TABLE \"Authorship\" (\n\t\"authID\" INTEGER, \n\t\"instID\" INTEGER, \n\t\"paperID\" INTEGER, \n\t\"authOrder\" INTEGER, \n\tPRIMARY KEY (\"authID\", \"instID\", \"paperID\"), \n\tFOREIGN KEY(\"authID\") REFERENCES \"Authors\" (\"authID\"), \n\tFOREIGN KEY(\"instID\") REFERENCES \"Inst\" (\"instID\"), \n\tFOREIGN KEY(\"paperID\") REFERENCES \"Papers\" (\"paperID\")\n)\n/*\nColumns in Authorship and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\n*/\n/*\nColumns in Authorship and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\npaperID : 201, 204, 205, 200, 206, 203, 202\nauthOrder : 1, 2, 3\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Membership_card\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Time_of_purchase\" INTEGER, \n\t\"Level_of_membership\" INTEGER, \n\t\"Address\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Peeler, Russell, Rizzo, Todd, Campbell, Jessie, Breton, Robert, Komisarjevsky, Joshua, Webb, Daniel, Ashby, Lazale, Hayes, Steven, Reynolds, Richard, Cobb, Sedrick\nMembership_card : White, Black\nAge : 67, 45, 33, 50, 34, 42, 29, 51, 35\nTime_of_purchase : 26, 20, 44, 24, 18, 27, 41\nLevel_of_membership : 1, 2, 5, 4, 6, 3, 22\nAddress : Hartford, Bridgeport, Cheshire, Waterbury\n*/\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/*\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/*\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n*/\n/*\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_first_name VARCHAR(80), \n\tstaff_last_name VARCHAR(80), \n\tother_staff_details VARCHAR(255), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_first_name : Junius, Israel, Kenyatta\nstaff_last_name : Mante, Treutel, Weber\n*/\n/*\nColumns in Staff and all categories for low cardinality columns :\nother_staff_details : d, m, q, b, i, e, w, j, p, x\n*/\n \nCREATE TABLE dept_locations (\n\t\"Dnumber\" INTEGER, \n\t\"Dlocation\" TEXT, \n\tPRIMARY KEY (\"Dnumber\", \"Dlocation\")\n)\n/*\nColumns in dept_locations and all categories for low cardinality columns :\nDnumber : 1, 4, 5\nDlocation : Stafford, Sugarland, Bellaire, Houston\n*/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/*\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n*/\n \nCREATE TABLE \"Electoral_Register\" (\n\telectoral_register_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (electoral_register_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/*\nColumns in Electoral_Register and all categories for low cardinality columns :\nelectoral_register_id : 2, 7, 8, 4, 6, 3\ncmi_cross_ref_id : 65, 75, 100, 83, 95\n*/\n" }, { "role": "user", "content": "What is the id, name and nationality of the architect who built most mills?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: architect, mill.\nFrom these tables, I'll be using the following columns: architect.id, architect.name, architect.nationality, mill.architect_id.\nThe SQL query I'll be generating is:\nSELECT T1.id , T1.name , T1.nationality FROM architect AS T1 JOIN mill AS T2 ON T1.id = T2.architect_id GROUP BY T1.id ORDER BY count(*) DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE shop (\n\t\"Shop_ID\" INTEGER, \n\t\"Shop_Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Open_Date\" TEXT, \n\t\"Open_Year\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\")\n)\n/*\nColumns in shop and 3 examples in each column for high cardinality columns :\nShop_ID : 1, 11, 2\nShop_Name : Pentre store, Best Buy, Apple\nOpen_Date : 24 February, 18 February, 1 January\n*/\n/*\nColumns in shop and all categories for low cardinality columns :\nLocation : Maerdy, Porth, Blaenllechau, Pentre, Penygraig, Gelli, Dinas, Wattstown, Cymmer\nOpen_Year : 2009, 2013, 2015, 2017, 2006, 2011, 2014, 2010, 2007\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tparent_product_id INTEGER, \n\tproduct_category_code VARCHAR(20) NOT NULL, \n\tdate_product_first_available DATETIME, \n\tdate_product_discontinued DATETIME, \n\tproduct_name VARCHAR(80), \n\tproduct_description VARCHAR(255), \n\tproduct_price DECIMAL(19, 4), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\nparent_product_id : 8, 4, 9, 3\nproduct_category_code : Food, Book, Hardware\ndate_product_first_available : 1988-09-29 17:54:50, 1998-06-20 15:04:11, 1994-12-18 15:13:19, 1974-06-25 12:26:47\ndate_product_discontinued : 1987-12-20 13:46:16, 1997-07-02 18:26:16, 1980-06-26 10:40:19, 1991-08-20 05:22:31\nproduct_name : Chocolate, The Great Gatsby, Mouse, Keyboard\nproduct_description : Designed for games, Handmade chocolate, American novel, Blue tooth mouse\nproduct_price : 23.3500, 2.8800, 109.9900, 35.0000\n*/\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/*\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n*/\n \nCREATE TABLE round (\n\t\"Round_ID\" INTEGER, \n\t\"Member_ID\" INTEGER, \n\t\"Decoration_Theme\" TEXT, \n\t\"Rank_in_Round\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Round_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/*\nColumns in round and all categories for low cardinality columns :\nRound_ID : 1, 2\nMember_ID : 1, 2, 4, 6, 10, 9\nDecoration_Theme : Dark Nights, Summer, Walk on the Moon, Sweetie, Soft Dream, Happiness\nRank_in_Round : 1, 2, 4, 3\n*/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/*\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n*/\n \nCREATE TABLE \"Visits_Restaurant\" (\n\t\"StuID\" INTEGER, \n\t\"ResID\" INTEGER, \n\t\"Time\" TIMESTAMP, \n\t\"Spent\" FLOAT, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\")\n)\n/*\nColumns in Visits_Restaurant and all categories for low cardinality columns :\nStuID : 1001, 1032\nResID : 1, 2\nTime : 2017-10-09 18:15:00, 2017-10-08 13:00:30\nSpent : 13.2, 6.53\n*/\n \nCREATE TABLE \"Customer_Payments\" (\n\tcustomer_id INTEGER NOT NULL, \n\tdatetime_payment DATETIME NOT NULL, \n\tpayment_method_code VARCHAR(10) NOT NULL, \n\tamount_payment DOUBLE, \n\tPRIMARY KEY (customer_id, datetime_payment), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Payments and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ndatetime_payment : 2018-03-20 21:38:41, 2018-02-15 16:38:49, 2018-02-19 01:49:59\namount_payment : 9570.93, 6782.84, 787.12\n*/\n/*\nColumns in Customer_Payments and all categories for low cardinality columns :\npayment_method_code : Direct Debit, Credit Card\n*/\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/*\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Birth_Date\" TEXT, \n\t\"Birth_Place\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 4, 6, 3\nName : Ty Conklin, Jake Gardiner, Al Montoya, Mark Fayne, Jack Campbell, Cam Fowler\nHeight : 215.0, 182.0, 195.0, 205.0, 192.0, 196.0\nWeight : 89.0, 100.0, 90.0, 102.0, 80.0, 92.0\nBirth_Date : December 5, 1991, May 5, 1987, July 4, 1990, February 13, 1985, March 30, 1976, January 1, 1992\nBirth_Place : Farmington Hills, Michigan, Anchorage, Alaska, Glenview, Illinois, Nashua, New Hampshire, Minnetonka, Minnesota, Port Huron, Michigan\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Problem_Log\" (\n\tproblem_log_id INTEGER, \n\tassigned_to_staff_id INTEGER NOT NULL, \n\tproblem_id INTEGER NOT NULL, \n\tproblem_category_code VARCHAR(20) NOT NULL, \n\tproblem_status_code VARCHAR(20) NOT NULL, \n\tlog_entry_date DATETIME, \n\tlog_entry_description VARCHAR(255), \n\tlog_entry_fix VARCHAR(255), \n\tother_log_details VARCHAR(255), \n\tPRIMARY KEY (problem_log_id), \n\tFOREIGN KEY(problem_status_code) REFERENCES \"Problem_Status_Codes\" (problem_status_code), \n\tFOREIGN KEY(problem_id) REFERENCES \"Problems\" (problem_id), \n\tFOREIGN KEY(assigned_to_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(problem_category_code) REFERENCES \"Problem_Category_Codes\" (problem_category_code)\n)\n/*\nColumns in Problem_Log and 3 examples in each column for high cardinality columns :\nproblem_log_id : 1, 13, 11\nlog_entry_date : 1997-08-31 08:19:12, 1974-09-13 00:37:26, 2011-11-12 23:30:53\nlog_entry_description : t, d, b\nlog_entry_fix : t, i, s\nother_log_details : d, f, b\n*/\n/*\nColumns in Problem_Log and all categories for low cardinality columns :\nassigned_to_staff_id : 1, 13, 11, 2, 5, 8, 4, 6, 12, 10\nproblem_id : 1, 13, 11, 10, 7, 8, 4, 12, 15\nproblem_category_code : Datatabase, Middleware, GUI\nproblem_status_code : Solved, Reported\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/*\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n*/\n \nCREATE TABLE \"Companies\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Industry\" TEXT, \n\t\"Sales_billion\" REAL, \n\t\"Profits_billion\" REAL, \n\t\"Assets_billion\" REAL, \n\t\"Market_Value_billion\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Companies and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : PetroChina, Berkshire Hathaway, Petrobras\nSales_billion : 69.2, 189.6, 421.8\nProfits_billion : 16.4, 19.9, 17.4\nAssets_billion : 2467.9, 192.8, 1913.9\nMarket_Value_billion : 239.5, 186.5, 224.8\n*/\n/*\nColumns in Companies and all categories for low cardinality columns :\nHeadquarters : Spain, UK, China, Brazil, France, Russia, USA, Netherlands\nIndustry : Retailing, Conglomerate, Oil and gas, Telecommunications, Banking\n*/\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/*\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n*/\n \nCREATE TABLE affected_region (\n\t\"Region_id\" INTEGER, \n\t\"Storm_ID\" INTEGER, \n\t\"Number_city_affected\" REAL, \n\tPRIMARY KEY (\"Region_id\", \"Storm_ID\"), \n\tFOREIGN KEY(\"Storm_ID\") REFERENCES storm (\"Storm_ID\"), \n\tFOREIGN KEY(\"Region_id\") REFERENCES region (\"Region_id\")\n)\n/*\nColumns in affected_region and all categories for low cardinality columns :\nRegion_id : 1, 2, 12, 3\nStorm_ID : 1, 5, 4, 3\nNumber_city_affected : 12.0, 30.0, 15.0, 10.0, 22.0, 37.0\n*/\n" }, { "role": "user", "content": "What are the ids, names and genders of the architects who built two bridges or one mill?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: architect, bridge, mill.\nFrom these tables, I'll be using the following columns: architect.id, architect.name, architect.gender, mill.architect_id.\nThe SQL query I'll be generating is:\nSELECT T1.id , T1.name , T1.gender FROM architect AS T1 JOIN bridge AS T2 ON T1.id = T2.architect_id GROUP BY T1.id HAVING count(*) = 2 UNION SELECT T1.id , T1.name , T1.gender FROM architect AS T1 JOIN mill AS T2 ON T1.id = T2.architect_id GROUP BY T1.id HAVING count(*) = 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/*\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n*/\n\n \nCREATE TABLE \"Fault_Log_Parts\" (\n\tfault_log_entry_id INTEGER NOT NULL, \n\tpart_fault_id INTEGER NOT NULL, \n\tfault_status VARCHAR(10) NOT NULL, \n\tFOREIGN KEY(fault_log_entry_id) REFERENCES \"Fault_Log\" (fault_log_entry_id), \n\tFOREIGN KEY(part_fault_id) REFERENCES \"Part_Faults\" (part_fault_id)\n)\n/*\nColumns in Fault_Log_Parts and 3 examples in each column for high cardinality columns :\npart_fault_id : 1, 11, 2\n*/\n/*\nColumns in Fault_Log_Parts and all categories for low cardinality columns :\nfault_log_entry_id : 1, 3, 13, 11, 7, 4, 6, 14, 12\nfault_status : Fixed, Reported, Waiting, Return\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"Forms\" (\n\tform_id INTEGER, \n\tform_type_code VARCHAR(15) NOT NULL, \n\tservice_id INTEGER, \n\tform_number VARCHAR(50), \n\tform_name VARCHAR(80), \n\tform_description VARCHAR(255), \n\tPRIMARY KEY (form_id), \n\tFOREIGN KEY(service_id) REFERENCES \"Services\" (service_id)\n)\n/*\nColumns in Forms and all categories for low cardinality columns :\nform_id : 1, 2, 5, 4, 6, 3\nform_type_code : Basic, Complex\nservice_id : 13, 2, 7, 14, 3, 9\nform_number : 9173, 8069, 9837, 6673, 9130, 2675\nform_name : Marriage Certificate, Account Application, Divorce Certificate, Moving Form, Property Change, SSN Application\nform_description : Form for SSN Application, Form for moving house, Form for Property Change, Marriage Certificate, Divorce Certificate, Form for Account Application\n*/\n \nCREATE TABLE invoice_lines (\n\tid INTEGER, \n\tinvoice_id INTEGER NOT NULL, \n\ttrack_id INTEGER NOT NULL, \n\tunit_price NUMERIC(10, 2) NOT NULL, \n\tquantity INTEGER NOT NULL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(invoice_id) REFERENCES invoices (id), \n\tFOREIGN KEY(track_id) REFERENCES tracks (id)\n)\n/*\nColumns in invoice_lines and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\ninvoice_id : 36, 17, 21\ntrack_id : 1188, 756, 988\n*/\n/*\nColumns in invoice_lines and all categories for low cardinality columns :\nunit_price : 0.99\nquantity : 1\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Sponsor_name\" TEXT, \n\t\"Player_name\" TEXT, \n\t\"Gender\" TEXT, \n\t\"Residence\" TEXT, \n\t\"Occupation\" TEXT, \n\t\"Votes\" INTEGER, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Player_ID\")\n)\n/*\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nSponsor_name : Elmwood—Transcona, Brandon—Souris, Winnipeg South Centre\nPlayer_name : Mohamed Alli, Matt Schaubroeck, Jean Luc Bouché\nOccupation : Parliamentarian, Distribution Centre Associate, Product Consultant - MLCC\nVotes : 4673, 14097, 7190\n*/\n/*\nColumns in player and all categories for low cardinality columns :\nGender : F, M\nResidence : Selkirk, Thompson, Brandon, Birtle, Oakbank, Winnipeg\nRank : 4th, 3rd, 2nd, 1st\n*/\n \nCREATE TABLE \"Agreements\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/*\nColumns in Agreements and 3 examples in each column for high cardinality columns :\nDocument_ID : 1, 13, 11\n*/\n/*\nColumns in Agreements and all categories for low cardinality columns :\nEvent_ID : 13, 11, 10, 5, 8, 6, 12, 15, 9\n*/\n \nCREATE TABLE team (\n\t\"Team_id\" INTEGER, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Team_id\")\n)\n/*\nColumns in team and all categories for low cardinality columns :\nTeam_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Enrique Osinski, Berneice Hand, Columbus Crew, Evalyn Feil, D.C. United, Anais VonRueden, Ryley Goldner, Miami Fusion, Los Angeles Galaxy, Brown Erdman\n*/\n \nCREATE TABLE \"Faculty_Participates_in\" (\n\t\"FacID\" INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(\"FacID\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/*\nColumns in Faculty_Participates_in and 3 examples in each column for high cardinality columns :\nFacID : 7723, 6112, 3457\nactid : 771, 782, 770\n*/\n\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/*\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n*/\n/*\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n*/\n \nCREATE TABLE \"Gradeconversion\" (\n\tlettergrade VARCHAR(2), \n\tgradepoint FLOAT, \n\tPRIMARY KEY (lettergrade)\n)\n/*\nColumns in Gradeconversion and 3 examples in each column for high cardinality columns :\nlettergrade : D+, F, B-\ngradepoint : 3.7, 3.0, 2.7\n*/\n\n \nCREATE TABLE \"Has_Allergy\" (\n\t\"StuID\" INTEGER, \n\t\"Allergy\" VARCHAR(20), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Allergy\") REFERENCES \"Allergy_Type\" (\"Allergy\")\n)\n/*\nColumns in Has_Allergy and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nAllergy : Soy, Milk, Eggs\n*/\n\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/*\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Services\" (\n\tservice_id INTEGER NOT NULL, \n\torganization_id INTEGER NOT NULL, \n\tservice_type_code CHAR(15) NOT NULL, \n\tservice_details VARCHAR(255), \n\tPRIMARY KEY (service_id), \n\tFOREIGN KEY(organization_id) REFERENCES \"Organizations\" (organization_id)\n)\n/*\nColumns in Services and 3 examples in each column for high cardinality columns :\nservice_id : 87, 41, 65\n*/\n/*\nColumns in Services and all categories for low cardinality columns :\norganization_id : 7, 10, 8\nservice_type_code : Cleanning, Moving Out, Check, Pay bills\nservice_details : Satisfied, Unsatisfied\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Problem_Status_Codes\" (\n\tproblem_status_code VARCHAR(20), \n\tproblem_status_description VARCHAR(80), \n\tPRIMARY KEY (problem_status_code)\n)\n/*\nColumns in Problem_Status_Codes and all categories for low cardinality columns :\nproblem_status_code : Solved, Reported\nproblem_status_description : Solved, Reported\n*/\n \nCREATE TABLE festival_detail (\n\t\"Festival_ID\" INTEGER, \n\t\"Festival_Name\" TEXT, \n\t\"Chair_Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Festival_ID\")\n)\n/*\nColumns in festival_detail and all categories for low cardinality columns :\nFestival_ID : 1, 2, 5, 4, 3\nFestival_Name : Gobel Awards, LA Awards, Flower Awards, Panasonic Awards, Cherry Awards\nChair_Name : Doug Ford, Charles Coody, Lucy Lu, Arnold Palmer, Raymond Floyd\nLocation : United States\nYear : 2007, 2008, 2010, 2006\nNum_of_Audience : 160, 152, 161, 155\n*/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\tname TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" TEXT, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/*\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nname : AIB, IFG, HGS2, HSBIF, BK Slide, ASC\nRegion : Japan, UK, China, Brazil, England, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n*/\n" }, { "role": "user", "content": "What is the location of the bridge named 'Kolob Arch' or 'Rainbow Bridge'?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: bridge.\nFrom these tables, I'll be using the following columns: name.\nThe SQL query I'll be generating is:\nSELECT LOCATION FROM bridge WHERE name = 'Kolob Arch' OR name = 'Rainbow Bridge'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE weekly_weather (\n\tstation_id INTEGER, \n\tday_of_week TEXT, \n\thigh_temperature INTEGER, \n\tlow_temperature INTEGER, \n\tprecipitation REAL, \n\twind_speed_mph INTEGER, \n\tPRIMARY KEY (station_id, day_of_week), \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/*\nColumns in weekly_weather and 3 examples in each column for high cardinality columns :\nwind_speed_mph : 13, 20, 7\n*/\n/*\nColumns in weekly_weather and all categories for low cardinality columns :\nstation_id : 1, 2, 4, 3, 10\nday_of_week : Sunday, Wednesday, Tuesday, Thursday, Monday, Friday, Saturday\nhigh_temperature : 55, 49, 58, 50, 66, 59, 60, 57, 54\nlow_temperature : 56, 46, 55, 49, 50, 52, 54\nprecipitation : 60.0, 30.0, 10.0, 90.0, 50.0, 70.0, 80.0, 20.0\n*/\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/*\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/*\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n*/\n \nCREATE TABLE \"Parties_in_Events\" (\n\t\"Party_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Role_Code\" CHAR(15), \n\tPRIMARY KEY (\"Party_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES \"Parties\" (\"Party_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/*\nColumns in Parties_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 1, 13, 15\n*/\n/*\nColumns in Parties_in_Events and all categories for low cardinality columns :\nParty_ID : 5, 4, 6, 3, 9\nRole_Code : Organizer, Participant\n*/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/*\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n*/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Num_of_employees\" INTEGER, \n\t\"Num_of_shops\" REAL, \n\t\"Ranking\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/*\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nDistrict : New Brunswick, Quebec, Ontario, Nova Scotia, Alberta, British Columbia\nNum_of_employees : 1978, 1958, 1968, 1965, 1966\nNum_of_shops : 49.0, 10.0, 40.0, 32.0, 54.0\nRanking : 1, 5, 8, 4, 21, 3\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_first_name VARCHAR(80), \n\tstaff_last_name VARCHAR(80), \n\tother_staff_details VARCHAR(255), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_first_name : Junius, Israel, Kenyatta\nstaff_last_name : Mante, Treutel, Weber\n*/\n/*\nColumns in Staff and all categories for low cardinality columns :\nother_staff_details : d, m, q, b, i, e, w, j, p, x\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"Research_Outcomes\" (\n\toutcome_code VARCHAR(10), \n\toutcome_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (outcome_code)\n)\n/*\nColumns in Research_Outcomes and all categories for low cardinality columns :\noutcome_code : Patent, Paper\noutcome_description : Published Research Paper, Research Patent\n*/\n \nCREATE TABLE \"Investors\" (\n\tinvestor_id INTEGER, \n\t\"Investor_details\" VARCHAR(255), \n\tPRIMARY KEY (investor_id)\n)\n/*\nColumns in Investors and 3 examples in each column for high cardinality columns :\ninvestor_id : 17, 9, 16\nInvestor_details : d, t, b\n*/\n\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Album\" (\n\t\"AlbumId\" INTEGER NOT NULL, \n\t\"Title\" VARCHAR(160) NOT NULL, \n\t\"ArtistId\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"AlbumId\"), \n\tFOREIGN KEY(\"ArtistId\") REFERENCES \"Artist\" (\"ArtistId\")\n)\n/*\nColumns in Album and 3 examples in each column for high cardinality columns :\nAlbumId : 87, 56, 65\nTitle : The Number of The Beast, One By One, Dance Of Death\nArtistId : 87, 56, 95\n*/\n\n \nCREATE TABLE \"PersonFriend\" (\n\tname VARCHAR(20), \n\tfriend VARCHAR(20), \n\tyear INTEGER, \n\tFOREIGN KEY(name) REFERENCES \"Person\" (name), \n\tFOREIGN KEY(friend) REFERENCES \"Person\" (name)\n)\n/*\nColumns in PersonFriend and all categories for low cardinality columns :\nname : Alice, Zach, Bob\nfriend : Alice, Dan, Zach, Bob\nyear : 10, 5, 6, 12\n*/\n \nCREATE TABLE \"Customer_Master_Index\" (\n\tmaster_customer_id INTEGER NOT NULL, \n\tcmi_details VARCHAR(255), \n\tPRIMARY KEY (master_customer_id)\n)\n/*\nColumns in Customer_Master_Index and all categories for low cardinality columns :\nmaster_customer_id : 1, 2, 5, 7, 8, 4, 6, 3, 9\ncmi_details : Reynolds-McClure, Quigley-Paucek, Volkman, Mills and Ferry, Mayer-Hagenes, Schmidt, Kertzmann and Lubowitz, Gottlieb, Becker and Wyman, Streich-Morissette, Schmitt-Lang, Gusikowski PLC\n*/\n \nCREATE TABLE coach (\n\t\"Coach_ID\" INTEGER, \n\t\"Coach_name\" TEXT, \n\t\"Gender\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Coach_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/*\nColumns in coach and all categories for low cardinality columns :\nCoach_ID : 1, 2, 5, 4, 3\nCoach_name : Robert Chen, James Wong, Smith Brown, Jameson Tomas, Joe Fabbri\nGender : F, M\nClub_ID : 1, 3\nRank : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n*/\n/*\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n*/\n" }, { "role": "user", "content": "Which of the mill names contains the french word 'Moulin'?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: mill.\nFrom these tables, I'll be using the following columns: name.\nThe SQL query I'll be generating is:\nSELECT name FROM mill WHERE name LIKE '%Moulin%'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE faculty (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Faculty\" REAL, \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/*\nColumns in faculty and 3 examples in each column for high cardinality columns :\nCampus : 17, 21, 9\nFaculty : 449.8, 117.7, 1027.6\n*/\n/*\nColumns in faculty and all categories for low cardinality columns :\nYear : 2002, 2003, 2004\n*/\n \nCREATE TABLE train_station (\n\t\"Train_ID\" INTEGER, \n\t\"Station_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\", \"Station_ID\"), \n\tFOREIGN KEY(\"Train_ID\") REFERENCES train (\"Train_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES station (\"Station_ID\")\n)\n/*\nColumns in train_station and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\n*/\n/*\nColumns in train_station and all categories for low cardinality columns :\nStation_ID : 1, 2, 5, 8, 3, 10, 9\n*/\n \nCREATE TABLE \"Authorship\" (\n\t\"authID\" INTEGER, \n\t\"instID\" INTEGER, \n\t\"paperID\" INTEGER, \n\t\"authOrder\" INTEGER, \n\tPRIMARY KEY (\"authID\", \"instID\", \"paperID\"), \n\tFOREIGN KEY(\"authID\") REFERENCES \"Authors\" (\"authID\"), \n\tFOREIGN KEY(\"instID\") REFERENCES \"Inst\" (\"instID\"), \n\tFOREIGN KEY(\"paperID\") REFERENCES \"Papers\" (\"paperID\")\n)\n/*\nColumns in Authorship and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\n*/\n/*\nColumns in Authorship and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\npaperID : 201, 204, 205, 200, 206, 203, 202\nauthOrder : 1, 2, 3\n*/\n \nCREATE TABLE technician (\n\ttechnician_id REAL, \n\t\"Name\" TEXT, \n\t\"Team\" TEXT, \n\t\"Starting_Year\" REAL, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (technician_id)\n)\n/*\nColumns in technician and all categories for low cardinality columns :\ntechnician_id : 3.0, 8.0, 10.0, 1.0, 7.0, 2.0, 6.0, 9.0, 4.0, 5.0\nName : Mark Sewell, John Brown, Mickey Cochrane, Joe Sewell, Tony Sewell, Joe Cochrane, Eddie Collins, Charlie Hollocher, Lou Boudreau\nTeam : CHC, NYY, CLE, PHA, CWS\nStarting_Year : 2013.0, 2016.0, 2003.0, 2006.0, 2005.0, 2002.0, 2009.0, 2012.0\nAge : 38, 37, 45, 46, 28, 36, 32, 47, 43, 35\n*/\n \nCREATE TABLE storm (\n\t\"Storm_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Dates_active\" TEXT, \n\t\"Max_speed\" INTEGER, \n\t\"Damage_millions_USD\" REAL, \n\t\"Number_Deaths\" INTEGER, \n\tPRIMARY KEY (\"Storm_ID\")\n)\n/*\nColumns in storm and all categories for low cardinality columns :\nStorm_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Three, One, Five, Nine, Four, Seven, Six, Eight, 9 cyclones, Two\nDates_active : August5–August14, May19 –October26, August3–August10, September22–September28, September7–September17, May19–May25, October24–October26, August26–September2, September18–September25, October20–October24\nMax_speed : 1007, 988, 977, 961, 972, 1002, 983, 995\nDamage_millions_USD : 1.49, 10.75, 13.0, 29.3, 4.05, 0.039\nNumber_Deaths : 2, 7, 52, 3, 71, 0\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE faculty (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Faculty\" REAL, \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/*\nColumns in faculty and 3 examples in each column for high cardinality columns :\nCampus : 17, 21, 9\nFaculty : 449.8, 117.7, 1027.6\n*/\n/*\nColumns in faculty and all categories for low cardinality columns :\nYear : 2002, 2003, 2004\n*/\n \nCREATE TABLE \"Products_in_Events\" (\n\t\"Product_in_Event_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Product_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Product_in_Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\"), \n\tFOREIGN KEY(\"Product_ID\") REFERENCES \"Products\" (\"Product_ID\")\n)\n/*\nColumns in Products_in_Events and 3 examples in each column for high cardinality columns :\nProduct_in_Event_ID : 79, 69, 13\n*/\n/*\nColumns in Products_in_Events and all categories for low cardinality columns :\nEvent_ID : 1, 10, 5, 7, 8, 4, 6, 14, 15\nProduct_ID : 26, 45, 20, 11, 18, 34, 6, 3, 10, 29\n*/\n \nCREATE TABLE \"Products_for_Hire\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(15) NOT NULL, \n\tdaily_hire_cost DECIMAL(19, 4), \n\tproduct_name VARCHAR(80), \n\tproduct_description VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products_for_Hire and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 4, 3\nproduct_type_code : Din_Plates, Cutlery\ndaily_hire_cost : 18.5000, 39.5800, 15.6200, 39.7300, 26.1500\nproduct_name : DVD collection B, DVD collection A, Book collection C, Book collection A, Book collection B\nproduct_description : The Great Gatsby, Anna Karenina, One Hundred Years of Solitude, War and Peace, Twilight\n*/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n*/\n \nCREATE TABLE branch (\n\t\"Branch_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Open_year\" TEXT, \n\t\"Address_road\" TEXT, \n\t\"City\" TEXT, \n\tmembership_amount TEXT, \n\tPRIMARY KEY (\"Branch_ID\")\n)\n/*\nColumns in branch and all categories for low cardinality columns :\nBranch_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Popert, Zytogorski, Alexandre, Brooke Greville, Taverner, Stanley, Saint Amant, Cochrane\nOpen_year : 2009, 2013, 2015, 2001, 2012, 2014\nAddress_road : Abbott Street, Concord Road, Brampton Road, Cecilia Avenue, Oaks Crescent, Valleys Place, Glebe Street, Abbey Rise\nCity : Oxford, London\nmembership_amount : 91, 56, 11, 1418, 7, 6, 112, 31\n*/\n \nCREATE TABLE manufacturer (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Open_Year\" REAL, \n\t\"Name\" TEXT, \n\t\"Num_of_Factories\" INTEGER, \n\t\"Num_of_Shops\" INTEGER, \n\tPRIMARY KEY (\"Manufacturer_ID\")\n)\n/*\nColumns in manufacturer and all categories for low cardinality columns :\nManufacturer_ID : 1, 2, 5, 7, 4, 6, 3\nOpen_Year : 2001.0, 2008.0, 2000.0, 1980.0, 1992.0, 1991.0, 1990.0\nName : Tomorrow, Chevrolet, Chevrolet House, Jiaju, Ford Make, IKEA, Dodge\nNum_of_Factories : 1, 38, 36, 21, 12, 3\nNum_of_Shops : 2, 7, 8, 24, 4, 19, 35\n*/\n \nCREATE TABLE driver (\n\t\"Driver_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Home_city\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Driver_ID\")\n)\n/*\nColumns in driver and 3 examples in each column for high cardinality columns :\nDriver_ID : 1, 11, 2\nName : Edwin Vargas, Henry Genga, Douglas McCrory\n*/\n/*\nColumns in driver and all categories for low cardinality columns :\nParty : Rep, Dem\nHome_city : Coventry, East Hartford, Hartford, Bethel, Manchester\nAge : 38, 45, 46, 37, 40, 36, 30, 52, 42, 35\n*/\n \nCREATE TABLE submission (\n\t\"Submission_ID\" INTEGER, \n\t\"Scores\" REAL, \n\t\"Author\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\")\n)\n/*\nColumns in submission and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nScores : 89.0, 79.0, 82.0, 83.0, 92.0, 93.0, 72.0, 78.0\nAuthor : Rick Engles, Andy Bolton, Jeff Lloyd, Don Bitterlich, Steve Raible, Steve Niehaus, Sherman Smith, Randy Johnson, Sammy Green, Steve Myer\nCollege : Fisk, Georgia Tech, Tulsa, Georgia, Miami (OH), West Texas State, Temple, Notre Dame, Florida, New Mexico\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE film_actor (\n\tactor_id INTEGER NOT NULL, \n\tfilm_id INTEGER NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (actor_id, film_id), \n\tFOREIGN KEY(actor_id) REFERENCES actor (actor_id), \n\tFOREIGN KEY(film_id) REFERENCES film (film_id)\n)\n/*\nColumns in film_actor and 3 examples in each column for high cardinality columns :\nfilm_id : 87, 616, 56\n*/\n/*\nColumns in film_actor and all categories for low cardinality columns :\nactor_id : 1, 2, 5, 7, 8, 4, 6, 3, 9\nlast_update : 2006-02-15 05:05:03\n*/\n \nCREATE TABLE competition (\n\t\"Competition_ID\" INTEGER, \n\t\"Year\" REAL, \n\t\"Competition_type\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\")\n)\n/*\nColumns in competition and 3 examples in each column for high cardinality columns :\nCompetition_ID : 1, 11, 2\n*/\n/*\nColumns in competition and all categories for low cardinality columns :\nYear : 2006.0, 2007.0\nCompetition_type : Tournament, Friendly\nCountry : Italy, Slovenia, Spain, Australia, Russia, Ireland\n*/\n \nCREATE TABLE host (\n\t\"Host_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\tPRIMARY KEY (\"Host_ID\")\n)\n/*\nColumns in host and all categories for low cardinality columns :\nHost_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Lloyd Daniels, Kornel David, Antonio Davis, Carlos Delfino, DeMar DeRozan, Ed Davis, Austin Daye, Derrick Dial, Justin Dentmon, Hubert Davis\nNationality : United States, Argentina, Hungary\nAge : 26, 45, 37, 40, 30, 60, 47, 43, 31\n*/\n \nCREATE TABLE \"Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Event_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Service_ID\") REFERENCES \"Services\" (\"Service_ID\")\n)\n/*\nColumns in Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n*/\n/*\nColumns in Events and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nEvent_Details : Fail, Success\n*/\n \nCREATE TABLE \"ENROLL\" (\n\t\"CLASS_CODE\" VARCHAR(5), \n\t\"STU_NUM\" INTEGER, \n\t\"ENROLL_GRADE\" VARCHAR(50), \n\tFOREIGN KEY(\"CLASS_CODE\") REFERENCES \"CLASS\" (\"CLASS_CODE\"), \n\tFOREIGN KEY(\"STU_NUM\") REFERENCES \"STUDENT\" (\"STU_NUM\")\n)\n/*\nColumns in ENROLL and all categories for low cardinality columns :\nCLASS_CODE : 10014, 10021, 10018\nSTU_NUM : 321452, 324257\nENROLL_GRADE : A, C, B\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n" }, { "role": "user", "content": "What are the distinct name of the mills built by the architects who have also built a bridge longer than 80 meters?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: mill, architect, bridge.\nFrom these tables, I'll be using the following columns: mill.name, mill.architect_id, T2.id, bridge.architect_id, bridge.length_meters.\nThe SQL query I'll be generating is:\nSELECT DISTINCT T1.name FROM mill AS T1 JOIN architect AS t2 ON T1.architect_id = T2.id JOIN bridge AS T3 ON T3.architect_id = T2.id WHERE T3.length_meters > 80" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Sponsor_name\" TEXT, \n\t\"Player_name\" TEXT, \n\t\"Gender\" TEXT, \n\t\"Residence\" TEXT, \n\t\"Occupation\" TEXT, \n\t\"Votes\" INTEGER, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Player_ID\")\n)\n/*\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nSponsor_name : Elmwood—Transcona, Brandon—Souris, Winnipeg South Centre\nPlayer_name : Mohamed Alli, Matt Schaubroeck, Jean Luc Bouché\nOccupation : Parliamentarian, Distribution Centre Associate, Product Consultant - MLCC\nVotes : 4673, 14097, 7190\n*/\n/*\nColumns in player and all categories for low cardinality columns :\nGender : F, M\nResidence : Selkirk, Thompson, Brandon, Birtle, Oakbank, Winnipeg\nRank : 4th, 3rd, 2nd, 1st\n*/\n \nCREATE TABLE aircraft (\n\taid NUMERIC(9, 0), \n\tname TEXT(30), \n\tdistance NUMERIC(6, 0), \n\tPRIMARY KEY (aid)\n)\n/*\nColumns in aircraft and 3 examples in each column for high cardinality columns :\naid : 1, 16, 13\nname : Boeing 757-300, Lockheed L1011, Airbus A319\ndistance : 2128, 6475, 8430\n*/\n\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/*\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n*/\n/*\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n*/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/*\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Document_Sections\" (\n\tsection_id INTEGER, \n\tdocument_code VARCHAR(15) NOT NULL, \n\tsection_sequence INTEGER, \n\tsection_code VARCHAR(20), \n\tsection_title VARCHAR(80), \n\tPRIMARY KEY (section_id), \n\tFOREIGN KEY(document_code) REFERENCES \"Documents\" (document_code)\n)\n/*\nColumns in Document_Sections and 3 examples in each column for high cardinality columns :\nsection_id : 89, 62, 38\ndocument_code : 714, 217, 566\nsection_sequence : 5552, 4433, 8805\nsection_code : 91, 16, 38\n*/\n/*\nColumns in Document_Sections and all categories for low cardinality columns :\nsection_title : after, before\n*/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/*\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n*/\n/*\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n*/\n \nCREATE TABLE \"PersonFriend\" (\n\tname VARCHAR(20), \n\tfriend VARCHAR(20), \n\tyear INTEGER, \n\tFOREIGN KEY(name) REFERENCES \"Person\" (name), \n\tFOREIGN KEY(friend) REFERENCES \"Person\" (name)\n)\n/*\nColumns in PersonFriend and all categories for low cardinality columns :\nname : Alice, Zach, Bob\nfriend : Alice, Dan, Zach, Bob\nyear : 10, 5, 6, 12\n*/\n \nCREATE TABLE \"Staff\" (\n\t\"Staff_ID\" INTEGER NOT NULL, \n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(40), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Staff_ID\"), \n\tFOREIGN KEY(\"Tourist_Attraction_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/*\nColumns in Staff and 3 examples in each column for high cardinality columns :\nStaff_ID : 470, 170, 667\nTourist_Attraction_ID : 5265, 6653, 9360\nName : Astrid, Elouise, Trinity\n*/\n/*\nColumns in Staff and all categories for low cardinality columns :\nOther_Details : None\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"Invoice\" (\n\t\"InvoiceId\" INTEGER NOT NULL, \n\t\"CustomerId\" INTEGER NOT NULL, \n\t\"InvoiceDate\" DATETIME NOT NULL, \n\t\"BillingAddress\" VARCHAR(70) DEFAULT NULL, \n\t\"BillingCity\" VARCHAR(40) DEFAULT NULL, \n\t\"BillingState\" VARCHAR(40) DEFAULT NULL, \n\t\"BillingCountry\" VARCHAR(40) DEFAULT NULL, \n\t\"BillingPostalCode\" VARCHAR(10) DEFAULT NULL, \n\t\"Total\" DECIMAL(10, 2) NOT NULL, \n\tPRIMARY KEY (\"InvoiceId\"), \n\tFOREIGN KEY(\"CustomerId\") REFERENCES \"Customer\" (\"CustomerId\")\n)\n/*\nColumns in Invoice and 3 examples in each column for high cardinality columns :\nInvoiceId : 87, 56, 65\nCustomerId : 53, 56, 49\nInvoiceDate : 2009-06-10 00:00:00, 2010-05-30 00:00:00, 2011-02-16 00:00:00\nBillingAddress : 696 Osborne Street, 796 Dundas Street West, Grétrystraat 63\nBillingCity : Oslo, Lisbon, Mountain View\nBillingState : AZ, NSW, Dublin\nBillingCountry : Sweden, Australia, India\nBillingPostalCode : B3S 1C5, 85719, 1106\nTotal : 3.96, 17.91, 15.86\n*/\n\n \nCREATE TABLE trip (\n\tid INTEGER, \n\tduration INTEGER, \n\tstart_date TEXT, \n\tstart_station_name TEXT, \n\tstart_station_id INTEGER, \n\tend_date TEXT, \n\tend_station_name TEXT, \n\tend_station_id INTEGER, \n\tbike_id INTEGER, \n\tsubscription_type TEXT, \n\tzip_code INTEGER, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in trip and 3 examples in each column for high cardinality columns :\nid : 900645, 900752, 900524\nduration : 1131, 2146, 1155\nstart_date : 8/21/2015 17:39, 8/21/2015 17:03, 8/21/2015 17:16\nstart_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nstart_station_id : 56, 65, 49\nend_date : 8/21/2015 17:19, 8/21/2015 18:08, 8/21/2015 17:32\nend_station_name : Howard at 2nd, 2nd at Folsom, Market at 10th\nend_station_id : 56, 65, 49\nbike_id : 586, 56, 65\nzip_code : 94070, 94530, 94040-1724\n*/\n/*\nColumns in trip and all categories for low cardinality columns :\nsubscription_type : Customer, Subscriber\n*/\n \nCREATE TABLE exhibition_record (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Exhibition_ID\", \"Date\"), \n\tFOREIGN KEY(\"Exhibition_ID\") REFERENCES exhibition (\"Exhibition_ID\")\n)\n/*\nColumns in exhibition_record and 3 examples in each column for high cardinality columns :\nDate : February 25, February 19, December 2\nAttendance : 1313, 24808, 1233\n*/\n/*\nColumns in exhibition_record and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Ship\" (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Built_Year\" REAL, \n\t\"Class\" TEXT, \n\t\"Flag\" TEXT, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/*\nColumns in Ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : HMS Trojan, HMS Destiny, HMS Phalarope, HMS Undine, HMS Manxman, HM Cutter Avenger, HM Sloop Sparrow, HM Schooner Hotspur, HMS Gorgon\nType : Panamax\nBuilt_Year : 1997.0, 1998.0\nClass : GL, KR\nFlag : Panama, Malta\n*/\n \nCREATE TABLE grapes (\n\t\"ID\" INTEGER, \n\t\"Grape\" TEXT, \n\t\"Color\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tUNIQUE (\"Grape\")\n)\n/*\nColumns in grapes and 3 examples in each column for high cardinality columns :\nID : 17, 9, 16\nGrape : Marsanne, Tempranillo, Malbec\n*/\n/*\nColumns in grapes and all categories for low cardinality columns :\nColor : Red, White\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"SAVINGS\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/*\nColumns in SAVINGS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 4, 6, 3\nbalance : 80000.0, 230000.0, 999999999.0, 60.0, 240.0, 200000.0\n*/\n" }, { "role": "user", "content": "What is the most common mill type, and how many are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: mill.\nFrom these tables, I'll be using the following columns: TYPE.\nThe SQL query I'll be generating is:\nSELECT TYPE , count(*) FROM mill GROUP BY TYPE ORDER BY count(*) DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Dorm\" (\n\tdormid INTEGER, \n\tdorm_name VARCHAR(20), \n\tstudent_capacity INTEGER, \n\tgender VARCHAR(1)\n)\n/*\nColumns in Dorm and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\ndorm_name : University Hovels, Fawlty Towers, Anonymous Donor Hall, Smith Hall, Bud Jones Hall, Dorm-plex 2000, Grad Student Asylum\nstudent_capacity : 116, 400, 355, 40, 128, 85, 256\ngender : F, X, M\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"Party_Forms\" (\n\tparty_id INTEGER NOT NULL, \n\tform_id INTEGER NOT NULL, \n\tdate_completion_started DATETIME NOT NULL, \n\tform_status_code VARCHAR(15) NOT NULL, \n\tdate_fully_completed DATETIME, \n\tPRIMARY KEY (party_id, form_id), \n\tFOREIGN KEY(form_id) REFERENCES \"Forms\" (form_id), \n\tFOREIGN KEY(party_id) REFERENCES \"Parties\" (party_id)\n)\n/*\nColumns in Party_Forms and 3 examples in each column for high cardinality columns :\ndate_completion_started : 2017-11-29 03:11:38, 2017-12-17 11:29:47, 2017-12-04 16:57:31\ndate_fully_completed : 2018-02-15 23:09:42, 2018-02-11 16:46:10, 2018-02-04 05:57:01\n*/\n/*\nColumns in Party_Forms and all categories for low cardinality columns :\nparty_id : 13, 11, 2, 5, 7, 8, 6, 15, 9\nform_id : 2, 5, 4, 6, 3\nform_status_code : Work In Progress, Not Started, Completed, Partially Completed\n*/\n \nCREATE TABLE \"Department\" (\n\t\"DepartmentID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Head\" INTEGER NOT NULL, \n\tCONSTRAINT \"pk_Department\" PRIMARY KEY (\"DepartmentID\"), \n\tCONSTRAINT \"fk_Department_Physician_EmployeeID\" FOREIGN KEY(\"Head\") REFERENCES \"Physician\" (\"EmployeeID\")\n)\n/*\nColumns in Department and all categories for low cardinality columns :\nDepartmentID : 1, 2, 3\nName : Psychiatry, Surgery, General Medicine\nHead : 7, 4, 9\n*/\n \nCREATE TABLE browser (\n\tid INTEGER, \n\tname TEXT, \n\tmarket_share REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in browser and all categories for low cardinality columns :\nid : 1, 2, 4, 3\nname : Opera, Internet Explorer, Safari, Firefox\nmarket_share : 18.11, 8.54, 28.96, 1.2\n*/\n \nCREATE TABLE \"Settlements\" (\n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Date_Claim_Made\" DATE, \n\t\"Date_Claim_Settled\" DATE, \n\t\"Amount_Claimed\" INTEGER, \n\t\"Amount_Settled\" INTEGER, \n\t\"Customer_Policy_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Settlement_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claims\" (\"Claim_ID\")\n)\n/*\nColumns in Settlements and 3 examples in each column for high cardinality columns :\nSettlement_ID : 756, 616, 527\nDate_Claim_Made : 2017-05-19, 2016-09-05, 2018-05-12\nDate_Claim_Settled : 2017-12-24, 2017-11-15, 2018-02-20\nAmount_Claimed : 37302, 20569, 25078\nAmount_Settled : 1676, 1181, 930\nCustomer_Policy_ID : 943, 839, 590\n*/\n/*\nColumns in Settlements and all categories for low cardinality columns :\nClaim_ID : 843, 563, 801, 957, 761, 621, 486, 571, 569\n*/\n \nCREATE TABLE genre (\n\tg_name TEXT(20) NOT NULL, \n\trating TEXT(10), \n\tmost_popular_in TEXT(50), \n\tPRIMARY KEY (g_name)\n)\n/*\nColumns in genre and all categories for low cardinality columns :\ng_name : tagore, folk, modern, nazrul, blues, pop\nrating : 7, 8, 9\nmost_popular_in : America, Canada, Sylhet,Chittagong,Kustia, Bangladesh\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tpayment_method VARCHAR(15) NOT NULL, \n\tcustomer_name VARCHAR(80), \n\tcustomer_phone VARCHAR(80), \n\tcustomer_email VARCHAR(80), \n\tcustomer_address VARCHAR(255), \n\tcustomer_login VARCHAR(80), \n\tcustomer_password VARCHAR(10), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : Kyle, Ruthie, Elvera\ncustomer_phone : 698-327-5792, +66(7)1491041398, 203-036-0511x96487\ncustomer_email : kristina85@example.org, davis.rosamond@example.net, marc.schiller@example.com\ncustomer_address : 80569 Crona Path Suite 165, 5514 Ophelia Cliffs Apt. 266, 56955 Desmond Lake Apt. 120\ncustomer_password : 9dc50bc5b6, f64f0fd096, 0b9f651030\n*/\n/*\nColumns in Customers and all categories for low cardinality columns :\npayment_method : Credit Card, Direct Debit\ncustomer_login : None\n*/\n \nCREATE TABLE \"Organisation_Types\" (\n\torganisation_type VARCHAR(10), \n\torganisation_type_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (organisation_type)\n)\n/*\nColumns in Organisation_Types and all categories for low cardinality columns :\norganisation_type : RES, SPON\norganisation_type_description : Sponsor, Research\n*/\n \nCREATE TABLE employees (\n\tid INTEGER, \n\tlast_name VARCHAR(20) NOT NULL, \n\tfirst_name VARCHAR(20) NOT NULL, \n\ttitle VARCHAR(30), \n\treports_to INTEGER, \n\tbirth_date TIMESTAMP, \n\thire_date TIMESTAMP, \n\taddress VARCHAR(70), \n\tcity VARCHAR(40), \n\tstate VARCHAR(40), \n\tcountry VARCHAR(40), \n\tpostal_code VARCHAR(10), \n\tphone VARCHAR(24), \n\tfax VARCHAR(24), \n\temail VARCHAR(60), \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(reports_to) REFERENCES employees (id)\n)\n/*\nColumns in employees and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nlast_name : Callahan, Mitchell, Adams, Park, Edwards, Peacock, Johnson, King\nfirst_name : Jane, Michael, Steve, Laura, Margaret, Andrew, Robert, Nancy\ntitle : IT Staff, Sales Manager, IT Manager, Sales Support Agent, General Manager\nreports_to : 1, None, 2, 6\nbirth_date : 1973-07-01 00:00:00, 1962-02-18 00:00:00, 1968-01-09 00:00:00, 1947-09-19 00:00:00, 1973-08-29 00:00:00, 1965-03-03 00:00:00, 1970-05-29 00:00:00, 1958-12-08 00:00:00\nhire_date : 2002-04-01 00:00:00, 2003-10-17 00:00:00, 2002-05-01 00:00:00, 2004-01-02 00:00:00, 2003-05-03 00:00:00, 2002-08-14 00:00:00, 2004-03-04 00:00:00\naddress : 11120 Jasper Ave NW, 1111 6 Ave SW, 683 10 Street SW, 7727B 41 Ave, 590 Columbia Boulevard West, 923 7 ST NW, 825 8 Ave SW, 5827 Bowness Road NW\ncity : Edmonton, Calgary, Lethbridge\nstate : AB\ncountry : Canada\npostal_code : T1K 5N8, T3B 0C5, T5K 2N1, T2P 5G3, T2P 5M5, T3B 1Y7, T1H 1Y8, T2P 2T3\nphone : +1 (403) 262-3443, 1 (780) 836-9987, +1 (403) 246-9887, +1 (780) 428-9482, +1 (403) 456-9986, +1 (403) 467-3351, +1 (403) 263-4423\nfax : +1 (403) 467-8772, +1 (403) 262-3322, +1 (403) 456-8485, +1 (403) 246-9899, +1 (403) 262-6712, +1 (403) 263-4289, +1 (780) 428-3457, 1 (780) 836-9543\nemail : robert@chinookcorp.com, jane@chinookcorp.com, margaret@chinookcorp.com, steve@chinookcorp.com, michael@chinookcorp.com, andrew@chinookcorp.com, nancy@chinookcorp.com, laura@chinookcorp.com\n*/\n \nCREATE TABLE body_builder (\n\t\"Body_Builder_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Snatch\" REAL, \n\t\"Clean_Jerk\" REAL, \n\t\"Total\" REAL, \n\tPRIMARY KEY (\"Body_Builder_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in body_builder and all categories for low cardinality columns :\nBody_Builder_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 2, 5, 6, 3\nSnatch : 142.5, 137.5, 130.0, 140.0\nClean_Jerk : 162.5, 177.5, 175.0\nTotal : 315.0, 317.5, 312.5, 292.5\n*/\n \nCREATE TABLE camera_lens (\n\tid INTEGER, \n\tbrand TEXT, \n\tname TEXT, \n\tfocal_length_mm REAL, \n\tmax_aperture REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in camera_lens and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Panasonic Leica DG Summilux 25mm f /1.4 Asph., Sigma 19mm f2.8 EX DN, Sigma 30mm f2.8 DN\n*/\n/*\nColumns in camera_lens and all categories for low cardinality columns :\nbrand : Sigma, Olympus, Panasonic, Schneider Kreuznach\nfocal_length_mm : 45.0, 30.0, 15.0, 25.0, 150.0, 19.0, 14.0, 42.5, 75.0\nmax_aperture : 1.2, 8.0, 1.4, 2.0, 1.8, 2.8\n*/\n \nCREATE TABLE \"Catalog_Contents_Additional_Attributes\" (\n\tcatalog_entry_id INTEGER NOT NULL, \n\tcatalog_level_number INTEGER NOT NULL, \n\tattribute_id INTEGER NOT NULL, \n\tattribute_value VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(catalog_level_number) REFERENCES \"Catalog_Structure\" (catalog_level_number), \n\tFOREIGN KEY(catalog_entry_id) REFERENCES \"Catalog_Contents\" (catalog_entry_id)\n)\n/*\nColumns in Catalog_Contents_Additional_Attributes and all categories for low cardinality columns :\ncatalog_entry_id : 1, 11, 2, 5, 8, 4, 6, 12, 14, 15\ncatalog_level_number : 1, 8, 9\nattribute_id : 1, 2, 4, 3\nattribute_value : 1, 0\n*/\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE artist (\n\tartist_name TEXT(50) NOT NULL, \n\tcountry TEXT(20), \n\tgender TEXT(20), \n\tpreferred_genre TEXT(50), \n\tCONSTRAINT a_name PRIMARY KEY (artist_name), \n\tFOREIGN KEY(preferred_genre) REFERENCES genre (g_name) ON DELETE CASCADE\n)\n/*\nColumns in artist and all categories for low cardinality columns :\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\ncountry : India, UK, USA, Bangladesh\ngender : Male, Female\npreferred_genre : tagore, folk, modern, nazrul, blues, pop\n*/\n" }, { "role": "user", "content": "How many architects haven't built a mill before year 1850?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: architect, mill.\nFrom these tables, I'll be using the following columns: id, architect_id, built_year.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM architect WHERE id NOT IN ( SELECT architect_id FROM mill WHERE built_year < 1850 );" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE bridge (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tname TEXT, \n\tlocation TEXT, \n\tlength_meters REAL, \n\tlength_feet REAL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in bridge and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Xian Ren Qiao (Fairy Bridge), Hazarchishma Natural Bridge, Stevens Arch\nlocation : Guizhou , China, Natural Bridges National Monument , Utah , USA, Dinosaur National Monument , Colorado , USA\nlength_meters : 64.2, 69.0, 67.0\nlength_feet : 290.0, 225.0, 400.0\n*/\n/*\nColumns in bridge and all categories for low cardinality columns :\narchitect_id : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE injury_accident (\n\tgame_id INTEGER, \n\tid INTEGER, \n\t\"Player\" TEXT, \n\t\"Injury\" TEXT, \n\t\"Number_of_matches\" TEXT, \n\t\"Source\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(game_id) REFERENCES game (id)\n)\n/*\nColumns in injury_accident and 3 examples in each column for high cardinality columns :\ngame_id : 1, 11, 2\nid : 1, 13, 11\nPlayer : Dejan Stanković, Thiago Motta (2), Iván Córdoba\nInjury : Sustained a biceps femoris strain in his left leg, First-degree strain left hamstring muscles, Sustained posterior thigh strains in his left leg\n*/\n/*\nColumns in injury_accident and all categories for low cardinality columns :\nNumber_of_matches : 1, 4 (6), 2, 7 (17), 1 (2), 4, 12, 3, 10\nSource : inter.it\n*/\n \nCREATE TABLE railway (\n\t\"Railway_ID\" INTEGER, \n\t\"Railway\" TEXT, \n\t\"Builder\" TEXT, \n\t\"Built\" TEXT, \n\t\"Wheels\" TEXT, \n\t\"Location\" TEXT, \n\t\"ObjectNumber\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\")\n)\n/*\nColumns in railway and all categories for low cardinality columns :\nRailway_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nRailway : Longmoor, LTSR, GWRWk, GERSt, GWRSn, GERHt, MR, SECR, GWRS, GNRD\nBuilder : GNR Doncaster, Stephenson, Swindon Works, GWR Swindon, GER Stratford, MR Derby, GER Hartford, SECR Ashford, Avonside\nBuilt : 1902 Midland Railway 1000 was rebuilt in 1914., 1902, 1901, 1905, 1907, 1903, 1904, 1909, 1910\nWheels : 4-4-0, 4-6-0, 0-6-0T, 4-4-2, 4-4-2T, 2-8-0, 0-6-0, 0-6-0ST\nLocation : Shildon, Swindon, Basingstoke, York, Toddington, Barrow Hill, Bressingham, Bo'ness\nObjectNumber : 1975-7005, 1978-7028, 1978-7025, 1975-7003, 1978-7026, 2008-7159, 1975-7006, 1978-7027, 1975-7018, 1976-7001\n*/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/*\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n*/\n \nCREATE TABLE \"Problem_Status_Codes\" (\n\tproblem_status_code VARCHAR(20), \n\tproblem_status_description VARCHAR(80), \n\tPRIMARY KEY (problem_status_code)\n)\n/*\nColumns in Problem_Status_Codes and all categories for low cardinality columns :\nproblem_status_code : Solved, Reported\nproblem_status_description : Solved, Reported\n*/\n \nCREATE TABLE user_profiles (\n\tuid INTEGER NOT NULL, \n\tname VARCHAR(255) DEFAULT NULL, \n\temail VARCHAR(255) DEFAULT NULL, \n\tpartitionid INTEGER DEFAULT NULL, \n\tfollowers INTEGER DEFAULT NULL, \n\tPRIMARY KEY (uid)\n)\n/*\nColumns in user_profiles and all categories for low cardinality columns :\nuid : 1, 2, 5, 7, 4, 6, 3\nname : Natalie Portman, Mary, Black Widow\n, Tyler Swift, Celine Dion, Iron Man, Susan\nemail : susan@gmail.com\n, ts@superstar.com\n, cd@superstar.com, np@superstar.com, ts@richest.com, bw@superhero.com, Mary@yale.edu\npartitionid : 1, 2, 5, 23, 10\nfollowers : 23927492, 100, 94375428, 35425845, 890, 99999998, 6662425\n*/\n \nCREATE TABLE \"Campuses\" (\n\t\"Id\" INTEGER, \n\t\"Campus\" TEXT, \n\t\"Location\" TEXT, \n\t\"County\" TEXT, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Id\")\n)\n/*\nColumns in Campuses and 3 examples in each column for high cardinality columns :\nId : 17, 21, 9\nCampus : California State University-Chico, California State University-Sacramento, San Francisco State University\nLocation : San Bernardino, Seaside, Pomona\nCounty : Monterey, San Bernardino, Los Angeles\nYear : 1913, 1989, 1949\n*/\n\n \nCREATE TABLE list (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Grade\" INTEGER, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/*\nColumns in list and 3 examples in each column for high cardinality columns :\nLastName : HOUTCHENS, GELL, FLACHS\nFirstName : RAY, EMILE, PATRINA\nClassroom : 109, 110, 106\n*/\n/*\nColumns in list and all categories for low cardinality columns :\nGrade : 1, 2, 5, 4, 6, 3, 0\n*/\n \nCREATE TABLE gymnast (\n\t\"Gymnast_ID\" INTEGER, \n\t\"Floor_Exercise_Points\" REAL, \n\t\"Pommel_Horse_Points\" REAL, \n\t\"Rings_Points\" REAL, \n\t\"Vault_Points\" REAL, \n\t\"Parallel_Bars_Points\" REAL, \n\t\"Horizontal_Bar_Points\" REAL, \n\t\"Total_Points\" REAL, \n\tPRIMARY KEY (\"Gymnast_ID\"), \n\tFOREIGN KEY(\"Gymnast_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in gymnast and all categories for low cardinality columns :\nGymnast_ID : 1, 2, 7, 8, 4, 6, 10\nFloor_Exercise_Points : 9.762, 9.65, 9.412, 9.725, 9.7, 9.687, 8.987\nPommel_Horse_Points : 9.625, 9.325, 9.675, 9.525, 9.737, 9.75, 9.712\nRings_Points : 9.512, 9.625, 9.3, 9.712, 9.475, 9.75, 9.487\nVault_Points : 9.537, 9.762, 9.65, 9.637, 9.55, 9.575\nParallel_Bars_Points : 9.625, 9.787, 9.762, 9.562, 9.587, 9.725, 9.5\nHorizontal_Bar_Points : 9.55, 9.725, 9.412, 9.737, 9.5, 9.75\nTotal_Points : 57.398, 57.924, 57.649, 57.374, 57.436, 58.061, 57.424\n*/\n \nCREATE TABLE head (\n\t\"head_ID\" INTEGER, \n\tname TEXT, \n\tborn_state TEXT, \n\tage REAL, \n\tPRIMARY KEY (\"head_ID\")\n)\n/*\nColumns in head and all categories for low cardinality columns :\nhead_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nname : Jeff Maggert, Pádraig Harrington, Billy Mayfair, K. J. Choi, Dudley Hart, Sergio García, Stewart Cink, Tiger Woods, Nick Faldo, Franklin Langham\nborn_state : Delaware, Connecticut, Alabama, California, Florida\nage : 69.0, 67.0, 68.0, 53.0, 56.0, 52.0, 50.0, 43.0\n*/\n \nCREATE TABLE trust (\n\tsource_u_id INTEGER NOT NULL, \n\ttarget_u_id INTEGER NOT NULL, \n\ttrust INTEGER NOT NULL, \n\tFOREIGN KEY(target_u_id) REFERENCES useracct (u_id), \n\tFOREIGN KEY(source_u_id) REFERENCES useracct (u_id)\n)\n/*\nColumns in trust and all categories for low cardinality columns :\nsource_u_id : 1, 2, 7, 6, 3\ntarget_u_id : 2, 5, 4, 6, 3\ntrust : 1, 2, 7, 8, 4, 6, 3, 10\n*/\n \nCREATE TABLE mill (\n\tarchitect_id INTEGER, \n\tid INTEGER, \n\tlocation TEXT, \n\tname TEXT, \n\ttype TEXT, \n\tbuilt_year INTEGER, \n\tnotes TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(architect_id) REFERENCES architect (id)\n)\n/*\nColumns in mill and all categories for low cardinality columns :\narchitect_id : 1, 2, 4, 3\nid : 1, 2, 5, 4, 6, 3\nlocation : Donceel, Momalle, Fexhe-le-haut-Clocher, Othée, Pousset, Coswarem\nname : Le Vieux Molen, Moulin de Pousset, Moulin de Momalle, Moulin Bertrand, Moulin de Fexhe, Moulin du Château\ntype : Bergmolen, Grondzeiler\nbuilt_year : 1840, 1819, 1856, 1843, 1850, 1890\nnotes : Molenechos (Dutch)\n*/\n \nCREATE TABLE cinema (\n\t\"Cinema_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Openning_year\" INTEGER, \n\t\"Capacity\" INTEGER, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"Cinema_ID\")\n)\n/*\nColumns in cinema and all categories for low cardinality columns :\nCinema_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Glenmore, Oriel, Codling, Dublin Array, Glenough, Grouse Lodge, Carrowleagh, Gortahile, Mount Callan, Moneypoint\nOpenning_year : 2009, 2013, 2015, 2012, 2011, 2010\nCapacity : 330, 305, 368, 364, 325, 203, 908, 208, 1100, 225\nLocation : County Cork, County Louth, County Laois, County Tipperary, County Clare, County Dublin, County Wicklow\n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE \"PROFESSOR\" (\n\t\"EMP_NUM\" INTEGER, \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"PROF_OFFICE\" VARCHAR(50), \n\t\"PROF_EXTENSION\" VARCHAR(4), \n\t\"PROF_HIGH_DEGREE\" VARCHAR(5), \n\tFOREIGN KEY(\"EMP_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/*\nColumns in PROFESSOR and 3 examples in each column for high cardinality columns :\nEMP_NUM : 387, 301, 155\nDEPT_CODE : ECON/FIN, ART, HIST\nPROF_OFFICE : KLR 203E, BBG 208, AAK 230\nPROF_EXTENSION : 2248, 2851, 4436\n*/\n/*\nColumns in PROFESSOR and all categories for low cardinality columns :\nPROF_HIGH_DEGREE : Ph.D., MBA, MA, DBA\n*/\n \nCREATE TABLE camera_lens (\n\tid INTEGER, \n\tbrand TEXT, \n\tname TEXT, \n\tfocal_length_mm REAL, \n\tmax_aperture REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in camera_lens and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Panasonic Leica DG Summilux 25mm f /1.4 Asph., Sigma 19mm f2.8 EX DN, Sigma 30mm f2.8 DN\n*/\n/*\nColumns in camera_lens and all categories for low cardinality columns :\nbrand : Sigma, Olympus, Panasonic, Schneider Kreuznach\nfocal_length_mm : 45.0, 30.0, 15.0, 25.0, 150.0, 19.0, 14.0, 42.5, 75.0\nmax_aperture : 1.2, 8.0, 1.4, 2.0, 1.8, 2.8\n*/\n \nCREATE TABLE \"Document_Functional_Areas\" (\n\tdocument_code VARCHAR(15) NOT NULL, \n\tfunctional_area_code VARCHAR(15) NOT NULL, \n\tFOREIGN KEY(functional_area_code) REFERENCES \"Functional_Areas\" (functional_area_code), \n\tFOREIGN KEY(document_code) REFERENCES \"Documents\" (document_code)\n)\n/*\nColumns in Document_Functional_Areas and 3 examples in each column for high cardinality columns :\ndocument_code : 217, 930, 958\n*/\n/*\nColumns in Document_Functional_Areas and all categories for low cardinality columns :\nfunctional_area_code : 1, 8, 9\n*/\n" }, { "role": "user", "content": "show the name of all bridges that was designed by american archtect, and sort the result by the bridge feet length." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: bridge, architect.\nFrom these tables, I'll be using the following columns: bridge.name, bridge.architect_id, architect.id, architect.nationality, bridge.length_feet.\nThe SQL query I'll be generating is:\nSELECT t1.name FROM bridge AS t1 JOIN architect AS t2 ON t1.architect_id = t2.id WHERE t2.nationality = 'American' ORDER BY t1.length_feet" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE nomination (\n\t\"Artwork_ID\" INTEGER, \n\t\"Festival_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\", \"Festival_ID\"), \n\tFOREIGN KEY(\"Festival_ID\") REFERENCES festival_detail (\"Festival_ID\"), \n\tFOREIGN KEY(\"Artwork_ID\") REFERENCES artwork (\"Artwork_ID\")\n)\n/*\nColumns in nomination and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 8, 4, 3, 9\nFestival_ID : 1, 2, 5\nResult : Nominated, Won\n*/\n \nCREATE TABLE grapes (\n\t\"ID\" INTEGER, \n\t\"Grape\" TEXT, \n\t\"Color\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tUNIQUE (\"Grape\")\n)\n/*\nColumns in grapes and 3 examples in each column for high cardinality columns :\nID : 17, 9, 16\nGrape : Marsanne, Tempranillo, Malbec\n*/\n/*\nColumns in grapes and all categories for low cardinality columns :\nColor : Red, White\n*/\n \nCREATE TABLE phone_market (\n\t\"Market_ID\" INTEGER, \n\t\"Phone_ID\" TEXT, \n\t\"Num_of_stock\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\", \"Phone_ID\"), \n\tFOREIGN KEY(\"Phone_ID\") REFERENCES phone (\"Phone_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/*\nColumns in phone_market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 6\nPhone_ID : 1, 2, 4, 3\nNum_of_stock : 2232, 874, 4324, 682, 908, 1632\n*/\n \nCREATE TABLE \"Party_Forms\" (\n\tparty_id INTEGER NOT NULL, \n\tform_id INTEGER NOT NULL, \n\tdate_completion_started DATETIME NOT NULL, \n\tform_status_code VARCHAR(15) NOT NULL, \n\tdate_fully_completed DATETIME, \n\tPRIMARY KEY (party_id, form_id), \n\tFOREIGN KEY(form_id) REFERENCES \"Forms\" (form_id), \n\tFOREIGN KEY(party_id) REFERENCES \"Parties\" (party_id)\n)\n/*\nColumns in Party_Forms and 3 examples in each column for high cardinality columns :\ndate_completion_started : 2017-11-29 03:11:38, 2017-12-17 11:29:47, 2017-12-04 16:57:31\ndate_fully_completed : 2018-02-15 23:09:42, 2018-02-11 16:46:10, 2018-02-04 05:57:01\n*/\n/*\nColumns in Party_Forms and all categories for low cardinality columns :\nparty_id : 13, 11, 2, 5, 7, 8, 6, 15, 9\nform_id : 2, 5, 4, 6, 3\nform_status_code : Work In Progress, Not Started, Completed, Partially Completed\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Performance\" (\n\t\"SongId\" INTEGER, \n\t\"Bandmate\" INTEGER, \n\t\"StagePosition\" TEXT, \n\tPRIMARY KEY (\"SongId\", \"Bandmate\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"Bandmate\") REFERENCES \"Band\" (\"Id\")\n)\n/*\nColumns in Performance and all categories for low cardinality columns :\nSongId : \nBandmate : \nStagePosition : \n*/\n \nCREATE TABLE results (\n\t\"resultId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\t\"constructorId\" INTEGER, \n\tnumber INTEGER, \n\tgrid INTEGER, \n\tposition TEXT, \n\t\"positionText\" TEXT, \n\t\"positionOrder\" INTEGER, \n\tpoints REAL, \n\tlaps TEXT, \n\ttime TEXT, \n\tmilliseconds TEXT, \n\t\"fastestLap\" TEXT, \n\trank TEXT, \n\t\"fastestLapTime\" TEXT, \n\t\"fastestLapSpeed\" TEXT, \n\t\"statusId\" INTEGER, \n\tPRIMARY KEY (\"resultId\"), \n\tFOREIGN KEY(\"constructorId\") REFERENCES constructors (\"constructorId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/*\nColumns in results and 3 examples in each column for high cardinality columns :\nresultId : 87, 56, 65\ndriverId : 17, 21, 9\nconstructorId : 1, 11, 2\nnumber : 17, 21, 9\ngrid : 17, 21, 9\nposition : , 19, 17\npositionText : 19, 17, 9\npositionOrder : 17, 21, 9\nlaps : 53, 56, 65\ntime : , 58.244, 45.832\nmilliseconds : , 5838976, 5855526\nfastestLap : , 53, 56\nrank : , 19, 17\nfastestLapTime : , 01:26.7, 01:20.7\nfastestLapSpeed : , 151.021, 118.872\nstatusId : 1, 20, 11\n*/\n/*\nColumns in results and all categories for low cardinality columns :\nraceId : 26, 20, 25, 24, 23, 21, 19, 18, 27, 22\npoints : 8.0, 3.0, 10.0, 1.0, 0.0, 6.0, 2.0, 4.0, 5.0\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n*/\n/*\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE station (\n\t\"Station_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Annual_entry_exit\" REAL, \n\t\"Annual_interchanges\" REAL, \n\t\"Total_Passengers\" REAL, \n\t\"Location\" TEXT, \n\t\"Main_Services\" TEXT, \n\t\"Number_of_Platforms\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nName : London King's Cross, London Waterloo, Birmingham New Street\nAnnual_entry_exit : 20.551, 21.797, 36.609\nAnnual_interchanges : 9.157, 2.064, 9.489\nTotal_Passengers : 26.892, 29.658, 30.896\nMain_Services : South Eastern Main Line, Great Eastern Main Line Lea Valley Lines, Midland Main Line Thameslink High-Speed 1 Eurostar\n*/\n/*\nColumns in station and all categories for low cardinality columns :\nLocation : Glasgow, London, Birmingham\nNumber_of_Platforms : 13, 15, 17, 6, 12, 19, 18\n*/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Rank_in_series\" INTEGER, \n\t\"Number_in_season\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Directed_by\" TEXT, \n\t\"Original_air_date\" TEXT, \n\t\"Production_code\" TEXT, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/*\nColumns in film and all categories for low cardinality columns :\nFilm_ID : 1, 2, 5, 4, 3\nRank_in_series : 26, 28, 30, 27, 29\nNumber_in_season : 1, 2, 5, 4, 3\nTitle : The Case: Off the Record, The Case of the Mystery Weekend, The Case of the Piggy Banker, The Case of the Smart Dummy, The Case of the Bermuda Triangle\nDirected_by : Bill Schreiner, Jesus Salvador Treviño\nOriginal_air_date : October 5–9, 1992, September 28–October 2, 1992, October 19–23, 1992, October 12–16, 1992, September 21–25, 1992\nProduction_code : 50241–50245, 50011–50015, 50251–50255, 50231–50235, 50021–50025\n*/\n \nCREATE TABLE \"Albums\" (\n\t\"AId\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Label\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"AId\")\n)\n/*\nColumns in Albums and all categories for low cardinality columns :\nAId : \nTitle : \nYear : \nLabel : \nType : \n*/\n \nCREATE TABLE \"Dorm\" (\n\tdormid INTEGER, \n\tdorm_name VARCHAR(20), \n\tstudent_capacity INTEGER, \n\tgender VARCHAR(1)\n)\n/*\nColumns in Dorm and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\ndorm_name : University Hovels, Fawlty Towers, Anonymous Donor Hall, Smith Hall, Bud Jones Hall, Dorm-plex 2000, Grad Student Asylum\nstudent_capacity : 116, 400, 355, 40, 128, 85, 256\ngender : F, X, M\n*/\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/*\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n*/\n \nCREATE TABLE \"Participants_in_Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Participant_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Event_ID\", \"Participant_ID\"), \n\tFOREIGN KEY(\"Participant_ID\") REFERENCES \"Participants\" (\"Participant_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/*\nColumns in Participants_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n*/\n/*\nColumns in Participants_in_Events and all categories for low cardinality columns :\nParticipant_ID : 26, 86, 37, 90, 36, 96, 66, 63, 60, 64\n*/\n \nCREATE TABLE review (\n\ta_id INTEGER NOT NULL, \n\tu_id INTEGER NOT NULL, \n\ti_id INTEGER NOT NULL, \n\trating INTEGER DEFAULT NULL, \n\trank INTEGER DEFAULT NULL, \n\tPRIMARY KEY (a_id), \n\tFOREIGN KEY(i_id) REFERENCES item (i_id), \n\tFOREIGN KEY(u_id) REFERENCES useracct (u_id)\n)\n/*\nColumns in review and all categories for low cardinality columns :\na_id : 1, 2, 5, 7, 4, 6, 3\nu_id : 1, 2\ni_id : 1, 5, 7, 4, 3\nrating : 7, 10, 5, 6\nrank : 1, 2, 5, 7, 4, 6, 3\n*/\n" }, { "role": "user", "content": "How many book clubs are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: .\nThe SQL query I'll be generating is:\nSELECT count(*) FROM book_club" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE protein (\n\tcommon_name TEXT, \n\tprotein_name TEXT, \n\tdivergence_from_human_lineage REAL, \n\taccession_number TEXT, \n\tsequence_length REAL, \n\tsequence_identity_to_human_protein TEXT, \n\t\"Institution_id\" TEXT, \n\tPRIMARY KEY (common_name), \n\tFOREIGN KEY(\"Institution_id\") REFERENCES \"Institution\" (\"Institution_id\")\n)\n/*\nColumns in protein and all categories for low cardinality columns :\ncommon_name : Tropical Clawed Frog, porkworm, body louse, southern house mosquito, purple sea urchin\nprotein_name : uncharacterized protein LOC578090, conserved hypothetical protein, Centromeric protein E, putative, surface antigen repeat family protein, uncharacterized protein C20orf117-like\ndivergence_from_human_lineage : 937.5, 742.9, 782.7, 371.2\naccession_number : XP_003380263.1, XP_002942331.1, XP_783370.2, XP_002429877.1, XP_001843754.1\nsequence_length : 2030.0, 1587.0, 2086.0, 1584.0, 1878.0\nsequence_identity_to_human_protein : 30%, 47%, 36%, 39%, 32%\nInstitution_id : 1, 5, 9, 3\n*/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n*/\n \nCREATE TABLE shop (\n\t\"Shop_ID\" INTEGER, \n\t\"Address\" TEXT, \n\t\"Num_of_staff\" TEXT, \n\t\"Score\" REAL, \n\t\"Open_Year\" TEXT, \n\tPRIMARY KEY (\"Shop_ID\")\n)\n/*\nColumns in shop and all categories for low cardinality columns :\nShop_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAddress : 414 E. 12th Street, 324 E. 11th Street, 1330 Baltimore Street, 1201 Walnut Street, 909 Main Street, 1111 Main Street, 2345 McGee Street, 1200 Main Street, 1100 Main Street, 909 Walnut Street\nNum_of_staff : 16, 13, 28, 24, 34, 23, 19, 42, 27, 425\nScore : 36.0, 30.0, 42.0, 28.0, 38.0, 40.0, 32.0\nOpen_Year : 2008, 2010, 2011, 2006\n*/\n \nCREATE TABLE \"Employees\" (\n\t\"Employee_ID\" INTEGER NOT NULL, \n\t\"Role_Code\" CHAR(15) NOT NULL, \n\t\"Employee_Name\" VARCHAR(255), \n\t\"Gender_MFU\" CHAR(1) NOT NULL, \n\t\"Date_of_Birth\" DATETIME NOT NULL, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Employee_ID\"), \n\tFOREIGN KEY(\"Role_Code\") REFERENCES \"Roles\" (\"Role_Code\")\n)\n/*\nColumns in Employees and 3 examples in each column for high cardinality columns :\nEmployee_ID : 173, 159, 38\nEmployee_Name : Harley, Armani, Leo\nDate_of_Birth : 1973-04-04 21:41:22, 1977-07-04 16:25:21, 1979-09-20 12:50:15\n*/\n/*\nColumns in Employees and all categories for low cardinality columns :\nRole_Code : PR, HR, PT, MG, ED\nGender_MFU : , 1\nOther_Details : None\n*/\n \nCREATE TABLE station (\n\t\"Station_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Annual_entry_exit\" REAL, \n\t\"Annual_interchanges\" REAL, \n\t\"Total_Passengers\" REAL, \n\t\"Location\" TEXT, \n\t\"Main_Services\" TEXT, \n\t\"Number_of_Platforms\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nName : London King's Cross, London Waterloo, Birmingham New Street\nAnnual_entry_exit : 20.551, 21.797, 36.609\nAnnual_interchanges : 9.157, 2.064, 9.489\nTotal_Passengers : 26.892, 29.658, 30.896\nMain_Services : South Eastern Main Line, Great Eastern Main Line Lea Valley Lines, Midland Main Line Thameslink High-Speed 1 Eurostar\n*/\n/*\nColumns in station and all categories for low cardinality columns :\nLocation : Glasgow, London, Birmingham\nNumber_of_Platforms : 13, 15, 17, 6, 12, 19, 18\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Birth_Date\" TEXT, \n\t\"Birth_Place\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 4, 6, 3\nName : Ty Conklin, Jake Gardiner, Al Montoya, Mark Fayne, Jack Campbell, Cam Fowler\nHeight : 215.0, 182.0, 195.0, 205.0, 192.0, 196.0\nWeight : 89.0, 100.0, 90.0, 102.0, 80.0, 92.0\nBirth_Date : December 5, 1991, May 5, 1987, July 4, 1990, February 13, 1985, March 30, 1976, January 1, 1992\nBirth_Place : Farmington Hills, Michigan, Anchorage, Alaska, Glenview, Illinois, Nashua, New Hampshire, Minnetonka, Minnesota, Port Huron, Michigan\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_address_id INTEGER NOT NULL, \n\tnickname VARCHAR(80), \n\tfirst_name VARCHAR(80), \n\tmiddle_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tdate_of_birth DATETIME, \n\tdate_joined_staff DATETIME, \n\tdate_left_staff DATETIME, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(staff_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/*\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nnickname : ymiller, weissnat.vincenzo, nicholaus92\nfirst_name : Jedidiah, Eulalia, Camylle\nmiddle_name : Clarabelle, Maiya, Ulices\nlast_name : Sawayn, Maggio, Kuphal\ndate_of_birth : 2005-05-02 06:23:36, 2003-01-16 06:29:11, 2007-06-11 20:03:28\ndate_joined_staff : 2017-08-27 19:19:44, 2017-04-27 03:21:26, 2016-06-06 08:54:28\ndate_left_staff : 2018-03-08 12:31:16, 2018-03-10 15:25:00, 2018-03-24 10:11:08\n*/\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_address_id : 1, 3, 13, 2, 5, 7, 4, 6, 12, 14\n*/\n \nCREATE TABLE stadium (\n\t\"ID\" INTEGER, \n\tname TEXT, \n\t\"Capacity\" INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"Opening_year\" INTEGER, \n\tPRIMARY KEY (\"ID\")\n)\n/*\nColumns in stadium and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nname : Northumberland Development Project, Fisht Olympic Stadium, Ferenc Puskás Stadion, Nou Mestalla, Yubileyniy Stadium, Estadio La Peineta, Baku Olympic Stadium, Arena Baltika, Stade des Lumières, Gazprom Arena\nCapacity : 61556, 69501, 56250, 68000, 47659, 45015, 67500, 75000, 65000\nCity : London, Sochi, Budapest, Saint Petersburg, Baku, Kaliningrad, Madrid, Valencia, Lyon, Saransk\nCountry : Spain, France, England, Russia, Azerbaijan, Hungary\nOpening_year : 2004, 2005, 2007, 2006\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE gas_station (\n\t\"Station_ID\" INTEGER, \n\t\"Open_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Manager_Name\" TEXT, \n\t\"Vice_Manager_Name\" TEXT, \n\t\"Representative_Name\" TEXT, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in gas_station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nOpen_Year : 2004, 2009, 2005\nLocation : Channel Hill, Newport Rd, Herne Ave\n*/\n/*\nColumns in gas_station and all categories for low cardinality columns :\nManager_Name : Simon Cope Derek Marloe, BryanDenman, Luke Rowe, BrianWingrave, Bryan Taylor, Jon Rowe, Tony Bristow, Tom Whit, SimonMarloe, Colin Denman\nVice_Manager_Name : TonyBristow, Russell Brown, Russell Denman, Martin Freeman, Simon Gaywood, James Holland-Leader, James Colin , JameMarloe, Steve Parsons, Martin Garnham\nRepresentative_Name : Andrew Russell, Chris Pyatt, Tim Read, Ray Hughes, Simon Gaywood, Tony Gibb, Clive Burr, Courtney Rowe, Rob Jefferies , Dave Edwards Roger \n*/\n \nCREATE TABLE \"Employees\" (\n\temployee_id INTEGER NOT NULL, \n\trole_code CHAR(15) NOT NULL, \n\temployee_name VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (employee_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Roles\" (role_code)\n)\n/*\nColumns in Employees and all categories for low cardinality columns :\nemployee_id : 1, 2, 5, 7, 8, 3\nrole_code : MG, ED, PR, PT\nemployee_name : Koby, Erling, Kenyon, Haley, Jordyn, Clemens\nother_details : f, b, h, v, u\n*/\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n" }, { "role": "user", "content": "Count the number of book clubs." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: .\nThe SQL query I'll be generating is:\nSELECT count(*) FROM book_club" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE swimmer (\n\t\"ID\" INTEGER, \n\tname TEXT, \n\t\"Nationality\" TEXT, \n\tmeter_100 REAL, \n\tmeter_200 TEXT, \n\tmeter_300 TEXT, \n\tmeter_400 TEXT, \n\tmeter_500 TEXT, \n\tmeter_600 TEXT, \n\tmeter_700 TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"ID\")\n)\n/*\nColumns in swimmer and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3\nname : Przemysław Stańczyk, Grant Hackett, Federico Colbertaldo, Sébastien Rouault, Craig Stevens, Sergiy Fesenko, Oussama Mellouli, Ryan Cochrane\nNationality : Italy, Canada, Australia, Ukraine, France, Tunisia, Poland\nmeter_100 : 57.35, 57.31, 55.67, 57.84, 57.66, 57.34\nmeter_200 : 1:57.21, 1:54.40, 1:57.26, 1:57.10, 1:56.44, 1:56.34, 1:56.77\nmeter_300 : 2:56.64, 2:56.95, 2:57.10, 2:55.94, 2:53.46, 2:55.90, 2:56.02, 2:56.04\nmeter_400 : 3:55.72, 3:55.49, 3:55.36, 3:57.00, 3:52.93, 3:56.34, 3:57.12, 3:55.37\nmeter_500 : 4:54.48, 4:56.96, 4:55.08, 4:54.21, 4:54.19, 4:52.85, 4:57.03, 4:56.15\nmeter_600 : 5:54.45, 5:53.03, 5:52.92, 5:56.99, 5:56.31, 5:53.53, 5:57.10, 5:52.59\nmeter_700 : 6:55.07, 6:57.44, 6:50.91, 6:53.34, 6:52.58, 6:57.69, 6:50.80, 6:52.69\nTime : 7:55.39, 7:52.04, 7:47.91, 7:53.43, 7:46.95, 7:56.56, 7:48.67, 7:49.98\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Video_Games\" (\n\t\"GameID\" INTEGER, \n\t\"GName\" VARCHAR(40), \n\t\"GType\" VARCHAR(40), \n\tPRIMARY KEY (\"GameID\")\n)\n/*\nColumns in Video_Games and all categories for low cardinality columns :\nGameID : 1, 2, 5, 4, 6, 3\nGName : Call of Destiny, Grand Term Assignment, The Vanishing of Eric Calder, Europe is the Universe, Works of Widenius, RNG Stone\nGType : Role-playing game, Collectible card game, Frist-person shooter, Walking Simulator, Grand strategy, Massively multiplayer online game\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_first_name VARCHAR(20), \n\tcustomer_last_name VARCHAR(20), \n\tcustomer_address VARCHAR(255), \n\tcustomer_phone VARCHAR(255), \n\tcustomer_email VARCHAR(255), \n\tother_customer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_first_name : Armani, Bryce, Nat\ncustomer_last_name : Swift, Lind, Huels\ncustomer_address : 6478 Moen Isle Suite 910\nSchimmelmouth, VT 96364-4898, 47286 Mraz Park Apt. 424\nJocelynfurt, OH 59023-2787, 094 Julianne Mill\nWebstertown, KY 91980-4004\ncustomer_phone : (415)237-0701x3115, 679-845-8645x94312, 284.749.0453\ncustomer_email : kyra.murazik@example.org, schaden.katrina@example.net, huels.antonina@example.com\n*/\n/*\nColumns in Customers and all categories for low cardinality columns :\nother_customer_details : None\n*/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/*\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n*/\n \nCREATE TABLE company (\n\t\"Company_ID\" REAL, \n\t\"Name\" TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Industry\" TEXT, \n\t\"Sales_in_Billion\" REAL, \n\t\"Profits_in_Billion\" REAL, \n\t\"Assets_in_Billion\" REAL, \n\t\"Market_Value_in_Billion\" REAL, \n\tPRIMARY KEY (\"Company_ID\")\n)\n/*\nColumns in company and 3 examples in each column for high cardinality columns :\nCompany_ID : 3.0, 8.0, 11.0\nName : PetroChina, Berkshire Hathaway, Petrobras\nSales_in_Billion : 82.6, 110.8, 143.7\nProfits_in_Billion : 15.7, 20.1, 25.1\nAssets_in_Billion : 213.0, 331.1, 1313.9\nMarket_Value_in_Billion : 237.4, 213.7, 164.3\n*/\n/*\nColumns in company and all categories for low cardinality columns :\nHeadquarters : UK, China, Brazil, France, Russia, USA, Germany, Netherlands\nIndustry : Retailing, Automotive, Conglomerate, Oil and gas, Banking\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Attribute_Definitions\" (\n\tattribute_id INTEGER, \n\tattribute_name VARCHAR(30), \n\tattribute_data_type VARCHAR(10), \n\tPRIMARY KEY (attribute_id)\n)\n/*\nColumns in Attribute_Definitions and all categories for low cardinality columns :\nattribute_id : 1, 2, 4, 3\nattribute_name : Yellow, Sweet, Green, Black\nattribute_data_type : Bool\n*/\n \nCREATE TABLE \"Document_Drafts\" (\n\tdocument_id INTEGER NOT NULL, \n\tdraft_number INTEGER NOT NULL, \n\tdraft_details VARCHAR(255), \n\tPRIMARY KEY (document_id, draft_number), \n\tFOREIGN KEY(document_id) REFERENCES \"Documents\" (document_id)\n)\n/*\nColumns in Document_Drafts and 3 examples in each column for high cardinality columns :\ndocument_id : 1, 13, 20\ndraft_number : 1, 16, 20\ndraft_details : m, b, e\n*/\n\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE cinema (\n\t\"Cinema_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Openning_year\" INTEGER, \n\t\"Capacity\" INTEGER, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"Cinema_ID\")\n)\n/*\nColumns in cinema and all categories for low cardinality columns :\nCinema_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Glenmore, Oriel, Codling, Dublin Array, Glenough, Grouse Lodge, Carrowleagh, Gortahile, Mount Callan, Moneypoint\nOpenning_year : 2009, 2013, 2015, 2012, 2011, 2010\nCapacity : 330, 305, 368, 364, 325, 203, 908, 208, 1100, 225\nLocation : County Cork, County Louth, County Laois, County Tipperary, County Clare, County Dublin, County Wicklow\n*/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Train_Num\" TEXT, \n\t\"Name\" TEXT, \n\t\"From\" TEXT, \n\t\"Arrival\" TEXT, \n\t\"Railway_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/*\nColumns in train and all categories for low cardinality columns :\nTrain_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nTrain_Num : 57136, 57135, 16032, 12140, 51195, 12139, 16031, 11401, 16094\nName : Wardha-Ballarshah Pass, Nagpur-Kazipet Pass, Ballarshah-Mumbai Pass, Nandigram Exp, Lucknow-Chennai Exp, Sewagram Exp, Andaman Exp, Kazipet-Nagpur Pass\nFrom : Lucknow, Ballarshah, Nagpur, Kazipet, Mumbai CST, Jammu Tawi, Wardha, Chennai\nArrival : 23:39, 08:54, 23:44, 05:09, 09:48, 13:28, 13:04, 09:08\nRailway_ID : 1, 2, 5, 7, 3, 10, 9\n*/\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/*\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n*/\n \nCREATE TABLE \"Order_Items\" (\n\t\"Order_Item_ID\" INTEGER NOT NULL, \n\t\"Order_ID\" INTEGER NOT NULL, \n\t\"Product_ID\" INTEGER NOT NULL, \n\t\"Order_Quantity\" VARCHAR(288), \n\t\"Other_Item_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Order_Item_ID\"), \n\tFOREIGN KEY(\"Order_ID\") REFERENCES \"Customer_Orders\" (\"Order_ID\"), \n\tFOREIGN KEY(\"Product_ID\") REFERENCES \"Products\" (\"Product_ID\")\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\nOrder_Item_ID : 1, 13, 11\nOrder_ID : 1, 10, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nProduct_ID : 300, 233, 46, 156, 83, 179, 216, 81, 273\nOrder_Quantity : 1, 2\nOther_Item_Details : None\n*/\n" }, { "role": "user", "content": "show the titles, and authors or editors for all books made after the year 1989." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: book_title, author_or_editor.\nThe SQL query I'll be generating is:\nSELECT book_title , author_or_editor FROM book_club WHERE YEAR > 1989" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Student_Course_Registrations\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tregistration_date DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(course_id) REFERENCES \"Courses\" (course_id)\n)\n/*\nColumns in Student_Course_Registrations and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 121\ncourse_id : 302, 303, 301, 305\nregistration_date : 2008-11-08 10:35:13, 2008-11-07 10:35:13, 2008-11-05 10:35:13, 2008-11-04 10:35:13, 2008-11-14 10:35:13, 2008-11-06 10:35:13, 2008-10-04 10:35:13\n*/\n \nCREATE TABLE storm (\n\t\"Storm_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Dates_active\" TEXT, \n\t\"Max_speed\" INTEGER, \n\t\"Damage_millions_USD\" REAL, \n\t\"Number_Deaths\" INTEGER, \n\tPRIMARY KEY (\"Storm_ID\")\n)\n/*\nColumns in storm and all categories for low cardinality columns :\nStorm_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Three, One, Five, Nine, Four, Seven, Six, Eight, 9 cyclones, Two\nDates_active : August5–August14, May19 –October26, August3–August10, September22–September28, September7–September17, May19–May25, October24–October26, August26–September2, September18–September25, October20–October24\nMax_speed : 1007, 988, 977, 961, 972, 1002, 983, 995\nDamage_millions_USD : 1.49, 10.75, 13.0, 29.3, 4.05, 0.039\nNumber_Deaths : 2, 7, 52, 3, 71, 0\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE journal (\n\t\"Journal_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Theme\" TEXT, \n\t\"Sales\" INTEGER, \n\tPRIMARY KEY (\"Journal_ID\")\n)\n/*\nColumns in journal and 3 examples in each column for high cardinality columns :\nJournal_ID : 1, 16, 13\nDate : September 23, 2001, November 25, 2001, October 21, 2001\nTheme : Cleveland Browns, at Baltimore Ravens, Baltimore Ravens\nSales : 3798, 5342, 2804\n*/\n\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE \"Club\" (\n\t\"ClubID\" INTEGER, \n\t\"ClubName\" VARCHAR(40), \n\t\"ClubDesc\" VARCHAR(1024), \n\t\"ClubLocation\" VARCHAR(40), \n\tPRIMARY KEY (\"ClubID\")\n)\n/*\nColumns in Club and all categories for low cardinality columns :\nClubID : 1, 2, 4, 3\nClubName : Bootup Baltimore, Pen and Paper Gaming, Tennis Club, Hopkins Student Enterprises\nClubDesc : Venture capital fund for student business., A competitive tennis club., Refurbish computers; teach kids and adults about computer basics., Play pen and paper games on campus.\nClubLocation : HHH, AKW\n*/\n \nCREATE TABLE \"Invoice_Line_Items\" (\n\torder_item_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tproduct_title VARCHAR(80), \n\tproduct_quantity VARCHAR(50), \n\tproduct_price DECIMAL(19, 4), \n\tderived_product_cost DECIMAL(19, 4), \n\tderived_vat_payable DECIMAL(19, 4), \n\tderived_total_cost DECIMAL(19, 4), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Invoice_Line_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 11, 10, 5\nproduct_price : 556.3600, 727.4100, 559.9500\nderived_product_cost : 73.1400, 28.1800, 249.1900\nderived_total_cost : 82.7700, 71.2200, 78.2600\n*/\n/*\nColumns in Invoice_Line_Items and all categories for low cardinality columns :\ninvoice_number : 1, 11, 5, 15, 7, 14, 12, 10, 9\nproduct_id : 1, 11, 5, 15, 8, 6, 14, 3, 10, 9\nproduct_title : prod_name\nproduct_quantity : 1, 2, 5, 7, 8, 4, 6, 3, 9\nderived_vat_payable : None\n*/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\taddress_content VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tother_address_details VARCHAR(255), \n\tPRIMARY KEY (address_id)\n)\n/*\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\naddress_content : 92865 Margaretta Streets Suite 467, 78614 Maybell Alley Suite 057, 9443 Boyle Route Suite 857\ncity : South Meghanview, South Bellaland, Gleasonmouth\nzip_postcode : 721, 255, 416\nstate_province_county : RhodeIsland, Arizona, Mississippi\n*/\n/*\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\nother_address_details : None\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Customer_Contact_Channels\" (\n\tcustomer_id INTEGER NOT NULL, \n\tchannel_code VARCHAR(15) NOT NULL, \n\tactive_from_date DATETIME NOT NULL, \n\tactive_to_date DATETIME, \n\tcontact_number VARCHAR(50) NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Contact_Channels and 3 examples in each column for high cardinality columns :\nactive_from_date : 2017-05-25 16:08:45, 2017-06-21 06:41:19, 2018-03-01 10:17:18\nactive_to_date : 2018-03-16 14:00:15, 2018-02-24 00:57:39, 2018-03-20 14:01:12\ncontact_number : 940.035.6435x0225, 846.043.4809x0426, 1-968-863-4947x96956\n*/\n/*\nColumns in Customer_Contact_Channels and all categories for low cardinality columns :\ncustomer_id : 13, 2, 5, 15, 4, 6, 14, 3, 10, 9\nchannel_code : Mobile, Email, Fax, Handheld, Cell\n*/\n \nCREATE TABLE wrestler (\n\t\"Wrestler_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Reign\" TEXT, \n\t\"Days_held\" TEXT, \n\t\"Location\" TEXT, \n\t\"Event\" TEXT, \n\tPRIMARY KEY (\"Wrestler_ID\")\n)\n/*\nColumns in wrestler and all categories for low cardinality columns :\nWrestler_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Fishman, El Samurai §, Rey Misterio Sr., Último Dragón §, Shinjiro Otani §, Gran Hamada, Jushin Liger §, Villaño IV, The Great Sasuke §, El Samurai\nReign : 1, 2\nDays_held : 1, 113, 35, 56, 183, 1285, 960, 344, 99, 54\nLocation : Nagoya , Japan, Tijuana , Mexico, Sapporo , Japan, Tokyo , Japan, Osaka , Japan\nEvent : Wrestling World 1997, Live event\n*/\n \nCREATE TABLE technician (\n\ttechnician_id REAL, \n\t\"Name\" TEXT, \n\t\"Team\" TEXT, \n\t\"Starting_Year\" REAL, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (technician_id)\n)\n/*\nColumns in technician and all categories for low cardinality columns :\ntechnician_id : 3.0, 8.0, 10.0, 1.0, 7.0, 2.0, 6.0, 9.0, 4.0, 5.0\nName : Mark Sewell, John Brown, Mickey Cochrane, Joe Sewell, Tony Sewell, Joe Cochrane, Eddie Collins, Charlie Hollocher, Lou Boudreau\nTeam : CHC, NYY, CLE, PHA, CWS\nStarting_Year : 2013.0, 2016.0, 2003.0, 2006.0, 2005.0, 2002.0, 2009.0, 2012.0\nAge : 38, 37, 45, 46, 28, 36, 32, 47, 43, 35\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Elimination\" (\n\t\"Elimination_ID\" TEXT, \n\t\"Wrestler_ID\" TEXT, \n\t\"Team\" TEXT, \n\t\"Eliminated_By\" TEXT, \n\t\"Elimination_Move\" TEXT, \n\t\"Time\" TEXT, \n\tPRIMARY KEY (\"Elimination_ID\"), \n\tFOREIGN KEY(\"Wrestler_ID\") REFERENCES wrestler (\"Wrestler_ID\")\n)\n/*\nColumns in Elimination and all categories for low cardinality columns :\nElimination_ID : 1, 2, 5, 4, 6, 3\nWrestler_ID : 1, 2, 5, 7, 4, 9\nTeam : Team Orton, Team Batista\nEliminated_By : Punk, Henry, Benjamin, Orton, Batista, Rhodes\nElimination_Move : Spear, World's Strongest Slam, Silver Spoon DDT, Rope hung DDT, Paydirt, Go To Sleep\nTime : 13:06, 14:22, 07:38, 14:32, 00:11, 10:45\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n*/\n \nCREATE TABLE competition_record (\n\t\"Competition_ID\" INTEGER, \n\t\"Farm_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Competition_ID\", \"Farm_ID\"), \n\tFOREIGN KEY(\"Farm_ID\") REFERENCES farm (\"Farm_ID\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES farm_competition (\"Competition_ID\")\n)\n/*\nColumns in competition_record and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 3\nFarm_ID : 1, 2, 5, 7, 8, 4, 3\nRank : 1, 2, 4, 3\n*/\n" }, { "role": "user", "content": "What are the titles and authors or editors that correspond to books made after 1989?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: book_title, author_or_editor.\nThe SQL query I'll be generating is:\nSELECT book_title , author_or_editor FROM book_club WHERE YEAR > 1989" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Department\" (\n\t\"DNO\" INTEGER, \n\t\"Division\" VARCHAR(2), \n\t\"DName\" VARCHAR(25), \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\t\"DPhone\" INTEGER, \n\tPRIMARY KEY (\"DNO\")\n)\n/*\nColumns in Department and 3 examples in each column for high cardinality columns :\nDNO : 170, 560, 540\nDName : Economics, Mechanical Engineering, English\nRoom : 206, 312, 440\nBuilding : Krieger, NEB, Latrobe\nDPhone : 7499, 7601, 7119\n*/\n/*\nColumns in Department and all categories for low cardinality columns :\nDivision : EN, AS\n*/\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/*\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n*/\n/*\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n*/\n \nCREATE TABLE \"Allergy_Type\" (\n\t\"Allergy\" VARCHAR(20), \n\t\"AllergyType\" VARCHAR(20), \n\tPRIMARY KEY (\"Allergy\")\n)\n/*\nColumns in Allergy_Type and 3 examples in each column for high cardinality columns :\nAllergy : Soy, Milk, Eggs\n*/\n/*\nColumns in Allergy_Type and all categories for low cardinality columns :\nAllergyType : food, animal, environmental\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Bookings\" (\n\tbooking_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tbooking_status_code VARCHAR(10) NOT NULL, \n\treturned_damaged_yn VARCHAR(40), \n\tbooking_start_date DATETIME, \n\tbooking_end_date DATETIME, \n\tcount_hired VARCHAR(40), \n\tamount_payable DECIMAL(19, 4), \n\tamount_of_discount DECIMAL(19, 4), \n\tamount_outstanding DECIMAL(19, 4), \n\tamount_of_refund DECIMAL(19, 4), \n\tPRIMARY KEY (booking_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Bookings and 3 examples in each column for high cardinality columns :\nbooking_id : 1, 13, 11\nbooking_start_date : 2016-04-25 11:04:18, 2016-11-06 20:54:26, 2017-04-28 08:35:56\nbooking_end_date : 2018-03-04 21:42:45, 2018-02-19 21:53:31, 2017-10-02 07:28:09\ncount_hired : 843, 298, 236\namount_payable : 214.3900, 306.2600, 386.9200\namount_of_discount : 48.7300, 61.5500, 45.0600\namount_outstanding : 26.0400, 66.0100, 93.8800\namount_of_refund : 135.9400, 126.1000, 124.9500\n*/\n/*\nColumns in Bookings and all categories for low cardinality columns :\ncustomer_id : 11, 10, 7, 8, 3, 15, 9\nbooking_status_code : Provisional, Confirmed\nreturned_damaged_yn : 1, 0\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Rating\" (\n\t\"rID\" INTEGER, \n\t\"mID\" INTEGER, \n\tstars INTEGER, \n\t\"ratingDate\" DATE, \n\tFOREIGN KEY(\"mID\") REFERENCES \"Movie\" (\"mID\"), \n\tFOREIGN KEY(\"rID\") REFERENCES \"Reviewer\" (\"rID\")\n)\n/*\nColumns in Rating and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nmID : 108, 106, 103, 101, 104, 107\nstars : 2, 4, 5, 3\nratingDate : 2011-01-20, 2011-01-09, 2011-01-30, 2011-01-22, 2011-01-27, 2011-01-19, 2011-01-02, None, 2011-01-12, 2011-01-15\n*/\n \nCREATE TABLE \"All_Documents\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Date_Stored\" DATETIME, \n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Name\" CHAR(255), \n\t\"Document_Description\" CHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Document_Type_Code\") REFERENCES \"Ref_Document_Types\" (\"Document_Type_Code\"), \n\tFOREIGN KEY(\"Date_Stored\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\")\n)\n/*\nColumns in All_Documents and 3 examples in each column for high cardinality columns :\nDocument_ID : 120, 230, 11\nDocument_Name : Cats and me, Alan CV, Hua Mulan\n*/\n/*\nColumns in All_Documents and all categories for low cardinality columns :\nDate_Stored : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1987-11-05 06:11:22, 1986-10-14 17:53:39, 1976-06-15 03:40:06, 1997-03-10 15:24:00, 1995-01-01 03:52:11, 2008-06-08 12:45:38\nDocument_Type_Code : RV, BK, PR, CV\nDocument_Description : None\nOther_Details : None\n*/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/*\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n*/\n \nCREATE TABLE debate_people (\n\t\"Debate_ID\" INTEGER, \n\t\"Affirmative\" INTEGER, \n\t\"Negative\" INTEGER, \n\t\"If_Affirmative_Win\" BOOLEAN, \n\tPRIMARY KEY (\"Debate_ID\", \"Affirmative\", \"Negative\"), \n\tFOREIGN KEY(\"Negative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Affirmative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Debate_ID\") REFERENCES debate (\"Debate_ID\")\n)\n/*\nColumns in debate_people and all categories for low cardinality columns :\nDebate_ID : 1, 5, 4, 6, 3\nAffirmative : 1, 2, 4, 5\nNegative : 7, 10, 8, 6\nIf_Affirmative_Win : True\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\t\"Club_name\" TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" INTEGER, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/*\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nClub_name : BK Häcken, Helsingborgs IF, Djurgårdens IF, Gefle IF, Halmstads BK, AIK\nRegion : Korea, UK, France, Russia, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n*/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/*\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Years_Played\" TEXT, \n\t\"Total_WL\" TEXT, \n\t\"Singles_WL\" TEXT, \n\t\"Doubles_WL\" TEXT, \n\t\"Team\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\")\n)\n/*\nColumns in player and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nPlayer : Seol Jae-Min (none), An Jae-Sung, Kim Young-Jun (474), Cho Soong-Jae (630), Jeong Suk-Young (793), Lim Yong-Kyu (288), Im Kyu-tae (492), Bae Nam-Ju, Kim Hyun-Joon (908), Chung Hong (717)\nYears_Played : 8 (2003–2005, 2007–2011), 2 (1988, 1990), 3 (2005, 2007–2008), 1 (2011), 2 (2010–2011), 2 (2010-2011), 3 (2009–2011), 4 (2003–2004, 2010–2011)\nTotal_WL : 1–3, 2–2, 0–0, 6–9, 2–0, 3–4, 4–3, 6–4, 7–6, 1–2\nSingles_WL : 6–3, 5–6, 0–0, 1–0, 2–1, 0–2, 5–7, 3–2, 1–2\nDoubles_WL : 1–3, 2–2, 0–0, 1–0, 1–1, 2–0, 0–1, 1–2\nTeam : 1, 2, 8, 4, 6\n*/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/*\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n*/\n \nCREATE TABLE \"Attribute_Definitions\" (\n\tattribute_id INTEGER, \n\tattribute_name VARCHAR(30), \n\tattribute_data_type VARCHAR(10), \n\tPRIMARY KEY (attribute_id)\n)\n/*\nColumns in Attribute_Definitions and all categories for low cardinality columns :\nattribute_id : 1, 2, 4, 3\nattribute_name : Yellow, Sweet, Green, Black\nattribute_data_type : Bool\n*/\n" }, { "role": "user", "content": "Show all distinct publishers for books." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT DISTINCT publisher FROM book_club" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Visits_Restaurant\" (\n\t\"StuID\" INTEGER, \n\t\"ResID\" INTEGER, \n\t\"Time\" TIMESTAMP, \n\t\"Spent\" FLOAT, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\")\n)\n/*\nColumns in Visits_Restaurant and all categories for low cardinality columns :\nStuID : 1001, 1032\nResID : 1, 2\nTime : 2017-10-09 18:15:00, 2017-10-08 13:00:30\nSpent : 13.2, 6.53\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Product_Characteristics\" (\n\tproduct_id INTEGER NOT NULL, \n\tcharacteristic_id INTEGER NOT NULL, \n\tproduct_characteristic_value VARCHAR(50), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(characteristic_id) REFERENCES \"Characteristics\" (characteristic_id)\n)\n/*\nColumns in Product_Characteristics and all categories for low cardinality columns :\nproduct_id : 1, 13, 11, 5, 7, 8, 6, 12, 14\ncharacteristic_id : 13, 10, 11, 2, 4, 6, 12, 3, 15\nproduct_characteristic_value : high, low, medium\n*/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/*\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n*/\n \nCREATE TABLE \"Catalog_Structure\" (\n\tcatalog_level_number INTEGER, \n\tcatalog_id INTEGER NOT NULL, \n\tcatalog_level_name VARCHAR(50), \n\tPRIMARY KEY (catalog_level_number), \n\tFOREIGN KEY(catalog_id) REFERENCES \"Catalogs\" (catalog_id)\n)\n/*\nColumns in Catalog_Structure and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\ncatalog_id : 1, 8, 2\ncatalog_level_name : Product, Category, Sub-Category\n*/\n \nCREATE TABLE user_profiles (\n\tuid INTEGER NOT NULL, \n\tname VARCHAR(255) DEFAULT NULL, \n\temail VARCHAR(255) DEFAULT NULL, \n\tpartitionid INTEGER DEFAULT NULL, \n\tfollowers INTEGER DEFAULT NULL, \n\tPRIMARY KEY (uid)\n)\n/*\nColumns in user_profiles and all categories for low cardinality columns :\nuid : 1, 2, 5, 7, 4, 6, 3\nname : Natalie Portman, Mary, Black Widow\n, Tyler Swift, Celine Dion, Iron Man, Susan\nemail : susan@gmail.com\n, ts@superstar.com\n, cd@superstar.com, np@superstar.com, ts@richest.com, bw@superhero.com, Mary@yale.edu\npartitionid : 1, 2, 5, 23, 10\nfollowers : 23927492, 100, 94375428, 35425845, 890, 99999998, 6662425\n*/\n \nCREATE TABLE \"Customer_Addresses\" (\n\tcustomer_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME NOT NULL, \n\taddress_type VARCHAR(10) NOT NULL, \n\tdate_to DATETIME, \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Addresses and 3 examples in each column for high cardinality columns :\ndate_from : 2010-12-29 11:01:39, 2013-05-06 00:49:45, 2012-08-31 15:41:03\ndate_to : 2018-03-22 02:54:10, 2018-02-25 15:34:58, 2018-03-02 23:42:49\n*/\n/*\nColumns in Customer_Addresses and all categories for low cardinality columns :\ncustomer_id : 1, 2, 5, 7, 8, 4, 14, 3, 12, 10\naddress_id : 1, 11, 2, 5, 7, 6, 3, 10, 9\naddress_type : Flat, Apartment, House\n*/\n \nCREATE TABLE station (\n\t\"Station_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Annual_entry_exit\" REAL, \n\t\"Annual_interchanges\" REAL, \n\t\"Total_Passengers\" REAL, \n\t\"Location\" TEXT, \n\t\"Main_Services\" TEXT, \n\t\"Number_of_Platforms\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nName : London King's Cross, London Waterloo, Birmingham New Street\nAnnual_entry_exit : 20.551, 21.797, 36.609\nAnnual_interchanges : 9.157, 2.064, 9.489\nTotal_Passengers : 26.892, 29.658, 30.896\nMain_Services : South Eastern Main Line, Great Eastern Main Line Lea Valley Lines, Midland Main Line Thameslink High-Speed 1 Eurostar\n*/\n/*\nColumns in station and all categories for low cardinality columns :\nLocation : Glasgow, London, Birmingham\nNumber_of_Platforms : 13, 15, 17, 6, 12, 19, 18\n*/\n \nCREATE TABLE \"Student_Course_Attendance\" (\n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_attendance DATETIME NOT NULL, \n\tPRIMARY KEY (student_id, course_id), \n\tFOREIGN KEY(student_id, course_id) REFERENCES \"Student_Course_Registrations\" (student_id, course_id)\n)\n/*\nColumns in Student_Course_Attendance and all categories for low cardinality columns :\nstudent_id : 151, 141, 171, 161, 111, 121\ncourse_id : 302, 303, 301, 305\ndate_of_attendance : 2012-09-09 11:44:34, 2012-05-09 11:44:34, 2014-01-09 11:44:34, 2014-04-09 11:44:34, 2008-11-04 10:35:13, 2012-04-09 11:44:34, 2013-04-09 11:44:34, 2015-04-09 11:44:34\n*/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n*/\n \nCREATE TABLE station_company (\n\t\"Station_ID\" INTEGER, \n\t\"Company_ID\" INTEGER, \n\t\"Rank_of_the_Year\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\", \"Company_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES gas_station (\"Station_ID\")\n)\n/*\nColumns in station_company and all categories for low cardinality columns :\nStation_ID : 1, 11, 7, 4, 6, 10\nCompany_ID : 1, 6, 3, 10, 9\nRank_of_the_Year : 1, 13, 2, 4, 3, 9\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Member_Name\" TEXT, \n\t\"Party_ID\" TEXT, \n\t\"In_office\" TEXT, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/*\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 13, 11\nMember_Name : Hon Bob Baldwin, Hon Kim Beazley, Kerry Bartlett\nIn_office : 1980–2007, 1996–2007, 1990–2010\n*/\n/*\nColumns in member and all categories for low cardinality columns :\nParty_ID : 1, 2, 3\n*/\n \nCREATE TABLE dependent (\n\t\"Essn\" INTEGER, \n\t\"Dependent_name\" TEXT, \n\t\"Sex\" TEXT, \n\t\"Bdate\" TEXT, \n\t\"Relationship\" TEXT, \n\tPRIMARY KEY (\"Essn\", \"Dependent_name\")\n)\n/*\nColumns in dependent and all categories for low cardinality columns :\nEssn : 333445555, 123456789, 987654321\nDependent_name : Alice, Michael, Theodore, Abner, Joy, Elizabeth\nSex : F, M\nBdate : 1986-04-05, 1988-01-04, 1967-05-05, 1983-10-25, 1958-05-03, 1942-02-28, 1988-12-30\nRelationship : Daughter, Son, Spouse\n*/\n \nCREATE TABLE \"Research_Staff\" (\n\tstaff_id INTEGER, \n\temployer_organisation_id INTEGER NOT NULL, \n\tstaff_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(employer_organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/*\nColumns in Research_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_details : aspernatur, dicta, ab\n*/\n/*\nColumns in Research_Staff and all categories for low cardinality columns :\nemployer_organisation_id : 1, 2, 5, 8, 4, 6, 3, 10, 9\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE section (\n\tcourse_id VARCHAR(8), \n\tsec_id VARCHAR(8), \n\tsemester VARCHAR(6), \n\tyear NUMERIC(4, 0), \n\tbuilding VARCHAR(15), \n\troom_number VARCHAR(7), \n\ttime_slot_id VARCHAR(4), \n\tPRIMARY KEY (course_id, sec_id, semester, year), \n\tFOREIGN KEY(course_id) REFERENCES course (course_id), \n\tFOREIGN KEY(building, room_number) REFERENCES classroom (building, room_number), \n\tCHECK (semester in ('Fall', 'Winter', 'Spring', 'Summer')), \n\tCHECK (year > 1701 and year < 2100)\n)\n/*\nColumns in section and 3 examples in each column for high cardinality columns :\ncourse_id : 561, 304, 927\nbuilding : Nassau, Garfield, Saucon\nroom_number : 261, 375, 757\ntime_slot_id : E, N, K\n*/\n/*\nColumns in section and all categories for low cardinality columns :\nsec_id : 1, 2, 3\nsemester : Fall, Spring\nyear : 2004, 2009, 2001, 2005, 2008, 2006, 2002, 2003, 2010, 2007\n*/\n" }, { "role": "user", "content": "What are all the different book publishers?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT DISTINCT publisher FROM book_club" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Tracklists\" (\n\t\"AlbumId\" INTEGER, \n\t\"Position\" INTEGER, \n\t\"SongId\" INTEGER, \n\tPRIMARY KEY (\"AlbumId\", \"Position\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"AlbumId\") REFERENCES \"Albums\" (\"AId\")\n)\n/*\nColumns in Tracklists and all categories for low cardinality columns :\nAlbumId : \nPosition : \nSongId : \n*/\n \nCREATE TABLE wedding (\n\t\"Church_ID\" INTEGER, \n\t\"Male_ID\" INTEGER, \n\t\"Female_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Church_ID\", \"Male_ID\", \"Female_ID\"), \n\tFOREIGN KEY(\"Female_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Male_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Church_ID\") REFERENCES church (\"Church_ID\")\n)\n/*\nColumns in wedding and all categories for low cardinality columns :\nChurch_ID : 1, 4, 5, 3\nMale_ID : 1, 7, 5, 3\nFemale_ID : 8, 2, 4, 6\nYear : 2015, 2016, 2014\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tparent_product_id INTEGER, \n\tproduction_type_code VARCHAR(15) NOT NULL, \n\tunit_price DECIMAL(19, 4), \n\tproduct_name VARCHAR(80), \n\tproduct_color VARCHAR(20), \n\tproduct_size VARCHAR(20), \n\tPRIMARY KEY (product_id), \n\tFOREIGN KEY(production_type_code) REFERENCES \"Product_Categories\" (production_type_code)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nunit_price : 49.6200, 563.5800, 729.0900\nproduct_name : Coffee Bean, Art History, Beer Menus\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nparent_product_id : 1, 2, 5, 7, 8, 4, 6, 9\nproduction_type_code : Food, Books, Electronics, DVDs\nproduct_color : Red, Yellow, Black\nproduct_size : Small, Medium, Large\n*/\n \nCREATE TABLE injury_accident (\n\tgame_id INTEGER, \n\tid INTEGER, \n\t\"Player\" TEXT, \n\t\"Injury\" TEXT, \n\t\"Number_of_matches\" TEXT, \n\t\"Source\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(game_id) REFERENCES game (id)\n)\n/*\nColumns in injury_accident and 3 examples in each column for high cardinality columns :\ngame_id : 1, 11, 2\nid : 1, 13, 11\nPlayer : Dejan Stanković, Thiago Motta (2), Iván Córdoba\nInjury : Sustained a biceps femoris strain in his left leg, First-degree strain left hamstring muscles, Sustained posterior thigh strains in his left leg\n*/\n/*\nColumns in injury_accident and all categories for low cardinality columns :\nNumber_of_matches : 1, 4 (6), 2, 7 (17), 1 (2), 4, 12, 3, 10\nSource : inter.it\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE school_bus (\n\t\"School_ID\" INTEGER, \n\t\"Driver_ID\" INTEGER, \n\t\"Years_Working\" INTEGER, \n\t\"If_full_time\" BOOLEAN, \n\tPRIMARY KEY (\"School_ID\", \"Driver_ID\"), \n\tFOREIGN KEY(\"Driver_ID\") REFERENCES driver (\"Driver_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in school_bus and all categories for low cardinality columns :\nSchool_ID : 1, 5, 7, 4, 3\nDriver_ID : 7, 4, 3, 10, 9\nYears_Working : 2, 8, 6, 3, 10\nIf_full_time : True\n*/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER NOT NULL, \n\taddress_details VARCHAR(255), \n\tPRIMARY KEY (address_id)\n)\n/*\nColumns in Addresses and all categories for low cardinality columns :\naddress_id : 1, 2, 5, 7, 8, 4, 6, 3, 9, 0\naddress_details : PT, IT, MX, US, DE, IE, ES\n*/\n \nCREATE TABLE submission (\n\t\"Submission_ID\" INTEGER, \n\t\"Scores\" REAL, \n\t\"Author\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\")\n)\n/*\nColumns in submission and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nScores : 89.0, 79.0, 82.0, 83.0, 92.0, 93.0, 72.0, 78.0\nAuthor : Rick Engles, Andy Bolton, Jeff Lloyd, Don Bitterlich, Steve Raible, Steve Niehaus, Sherman Smith, Randy Johnson, Sammy Green, Steve Myer\nCollege : Fisk, Georgia Tech, Tulsa, Georgia, Miami (OH), West Texas State, Temple, Notre Dame, Florida, New Mexico\n*/\n \nCREATE TABLE \"Behavior_Incident\" (\n\tincident_id INTEGER, \n\tincident_type_code VARCHAR(10) NOT NULL, \n\tstudent_id INTEGER NOT NULL, \n\tdate_incident_start DATETIME, \n\tdate_incident_end DATETIME, \n\tincident_summary VARCHAR(255), \n\trecommendations VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (incident_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(incident_type_code) REFERENCES \"Ref_Incident_Type\" (incident_type_code)\n)\n/*\nColumns in Behavior_Incident and 3 examples in each column for high cardinality columns :\nincident_id : 1, 13, 11\nstudent_id : 1, 13, 11\ndate_incident_start : 2018-01-31 10:51:13, 2017-08-27 03:21:30, 2017-05-02 12:52:09\ndate_incident_end : 2018-03-22 02:10:35, 2018-03-06 14:44:37, 2018-03-16 14:37:20\n*/\n/*\nColumns in Behavior_Incident and all categories for low cardinality columns :\nincident_type_code : VIOLENCE, DISTURB, NOISE\nincident_summary : None\nrecommendations : None, Transfer schools\nother_details : None\n*/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"City\" TEXT, \n\t\"Hanzi\" TEXT, \n\t\"Hanyu_Pinyin\" TEXT, \n\t\"Regional_Population\" INTEGER, \n\t\"GDP\" REAL, \n\tPRIMARY KEY (\"City_ID\")\n)\n/*\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 13, 11\nCity : Shanghai, Changzhou ( Jiangsu ), Jinhua ( Zhejiang )\nHanzi : 台州, 金华/ 金華, 上海\nHanyu_Pinyin : Shàoxīng, Tāizhōu, Hángzhōu\nRegional_Population : 8700400, 7605689, 4912200\nGDP : 1919.57, 408.02, 266.81\n*/\n\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n*/\n \nCREATE TABLE \"Mailshot_Customers\" (\n\tmailshot_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\toutcome_code VARCHAR(15) NOT NULL, \n\tmailshot_customer_date DATETIME, \n\tFOREIGN KEY(mailshot_id) REFERENCES \"Mailshot_Campaigns\" (mailshot_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Mailshot_Customers and 3 examples in each column for high cardinality columns :\nmailshot_customer_date : 2018-03-05 20:48:13, 2018-03-20 23:40:02, 2018-03-03 15:29:56\n*/\n/*\nColumns in Mailshot_Customers and all categories for low cardinality columns :\nmailshot_id : 20, 18, 15, 7, 17, 4, 6, 10\ncustomer_id : 1, 13, 11, 2, 4, 6, 14, 3, 9\noutcome_code : Order, No Response\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n*/\n \nCREATE TABLE music_festival (\n\t\"ID\" INTEGER, \n\t\"Music_Festival\" TEXT, \n\t\"Date_of_ceremony\" TEXT, \n\t\"Category\" TEXT, \n\t\"Volume\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Volume\") REFERENCES volume (\"Volume_ID\")\n)\n/*\nColumns in music_festival and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMusic_Festival : 34th Japan Academy Prize, 35th China Academy Prize, 37th Canadian Academy Prize, 40th Japan Academy Prize, 34th USA Academy Prize, 34th England Academy Prize, 37th Sweden Academy Prize, 36th Japan Academy Prize, 34th European Academy Prize\nDate_of_ceremony : 18 February 2011\nCategory : Best Sound Song, Best Song, Best Lyrics\nVolume : 1, 2, 5, 7, 8, 4, 6, 3, 9\nResult : Nominated, Awarded\n*/\n \nCREATE TABLE \"Channels\" (\n\t\"Channel_ID\" INTEGER NOT NULL, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Channel_ID\")\n)\n/*\nColumns in Channels and 3 examples in each column for high cardinality columns :\nChannel_ID : 1, 13, 11\nOther_Details : 668, 249, 943\n*/\n\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Block\" (\n\t\"BlockFloor\" INTEGER NOT NULL, \n\t\"BlockCode\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"BlockFloor\", \"BlockCode\")\n)\n/*\nColumns in Block and all categories for low cardinality columns :\nBlockFloor : 1, 2, 4, 3\nBlockCode : 1, 2, 3\n*/\n" }, { "role": "user", "content": "Show the years, book titles, and publishers for all books, in descending order by year." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: YEAR, book_title, publisher.\nThe SQL query I'll be generating is:\nSELECT YEAR , book_title , publisher FROM book_club ORDER BY YEAR DESC" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE festival_detail (\n\t\"Festival_ID\" INTEGER, \n\t\"Festival_Name\" TEXT, \n\t\"Chair_Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Festival_ID\")\n)\n/*\nColumns in festival_detail and all categories for low cardinality columns :\nFestival_ID : 1, 2, 5, 4, 3\nFestival_Name : Gobel Awards, LA Awards, Flower Awards, Panasonic Awards, Cherry Awards\nChair_Name : Doug Ford, Charles Coody, Lucy Lu, Arnold Palmer, Raymond Floyd\nLocation : United States\nYear : 2007, 2008, 2010, 2006\nNum_of_Audience : 160, 152, 161, 155\n*/\n \nCREATE TABLE record (\n\t\"ID\" INTEGER, \n\t\"Result\" TEXT, \n\t\"Swimmer_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\tPRIMARY KEY (\"Swimmer_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Swimmer_ID\") REFERENCES swimmer (\"ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"ID\")\n)\n/*\nColumns in record and 3 examples in each column for high cardinality columns :\nID : 1, 13, 11\n*/\n/*\nColumns in record and all categories for low cardinality columns :\nResult : Loss, Win, NC\nSwimmer_ID : 1, 2, 5, 4, 6, 3\nEvent_ID : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/*\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n*/\n \nCREATE TABLE \"Has_amenity\" (\n\tdormid INTEGER, \n\tamenid INTEGER, \n\tFOREIGN KEY(amenid) REFERENCES \"Dorm_amenity\" (amenid), \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid)\n)\n/*\nColumns in Has_amenity and 3 examples in each column for high cardinality columns :\namenid : 902, 955, 930\n*/\n/*\nColumns in Has_amenity and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n*/\n \nCREATE TABLE \"Candidate_Assessments\" (\n\tcandidate_id INTEGER NOT NULL, \n\tqualification CHAR(15) NOT NULL, \n\tassessment_date DATETIME NOT NULL, \n\tasessment_outcome_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (candidate_id, qualification), \n\tFOREIGN KEY(candidate_id) REFERENCES \"Candidates\" (candidate_id)\n)\n/*\nColumns in Candidate_Assessments and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 111, 121\nqualification : A, C, D, B\nassessment_date : 2010-04-06 11:44:34, 2010-04-17 11:44:34, 2010-04-09 11:44:34, 2010-04-07 11:44:34, 2010-04-05 11:44:34\nasessment_outcome_code : Fail, Pass\n*/\n \nCREATE TABLE ship (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Tonnage\" INTEGER, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/*\nColumns in ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Clan McTavish, Farringford, Appam, Author, Dromonby, Corbridge, Trader, Ariadne\nType : Battle ship, Cargo ship\nNationality : United States, United Kingdom\nTonnage : 3035, 3146, 7781, 3496, 3687, 5816, 3627, 3608\n*/\n \nCREATE TABLE \"Ref_Colors\" (\n\tcolor_code VARCHAR(15), \n\tcolor_description VARCHAR(80), \n\tPRIMARY KEY (color_code)\n)\n/*\nColumns in Ref_Colors and all categories for low cardinality columns :\ncolor_code : 1, 2, 5, 7, 8, 4, 3, 9\ncolor_description : blue, green, gray, red, black, yellow, purple, white\n*/\n \nCREATE TABLE \"Institution\" (\n\t\"Institution_id\" TEXT, \n\t\"Institution\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Type\" TEXT, \n\t\"Enrollment\" INTEGER, \n\t\"Team\" TEXT, \n\t\"Primary_Conference\" TEXT, \n\tbuilding_id TEXT, \n\tPRIMARY KEY (\"Institution_id\"), \n\tFOREIGN KEY(building_id) REFERENCES building (building_id)\n)\n/*\nColumns in Institution and 3 examples in each column for high cardinality columns :\nInstitution_id : 1, 2, 5\nInstitution : Ave Maria University, Lindenwood University–Belleville, Point University\nLocation : Mayville, North Dakota, Jacksonville, Florida, Babson Park, Florida\nEnrollment : 967, 616, 3102\nTeam : Gyrenes, Comets, Warriors\n*/\n/*\nColumns in Institution and all categories for low cardinality columns :\nFounded : 1937.0, 1881.0, 1927.0, 2003.0, 1883.0, 1866.0, 1998.0, 1884.0, 1889.0, 1890.0\nType : Public, Tribal, Private\nPrimary_Conference : MCAC, CalPac, Gulf Coast (GCAC), AAC, none, The Sun\nbuilding_id : 1, 2, 5, 7, 4, 3, 0\n*/\n \nCREATE TABLE circuits (\n\t\"circuitId\" INTEGER, \n\t\"circuitRef\" TEXT, \n\tname TEXT, \n\tlocation TEXT, \n\tcountry TEXT, \n\tlat REAL, \n\tlng REAL, \n\talt TEXT, \n\turl TEXT, \n\tPRIMARY KEY (\"circuitId\")\n)\n/*\nColumns in circuits and 3 examples in each column for high cardinality columns :\ncircuitId : 53, 56, 65\ncircuitRef : brands_hatch, valencia, kyalami\nname : N_rburgring, Circuito da Boavista, Reims-Gueux\nlocation : Yeongam County, Shanghai, Lisbon\ncountry : Sweden, Turkey, Australia\nlat : 42.475, 47.95, 40.3725\nlng : 39.9578, 1.00458, -74.6099\nurl : http://en.wikipedia.org/wiki/Riverside_International_Raceway, http://en.wikipedia.org/wiki/Charade_Circuit, http://en.wikipedia.org/wiki/Dijon-Prenois\n*/\n/*\nColumns in circuits and all categories for low cardinality columns :\nalt : , 10\n*/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/*\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n*/\n \nCREATE TABLE \"Services\" (\n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Service_Type_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (\"Service_ID\")\n)\n/*\nColumns in Services and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nService_Type_Code : Marriage, Birth Proof, Death Proof, Property Change\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_name VARCHAR(80), \n\tcustomer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_name : George, Beulah, Leilani\ncustomer_details : dicta, quidem, deleniti\n*/\n\n \nCREATE TABLE \"Apartment_Bookings\" (\n\tapt_booking_id INTEGER NOT NULL, \n\tapt_id INTEGER, \n\tguest_id INTEGER NOT NULL, \n\tbooking_status_code CHAR(15) NOT NULL, \n\tbooking_start_date DATETIME, \n\tbooking_end_date DATETIME, \n\tPRIMARY KEY (apt_booking_id), \n\tFOREIGN KEY(apt_id) REFERENCES \"Apartments\" (apt_id), \n\tFOREIGN KEY(guest_id) REFERENCES \"Guests\" (guest_id), \n\tUNIQUE (apt_booking_id)\n)\n/*\nColumns in Apartment_Bookings and 3 examples in each column for high cardinality columns :\napt_booking_id : 365, 577, 343\nbooking_start_date : 2017-07-03 14:15:56, 2017-03-04 02:23:49, 2016-06-07 05:05:18\nbooking_end_date : 2017-10-07 11:38:48, 2018-02-19 16:59:08, 2017-10-03 01:56:21\n*/\n/*\nColumns in Apartment_Bookings and all categories for low cardinality columns :\napt_id : 11, 2, 15, 7, 8, 4, 6, 12, 10, 9\nguest_id : 3, 13, 2, 5, 7, 8, 4, 12, 14, 15\nbooking_status_code : Provisional, Confirmed\n*/\n \nCREATE TABLE head (\n\t\"head_ID\" INTEGER, \n\tname TEXT, \n\tborn_state TEXT, \n\tage REAL, \n\tPRIMARY KEY (\"head_ID\")\n)\n/*\nColumns in head and all categories for low cardinality columns :\nhead_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nname : Jeff Maggert, Pádraig Harrington, Billy Mayfair, K. J. Choi, Dudley Hart, Sergio García, Stewart Cink, Tiger Woods, Nick Faldo, Franklin Langham\nborn_state : Delaware, Connecticut, Alabama, California, Florida\nage : 69.0, 67.0, 68.0, 53.0, 56.0, 52.0, 50.0, 43.0\n*/\n \nCREATE TABLE \"Services\" (\n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Service_Type_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (\"Service_ID\")\n)\n/*\nColumns in Services and all categories for low cardinality columns :\nService_ID : 8, 2, 5, 6\nService_Type_Code : Marriage, Birth Proof, Death Proof, Property Change\n*/\n \nCREATE TABLE country (\n\t\"Country_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Area\" INTEGER, \n\t\"Languages\" TEXT, \n\tPRIMARY KEY (\"Country_ID\")\n)\n/*\nColumns in country and all categories for low cardinality columns :\nCountry_ID : 1, 2, 3\nName : Austria, Sweden, Finland\nPopulation : 8206524, 9047752, 5261008\nArea : 83871, 338145, 449964\nLanguages : Swedish, Finnish Swedish, German\n*/\n \nCREATE TABLE \"Vocals\" (\n\t\"SongId\" INTEGER, \n\t\"Bandmate\" INTEGER, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"SongId\", \"Bandmate\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"Bandmate\") REFERENCES \"Band\" (\"Id\")\n)\n/*\nColumns in Vocals and all categories for low cardinality columns :\nSongId : \nBandmate : \nType : \n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n" }, { "role": "user", "content": "What are the years, titles, and publishers for all books, ordered by year descending?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: YEAR, book_title, publisher.\nThe SQL query I'll be generating is:\nSELECT YEAR , book_title , publisher FROM book_club ORDER BY YEAR DESC" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE station (\n\t\"Station_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Annual_entry_exit\" REAL, \n\t\"Annual_interchanges\" REAL, \n\t\"Total_Passengers\" REAL, \n\t\"Location\" TEXT, \n\t\"Main_Services\" TEXT, \n\t\"Number_of_Platforms\" INTEGER, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nName : London King's Cross, London Waterloo, Birmingham New Street\nAnnual_entry_exit : 20.551, 21.797, 36.609\nAnnual_interchanges : 9.157, 2.064, 9.489\nTotal_Passengers : 26.892, 29.658, 30.896\nMain_Services : South Eastern Main Line, Great Eastern Main Line Lea Valley Lines, Midland Main Line Thameslink High-Speed 1 Eurostar\n*/\n/*\nColumns in station and all categories for low cardinality columns :\nLocation : Glasgow, London, Birmingham\nNumber_of_Platforms : 13, 15, 17, 6, 12, 19, 18\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Purchases\" (\n\tpurchase_transaction_id INTEGER NOT NULL, \n\tpurchase_details VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(purchase_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/*\nColumns in Purchases and 3 examples in each column for high cardinality columns :\npurchase_transaction_id : 1, 13, 11\npurchase_details : t, i, o\n*/\n\n \nCREATE TABLE volume (\n\t\"Volume_ID\" INTEGER, \n\t\"Volume_Issue\" TEXT, \n\t\"Issue_Date\" TEXT, \n\t\"Weeks_on_Top\" REAL, \n\t\"Song\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\tPRIMARY KEY (\"Volume_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in volume and all categories for low cardinality columns :\nVolume_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nVolume_Issue : 46:5, 46:16, 46:14-15, 45:15, 45:21-22, 45:16, 46:6-8, 45:14 §, 46:10, 46:9\nIssue_Date : 16 May - 30 May, 6 June, 27 December 1986 - 10 January, 28 February - 7 March, 13 June, 24 January, 9 May, 17 January, 11 July - 18 July, 25 July\nWeeks_on_Top : 3.0, 1.0, 2.0\nSong : Head to Toe , Always , With or Without You , Looking for a New Love, La Isla Bonita , The Way, Everybody Have Fun Tonight , Touch Me (I Want Your Body) , (I Just) Died in Your Arms , Walk Like an Egyptian \nArtist_ID : 1, 2, 5, 4, 6\n*/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/*\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Sex\" TEXT, \n\t\"Name\" TEXT, \n\t\"Date_of_Birth\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nSex : F, M\nName : Vincent Montméat, Frantz Granvorka, Loïc De Kergret, Philippe Barça-Cysique, Guillaume Samica, Stéphane Antiga, Dominique Daquin, Laurent Capet, Hubert Henno\nDate_of_Birth : 20.08.1970, 10.03.1976, 05.05.1972, 28.09.1981, 22.04.1977, 01.09.1977, 10.11.1972, 06.10.1976, 03.02.1976\nHeight : 196.0, 195.0, 197.0, 188.0, 193.0, 200.0, 202.0, 194.0\nWeight : 89.0, 82.0, 85.0, 88.0, 90.0, 92.0, 83.0, 94.0\n*/\n \nCREATE TABLE browser (\n\tid INTEGER, \n\tname TEXT, \n\tmarket_share REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in browser and all categories for low cardinality columns :\nid : 1, 2, 4, 3\nname : Opera, Internet Explorer, Safari, Firefox\nmarket_share : 18.11, 8.54, 28.96, 1.2\n*/\n \nCREATE TABLE manager (\n\t\"Manager_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Working_year_starts\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Level\" INTEGER, \n\tPRIMARY KEY (\"Manager_ID\")\n)\n/*\nColumns in manager and all categories for low cardinality columns :\nManager_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ben Curtis, Sandy Lyle, Todd Hamilton, David Duval, Tiger Woods, Greg Norman, Nick Faldo\nCountry : United States, Australia, Scotland, England\nWorking_year_starts : 2004, 1993, 2001, 1985, 1999, 2006, 2003\nAge : 46, 45, 55, 48, 52, 47, 51\nLevel : 11, 5, 7, 8, 12\n*/\n \nCREATE TABLE debate_people (\n\t\"Debate_ID\" INTEGER, \n\t\"Affirmative\" INTEGER, \n\t\"Negative\" INTEGER, \n\t\"If_Affirmative_Win\" BOOLEAN, \n\tPRIMARY KEY (\"Debate_ID\", \"Affirmative\", \"Negative\"), \n\tFOREIGN KEY(\"Negative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Affirmative\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Debate_ID\") REFERENCES debate (\"Debate_ID\")\n)\n/*\nColumns in debate_people and all categories for low cardinality columns :\nDebate_ID : 1, 5, 4, 6, 3\nAffirmative : 1, 2, 4, 5\nNegative : 7, 10, 8, 6\nIf_Affirmative_Win : True\n*/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/*\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE head (\n\t\"head_ID\" INTEGER, \n\tname TEXT, \n\tborn_state TEXT, \n\tage REAL, \n\tPRIMARY KEY (\"head_ID\")\n)\n/*\nColumns in head and all categories for low cardinality columns :\nhead_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nname : Jeff Maggert, Pádraig Harrington, Billy Mayfair, K. J. Choi, Dudley Hart, Sergio García, Stewart Cink, Tiger Woods, Nick Faldo, Franklin Langham\nborn_state : Delaware, Connecticut, Alabama, California, Florida\nage : 69.0, 67.0, 68.0, 53.0, 56.0, 52.0, 50.0, 43.0\n*/\n \nCREATE TABLE \"Purchases\" (\n\tpurchase_transaction_id INTEGER NOT NULL, \n\tpurchase_details VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(purchase_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/*\nColumns in Purchases and 3 examples in each column for high cardinality columns :\npurchase_transaction_id : 1, 13, 11\npurchase_details : t, i, o\n*/\n\n \nCREATE TABLE \"Department\" (\n\t\"DNO\" INTEGER, \n\t\"Division\" VARCHAR(2), \n\t\"DName\" VARCHAR(25), \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\t\"DPhone\" INTEGER, \n\tPRIMARY KEY (\"DNO\")\n)\n/*\nColumns in Department and 3 examples in each column for high cardinality columns :\nDNO : 170, 560, 540\nDName : Economics, Mechanical Engineering, English\nRoom : 206, 312, 440\nBuilding : Krieger, NEB, Latrobe\nDPhone : 7499, 7601, 7119\n*/\n/*\nColumns in Department and all categories for low cardinality columns :\nDivision : EN, AS\n*/\n \nCREATE TABLE \"Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tdate_order_placed DATETIME NOT NULL, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\ncustomer_id : 1, 11, 10\ndate_order_placed : 2017-03-08 05:42:10, 2015-05-17 03:05:32, 2013-10-25 17:40:25\n*/\n/*\nColumns in Orders and all categories for low cardinality columns :\norder_details : None\n*/\n \nCREATE TABLE channel (\n\t\"Channel_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Owner\" TEXT, \n\t\"Share_in_percent\" REAL, \n\t\"Rating_in_percent\" REAL, \n\tPRIMARY KEY (\"Channel_ID\")\n)\n/*\nColumns in channel and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Shandong Satellite TV, CCTV-8, Hunan Satellite TV, CCTV-3, CCTV-14, CCTV-6, CCTV-13, CCTV-1, Anhui Satellite TV, CCTV-4\nOwner : HBS, Shandong Television, CCTV, Anhui Television\nShare_in_percent : 4.9, 2.33, 1.74, 2.91, 4.81, 2.6, 2.86, 3.76, 1.78, 2.73\nRating_in_percent : 0.53, 0.41, 0.32, 0.19, 0.54, 0.3, 0.31, 0.2, 0.29, 0.26\n*/\n \nCREATE TABLE budget (\n\t\"School_id\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Budgeted\" INTEGER, \n\ttotal_budget_percent_budgeted REAL, \n\t\"Invested\" INTEGER, \n\ttotal_budget_percent_invested REAL, \n\t\"Budget_invested_percent\" TEXT, \n\tPRIMARY KEY (\"School_id\", \"Year\"), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/*\nColumns in budget and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 4, 3\nYear : 2004, 2001, 2005, 1999, 2000, 2006, 2002, 2003\nBudgeted : 113531, 3666, 61283, 119527, 6803, 4979, 74849\ntotal_budget_percent_budgeted : 1.3, 2.0, 2.4\nInvested : 8335, 5840, 95542, 146102, 2134, 85249, 140102\ntotal_budget_percent_invested : 2.7, 2.2, 2.0\nBudget_invested_percent : 71.3, 228.6, 146.9, 127.6, 228.8, 122.5, 42.9, 159.3\n*/\n" }, { "role": "user", "content": "Show all publishers and the number of books for each publisher." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher , count(*) FROM book_club GROUP BY publisher" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n*/\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/*\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n*/\n \nCREATE TABLE \"Rating\" (\n\t\"rID\" INTEGER, \n\t\"mID\" INTEGER, \n\tstars INTEGER, \n\t\"ratingDate\" DATE, \n\tFOREIGN KEY(\"mID\") REFERENCES \"Movie\" (\"mID\"), \n\tFOREIGN KEY(\"rID\") REFERENCES \"Reviewer\" (\"rID\")\n)\n/*\nColumns in Rating and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nmID : 108, 106, 103, 101, 104, 107\nstars : 2, 4, 5, 3\nratingDate : 2011-01-20, 2011-01-09, 2011-01-30, 2011-01-22, 2011-01-27, 2011-01-19, 2011-01-02, None, 2011-01-12, 2011-01-15\n*/\n \nCREATE TABLE \"Claims_Processing_Stages\" (\n\t\"Claim_Stage_ID\" INTEGER NOT NULL, \n\t\"Next_Claim_Stage_ID\" INTEGER, \n\t\"Claim_Status_Name\" VARCHAR(255) NOT NULL, \n\t\"Claim_Status_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Claim_Stage_ID\")\n)\n/*\nColumns in Claims_Processing_Stages and all categories for low cardinality columns :\nClaim_Stage_ID : 1, 3\nNext_Claim_Stage_ID : 1\nClaim_Status_Name : Open, Close\nClaim_Status_Description : Open a new claim, Close a claim\n*/\n \nCREATE TABLE school_performance (\n\t\"School_Id\" INTEGER, \n\t\"School_Year\" TEXT, \n\t\"Class_A\" TEXT, \n\t\"Class_AA\" TEXT, \n\tPRIMARY KEY (\"School_Id\", \"School_Year\"), \n\tFOREIGN KEY(\"School_Id\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in school_performance and 3 examples in each column for high cardinality columns :\nSchool_Year : 1998-99, 2002-03, 1994-95\nClass_A : Skidmore-Tynan, Lindsay, Anton\nClass_AA : Buffalo, Henrietta, S&S Consolidated\n*/\n/*\nColumns in school_performance and all categories for low cardinality columns :\nSchool_Id : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Graduation_College\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 4, 6, 3\nAge : 37, 25, 30, 34, 27, 31\nName : Tom Sheehey, Reggie Lewis, Brad Lohaus, David Butler, Tim Naegeli, Darryl Kennedy, Jerry Corcoran\nNationality : United States, United Kindom\nGraduation_College : Wisconsin–Stevens Point, California, Virginia, Iowa, Northeastern, Oklahoma\n*/\n \nCREATE TABLE \"Product_Suppliers\" (\n\tproduct_id INTEGER NOT NULL, \n\tsupplier_id INTEGER NOT NULL, \n\tdate_supplied_from DATETIME NOT NULL, \n\tdate_supplied_to DATETIME, \n\ttotal_amount_purchased VARCHAR(80), \n\ttotal_value_purchased DECIMAL(19, 4), \n\tPRIMARY KEY (product_id, supplier_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(supplier_id) REFERENCES \"Suppliers\" (supplier_id)\n)\n/*\nColumns in Product_Suppliers and 3 examples in each column for high cardinality columns :\ndate_supplied_from : 2017-09-19 02:14:02, 2017-08-22 00:58:42, 2017-06-25 14:59:40\ndate_supplied_to : 2018-03-24 19:29:18, 2018-03-23 19:21:12, 2018-03-24 12:35:08\ntotal_amount_purchased : 25318.21, 32881.38, 20447.99\ntotal_value_purchased : 98086.8000, 36014.6000, 36274.5600\n*/\n/*\nColumns in Product_Suppliers and all categories for low cardinality columns :\nproduct_id : 11, 5, 7, 8, 4, 6, 14, 3, 15\nsupplier_id : 1, 2, 4, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"Official_Name\" TEXT, \n\t\"Status\" TEXT, \n\t\"Area_km_2\" REAL, \n\t\"Population\" REAL, \n\t\"Census_Ranking\" TEXT, \n\tPRIMARY KEY (\"City_ID\")\n)\n/*\nColumns in city and all categories for low cardinality columns :\nCity_ID : 1, 2, 5, 4, 3\nOfficial_Name : Plaster Rock, Aroostook, Perth-Andover, Drummond, Grand Falls/Grand-Sault\nStatus : Village, Town\nArea_km_2 : 8.91, 18.06, 8.89, 2.24, 3.09\nPopulation : 351.0, 1135.0, 775.0, 1778.0, 5706.0\nCensus_Ranking : 3460 of 5008, 1936 of 5,008, 2418 of 5008, 636 of 5008, 1442 of 5,008\n*/\n \nCREATE TABLE match_result (\n\t\"Rank\" INTEGER, \n\t\"Club_ID\" INTEGER, \n\t\"Gold\" INTEGER, \n\t\"Big_Silver\" INTEGER, \n\t\"Small_Silver\" INTEGER, \n\t\"Bronze\" INTEGER, \n\t\"Points\" INTEGER, \n\tPRIMARY KEY (\"Rank\", \"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/*\nColumns in match_result and all categories for low cardinality columns :\nRank : 1, 2, 5, 4, 6, 3\nClub_ID : 1, 2, 5, 4, 6, 3\nGold : 13, 20, 5, 7, 6, 12\nBig_Silver : 11, 7, 6, 12, 14, 9\nSmall_Silver : 16, 4, 6, 10, 9\nBronze : 7, 8, 6, 10, 9\nPoints : 89, 102, 84, 66, 139, 168\n*/\n \nCREATE TABLE region (\n\t\"Region_id\" INTEGER, \n\t\"Region_code\" TEXT, \n\t\"Region_name\" TEXT, \n\tPRIMARY KEY (\"Region_id\")\n)\n/*\nColumns in region and 3 examples in each column for high cardinality columns :\nRegion_id : 1, 13, 11\nRegion_code : AG, AI, AQ\nRegion_name : Angola, Cyprus, Denmark\n*/\n\n \nCREATE TABLE hosting_city (\n\t\"Year\" INTEGER, \n\t\"Match_ID\" INTEGER, \n\t\"Host_City\" TEXT, \n\tPRIMARY KEY (\"Year\"), \n\tFOREIGN KEY(\"Match_ID\") REFERENCES \"match\" (\"Match_ID\"), \n\tFOREIGN KEY(\"Host_City\") REFERENCES city (\"City_ID\")\n)\n/*\nColumns in hosting_city and all categories for low cardinality columns :\nYear : 2009, 2013, 2012, 2008, 2011, 2010\nMatch_ID : 1, 2, 5, 4, 6, 3\nHost_City : 1, 11, 2, 6, 12\n*/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/*\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE airport (\n\tid INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"IATA\" TEXT, \n\t\"ICAO\" TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in airport and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 9\nCity : Amsterdam, Anchorage, Bergen, Barcelona, Akureyri, Billund, Brussels, Boston, Baltimore\nCountry : Spain, Belgium, Iceland, United States, Norway, Netherlands, Denmark\nIATA : BRU, AMS, BGO, ANC, BCN, BLL, BOS, BWI, AEY\nICAO : EKBI, EHAM, KBWI, LEBL, BIAR, EBBR, PANC, KBOS, ENBR\nname : Schiphol Airport, Logan International Airport, Billund Airport, Akureyri Airport, Baltimore-Washington Airport, National Airport, Ted Stevens Airport, Bergen Airport, El Prat Airport\n*/\n" }, { "role": "user", "content": "How many books are there for each publisher?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher , count(*) FROM book_club GROUP BY publisher" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"ACCOUNTS\" (\n\tcustid BIGINT NOT NULL, \n\tname VARCHAR(64) NOT NULL, \n\tPRIMARY KEY (custid)\n)\n/*\nColumns in ACCOUNTS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nname : Wang, O'mahony, Granger, Wesley, Weeks, Brown, Porter\n*/\n \nCREATE TABLE \"Financial_Transactions\" (\n\ttransaction_id INTEGER NOT NULL, \n\taccount_id INTEGER NOT NULL, \n\tinvoice_number INTEGER, \n\ttransaction_type VARCHAR(15) NOT NULL, \n\ttransaction_date DATETIME, \n\ttransaction_amount DECIMAL(19, 4), \n\ttransaction_comment VARCHAR(255), \n\tother_transaction_details VARCHAR(255), \n\tFOREIGN KEY(account_id) REFERENCES \"Accounts\" (account_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number)\n)\n/*\nColumns in Financial_Transactions and 3 examples in each column for high cardinality columns :\ntransaction_id : 1, 13, 11\ntransaction_date : 2018-03-10 13:46:48, 2018-03-11 21:57:47, 2018-03-13 03:51:59\ntransaction_amount : 540.7300, 368.4600, 1214.2200\n*/\n/*\nColumns in Financial_Transactions and all categories for low cardinality columns :\naccount_id : 13, 11, 8, 4, 6, 14, 12, 9\ninvoice_number : 1, 3, 13, 2, 5, 6, 14, 12, 15\ntransaction_type : Refund, Payment\ntransaction_comment : None\nother_transaction_details : None\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Reviewer\" (\n\t\"rID\" INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (\"rID\")\n)\n/*\nColumns in Reviewer and all categories for low cardinality columns :\nrID : 201, 204, 205, 207, 206, 203, 208, 202\nname : Chris Jackson, Sarah Martinez, Mike Anderson, James Cameron, Elizabeth Thomas, Brittany Harris, Daniel Lewis, Ashley White\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Train_Num\" TEXT, \n\t\"Name\" TEXT, \n\t\"From\" TEXT, \n\t\"Arrival\" TEXT, \n\t\"Railway_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/*\nColumns in train and all categories for low cardinality columns :\nTrain_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nTrain_Num : 57136, 57135, 16032, 12140, 51195, 12139, 16031, 11401, 16094\nName : Wardha-Ballarshah Pass, Nagpur-Kazipet Pass, Ballarshah-Mumbai Pass, Nandigram Exp, Lucknow-Chennai Exp, Sewagram Exp, Andaman Exp, Kazipet-Nagpur Pass\nFrom : Lucknow, Ballarshah, Nagpur, Kazipet, Mumbai CST, Jammu Tawi, Wardha, Chennai\nArrival : 23:39, 08:54, 23:44, 05:09, 09:48, 13:28, 13:04, 09:08\nRailway_ID : 1, 2, 5, 7, 3, 10, 9\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Voting_record\" (\n\t\"StuID\" INTEGER, \n\t\"Registration_Date\" VARCHAR(12), \n\t\"Election_Cycle\" VARCHAR(12), \n\t\"President_Vote\" INTEGER, \n\t\"Vice_President_Vote\" INTEGER, \n\t\"Secretary_Vote\" INTEGER, \n\t\"Treasurer_Vote\" INTEGER, \n\t\"Class_President_Vote\" INTEGER, \n\t\"Class_Senator_Vote\" INTEGER, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Vice_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Secretary_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Treasurer_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_President_Vote\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Class_Senator_Vote\") REFERENCES \"Student\" (\"StuID\")\n)\n/*\nColumns in Voting_record and all categories for low cardinality columns :\nStuID : 1003, 1002, 1005, 1001, 1004\nRegistration_Date : 08/30/2014, 08/30/2015, 08/30/2013, 08/30/2012\nElection_Cycle : Fall, Spring\nPresident_Vote : 1014, 1024, 1004\nVice_President_Vote : 1007, 1017\nSecretary_Vote : 1030, 1010, 1020\nTreasurer_Vote : 1035, 1025\nClass_President_Vote : 1011, 1001, 1031, 1021\nClass_Senator_Vote : 1028, 1018\n*/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/*\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n*/\n \nCREATE TABLE \"Students_in_Detention\" (\n\tstudent_id INTEGER NOT NULL, \n\tdetention_id INTEGER NOT NULL, \n\tincident_id INTEGER NOT NULL, \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(detention_id) REFERENCES \"Detention\" (detention_id), \n\tFOREIGN KEY(incident_id) REFERENCES \"Behavior_Incident\" (incident_id)\n)\n/*\nColumns in Students_in_Detention and all categories for low cardinality columns :\nstudent_id : 3, 13, 11, 7, 8, 14, 12, 10, 9\ndetention_id : 3, 13, 2, 7, 6, 12, 14, 15, 9\nincident_id : 1, 13, 11, 8, 12, 3, 14, 15\n*/\n \nCREATE TABLE \"Student_Tests_Taken\" (\n\tregistration_id INTEGER NOT NULL, \n\tdate_test_taken DATETIME NOT NULL, \n\ttest_result VARCHAR(255), \n\tFOREIGN KEY(registration_id) REFERENCES \"Student_Course_Enrolment\" (registration_id)\n)\n/*\nColumns in Student_Tests_Taken and 3 examples in each column for high cardinality columns :\ndate_test_taken : 2018-03-19 02:04:26, 2018-03-25 03:27:16, 2018-03-25 21:41:51\n*/\n/*\nColumns in Student_Tests_Taken and all categories for low cardinality columns :\nregistration_id : 16, 2, 5, 7, 17, 4, 12, 19, 10, 9\ntest_result : Fail, Pass\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(20), \n\tproduct_price DECIMAL(19, 4), \n\tproduct_description VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 4, 6, 3\nproduct_name : electronics, food, dvds, cloth, gift, books\nproduct_price : 5022.3900, 3644.4500, 1322.7800, 2511.2900, 7111.6800, 6402.0900\nproduct_description : great condition, bad condition, good condition\n*/\n \nCREATE TABLE building (\n\tbuilding_id TEXT, \n\t\"Name\" TEXT, \n\t\"Street_address\" TEXT, \n\t\"Years_as_tallest\" TEXT, \n\t\"Height_feet\" INTEGER, \n\t\"Floors\" INTEGER, \n\tPRIMARY KEY (building_id)\n)\n/*\nColumns in building and all categories for low cardinality columns :\nbuilding_id : 1, 2, 5, 7, 4, 6, 3, 0\nName : Bank of America Tower, Franklin Exchange Building, One Tampa City Center, 100 North Tampa, Park Tower, Citizens Bank Building, Floridan Hotel, Tampa City Hall\nStreet_address : 905 Franklin Street, 701 North Franklin Street, 655 North Franklin Street, 315 John F. Kennedy Boulevard, 101 East Kennedy Boulevard, 100 North Tampa Street, 400 North Tampa Street, 201 North Franklin Street\nYears_as_tallest : 1966–1972, 1981–1986, 1913–1915, 1992–present, 1986–1992, 1915–1926, 1926–1966, 1972–1981\nHeight_feet : 204, 537, 458, 577, 145, 579, 160, 280\nFloors : 42, 36, 17, 12, 39, 10, 22\n*/\n \nCREATE TABLE technician (\n\ttechnician_id REAL, \n\t\"Name\" TEXT, \n\t\"Team\" TEXT, \n\t\"Starting_Year\" REAL, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (technician_id)\n)\n/*\nColumns in technician and all categories for low cardinality columns :\ntechnician_id : 3.0, 8.0, 10.0, 1.0, 7.0, 2.0, 6.0, 9.0, 4.0, 5.0\nName : Mark Sewell, John Brown, Mickey Cochrane, Joe Sewell, Tony Sewell, Joe Cochrane, Eddie Collins, Charlie Hollocher, Lou Boudreau\nTeam : CHC, NYY, CLE, PHA, CWS\nStarting_Year : 2013.0, 2016.0, 2003.0, 2006.0, 2005.0, 2002.0, 2009.0, 2012.0\nAge : 38, 37, 45, 46, 28, 36, 32, 47, 43, 35\n*/\n \nCREATE TABLE \"Movie\" (\n\t\"mID\" INTEGER, \n\ttitle TEXT, \n\tyear INTEGER, \n\tdirector TEXT, \n\tPRIMARY KEY (\"mID\")\n)\n/*\nColumns in Movie and all categories for low cardinality columns :\nmID : 108, 106, 103, 102, 101, 104, 107, 105\ntitle : Avatar, Raiders of the Lost Ark, Titanic, E.T., Gone with the Wind, Snow White, Star Wars, The Sound of Music\nyear : 1937, 2009, 1982, 1997, 1939, 1965, 1981, 1977\ndirector : Robert Wise, James Cameron, George Lucas, Victor Fleming, Steven Spielberg, None\n*/\n \nCREATE TABLE \"Lives_in\" (\n\tstuid INTEGER, \n\tdormid INTEGER, \n\troom_number INTEGER, \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid), \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\")\n)\n/*\nColumns in Lives_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nroom_number : 153, 102, 301\n*/\n/*\nColumns in Lives_in and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n*/\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/*\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n*/\n \nCREATE TABLE follows (\n\tf1 INTEGER NOT NULL, \n\tf2 INTEGER NOT NULL, \n\tPRIMARY KEY (f1, f2), \n\tFOREIGN KEY(f2) REFERENCES user_profiles (uid), \n\tFOREIGN KEY(f1) REFERENCES user_profiles (uid)\n)\n/*\nColumns in follows and all categories for low cardinality columns :\nf1 : 1, 2, 5, 7, 3\nf2 : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 1, 2, 3\nproduct_details : Dove Chocolate, Americano, Latte\n*/\n" }, { "role": "user", "content": "What is the publisher with most number of books?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher FROM book_club GROUP BY publisher ORDER BY count(*) DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Purchases\" (\n\tpurchase_transaction_id INTEGER NOT NULL, \n\tpurchase_details VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(purchase_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/*\nColumns in Purchases and 3 examples in each column for high cardinality columns :\npurchase_transaction_id : 1, 13, 11\npurchase_details : t, i, o\n*/\n\n \nCREATE TABLE \"Guests\" (\n\tguest_id INTEGER NOT NULL, \n\tgender_code CHAR(1), \n\tguest_first_name VARCHAR(80), \n\tguest_last_name VARCHAR(80), \n\tdate_of_birth DATETIME, \n\tPRIMARY KEY (guest_id), \n\tUNIQUE (guest_id)\n)\n/*\nColumns in Guests and 3 examples in each column for high cardinality columns :\nguest_id : 1, 13, 11\nguest_first_name : Louvenia, Lou, Keith\nguest_last_name : Bode, Mante, Schowalter\ndate_of_birth : 2001-06-18 20:05:55, 1980-06-20 18:15:39, 1997-01-15 17:37:40\n*/\n/*\nColumns in Guests and all categories for low cardinality columns :\ngender_code : Male, Unknown, Female\n*/\n \nCREATE TABLE pilot (\n\t\"Pilot_ID\" INTEGER, \n\t\"Pilot_name\" TEXT, \n\t\"Rank\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Nationality\" TEXT, \n\t\"Position\" TEXT, \n\t\"Join_Year\" INTEGER, \n\t\"Team\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\")\n)\n/*\nColumns in pilot and all categories for low cardinality columns :\nPilot_ID : 1, 2, 5, 4, 3\nPilot_name : Patrick O'Bryant, Charles Oakley, Dan O'Sullivan, Hakeem Olajuwon, Jermaine O'Neal\nRank : 34, 13, 45, 6\nAge : 37, 33, 40, 32, 22\nNationality : United States, Nigeria, United Kindom\nPosition : Center Team, Forward Team, Forward-Center Team\nJoin_Year : 2009, 2001, 2008, 1999, 2010\nTeam : Fordham, Eau Claire High School, Bradley, Virginia Union, Houston\n*/\n \nCREATE TABLE tweets (\n\tid BIGINT NOT NULL, \n\tuid INTEGER NOT NULL, \n\ttext CHAR(140) NOT NULL, \n\tcreatedate DATETIME DEFAULT CURRENT_TIMESTAMP, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(uid) REFERENCES user_profiles (uid)\n)\n/*\nColumns in tweets and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 9\nuid : 1, 5, 4, 6, 3\ntext : Today I have went shopping at Laffayette., Let’s celebrate women, fight for equality and support each other, not just today, but everyday!, Oh, I only have a few fans., I love my new boyfriend., I feel tired and don't want to write SQLs., My company is hiring interns., Hello I'm Tony Stark., I had a pretty rough time during the last couple of weeks\ncreatedate : 2018-03-09 20:00:14, 2018-03-12 02:30:30, 2018-03-09 20:01:02\n*/\n \nCREATE TABLE \"Functional_Areas\" (\n\tfunctional_area_code VARCHAR(15), \n\tparent_functional_area_code VARCHAR(15), \n\tfunctional_area_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (functional_area_code)\n)\n/*\nColumns in Functional_Areas and all categories for low cardinality columns :\nfunctional_area_code : 1, 8, 9\nparent_functional_area_code : 8\nfunctional_area_description : Keep blank, Signature, Acknowledgement\n*/\n \nCREATE TABLE \"Research_Outcomes\" (\n\toutcome_code VARCHAR(10), \n\toutcome_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (outcome_code)\n)\n/*\nColumns in Research_Outcomes and all categories for low cardinality columns :\noutcome_code : Patent, Paper\noutcome_description : Published Research Paper, Research Patent\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Problem_Status_Codes\" (\n\tproblem_status_code VARCHAR(20), \n\tproblem_status_description VARCHAR(80), \n\tPRIMARY KEY (problem_status_code)\n)\n/*\nColumns in Problem_Status_Codes and all categories for low cardinality columns :\nproblem_status_code : Solved, Reported\nproblem_status_description : Solved, Reported\n*/\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/*\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n*/\n/*\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n*/\n \nCREATE TABLE \"Customers\" (\n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Customer_name\" VARCHAR(40), \n\tPRIMARY KEY (\"Customer_ID\")\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\nCustomer_ID : 756, 882, 562\nCustomer_name : Miss Felicita Reichel, Selena Gerhold, Mrs. Liza Heller V\n*/\n\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/*\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n*/\n \nCREATE TABLE \"Office_locations\" (\n\tbuilding_id INTEGER, \n\tcompany_id INTEGER, \n\tmove_in_year INTEGER, \n\tPRIMARY KEY (building_id, company_id), \n\tFOREIGN KEY(building_id) REFERENCES buildings (id), \n\tFOREIGN KEY(company_id) REFERENCES \"Companies\" (id)\n)\n/*\nColumns in Office_locations and 3 examples in each column for high cardinality columns :\nbuilding_id : 1, 11, 2\nmove_in_year : 2023, 2020, 2022\n*/\n/*\nColumns in Office_locations and all categories for low cardinality columns :\ncompany_id : 1, 11, 2, 5, 19, 7, 4, 3, 10, 9\n*/\n \nCREATE TABLE mountain (\n\t\"Mountain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Mountain_ID\")\n)\n/*\nColumns in mountain and all categories for low cardinality columns :\nMountain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ngaliema / Mt Stanley (Margherita Pk), Mount Kenya (Lenana), Kibo (Uhuru Pk), Ngaliema / Mt Stanley (Savoia Pk), Mount Kenya (Batian), Duwoni / Mt Speke (Vittorio Emanuele Pk), Mawenzi (Hans Meyer Pk)\nHeight : 5109.0, 5199.0, 5895.0, 4890.0, 4985.0, 4977.0, 5148.0\nProminence : 720.0, 850.0, 3951.0, 3825.0, 130.0, 5885.0, 110.0\nRange : Kilimanjaro, Mount Kenya, Rwenzori\nCountry : DR Congo Uganda, Uganda, Tanzania, Kenya\n*/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Num_of_employees\" INTEGER, \n\t\"Num_of_shops\" REAL, \n\t\"Ranking\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/*\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nDistrict : New Brunswick, Quebec, Ontario, Nova Scotia, Alberta, British Columbia\nNum_of_employees : 1978, 1958, 1968, 1965, 1966\nNum_of_shops : 49.0, 10.0, 40.0, 32.0, 54.0\nRanking : 1, 5, 8, 4, 21, 3\n*/\n \nCREATE TABLE \"Enrolled_in\" (\n\t\"StuID\" INTEGER, \n\t\"CID\" VARCHAR(7), \n\t\"Grade\" VARCHAR(2), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"CID\") REFERENCES \"Course\" (\"CID\"), \n\tFOREIGN KEY(\"Grade\") REFERENCES \"Gradeconversion\" (lettergrade)\n)\n/*\nColumns in Enrolled_in and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nCID : 550.413, 520.345, 600.437\nGrade : D+, B-, C\n*/\n\n \nCREATE TABLE match_season (\n\t\"Season\" REAL, \n\t\"Player\" TEXT, \n\t\"Position\" TEXT, \n\t\"Country\" INTEGER, \n\t\"Team\" INTEGER, \n\t\"Draft_Pick_Number\" INTEGER, \n\t\"Draft_Class\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Season\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\"), \n\tFOREIGN KEY(\"Country\") REFERENCES country (\"Country_id\")\n)\n/*\nColumns in match_season and 3 examples in each column for high cardinality columns :\nSeason : 2003.0, 2001.0, 2006.0\nPlayer : Carlos Bocanegra Category:Articles with hCards, Ben Olsen Category:Articles with hCards, Rodrigo Faria Category:Articles with hCards\nDraft_Pick_Number : 87, 1, 13\nDraft_Class : 2005 MLS SuperDraft, 2004 MLS SuperDraft, 1996 MLS Inaugural Player Draft\nCollege : Cal State Northridge, Duke, Furman\n*/\n/*\nColumns in match_season and all categories for low cardinality columns :\nPosition : Midfielder, Defender, Forward\nCountry : 1, 4, 6, 5\nTeam : 1, 2, 5, 4, 3, 10, 9\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Shipments\" (\n\tshipment_id INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_number INTEGER NOT NULL, \n\tshipment_tracking_number VARCHAR(80), \n\tshipment_date DATETIME, \n\tother_shipment_details VARCHAR(255), \n\tPRIMARY KEY (shipment_id), \n\tFOREIGN KEY(invoice_number) REFERENCES \"Invoices\" (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Shipments and 3 examples in each column for high cardinality columns :\nshipment_id : 1, 13, 11\norder_id : 13, 2, 5\nshipment_tracking_number : 5991, 0182, 2323\nshipment_date : 1977-11-10 12:11:25, 1982-01-24 12:13:16, 1981-11-13 23:20:42\n*/\n/*\nColumns in Shipments and all categories for low cardinality columns :\ninvoice_number : 13, 10, 2, 5, 3, 15, 9\nother_shipment_details : None\n*/\n" }, { "role": "user", "content": "Return the publisher that has published the most books." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher FROM book_club GROUP BY publisher ORDER BY count(*) DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/*\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n*/\n \nCREATE TABLE qualifying (\n\t\"qualifyId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\t\"constructorId\" INTEGER, \n\tnumber INTEGER, \n\tposition INTEGER, \n\tq1 TEXT, \n\tq2 TEXT, \n\tq3 TEXT, \n\tPRIMARY KEY (\"qualifyId\"), \n\tFOREIGN KEY(\"constructorId\") REFERENCES constructors (\"constructorId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/*\nColumns in qualifying and 3 examples in each column for high cardinality columns :\nqualifyId : 87, 56, 65\ndriverId : 19, 17, 21\nconstructorId : 1, 11, 2\nnumber : 19, 17, 21\nposition : 17, 21, 9\nq1 : , 1:17.053, 1:16.933\nq2 : , 1:32.915, 1:20.894\nq3 : NULL, 1:35.748, 1:17.343\n*/\n/*\nColumns in qualifying and all categories for low cardinality columns :\nraceId : 26, 20, 25, 24, 23, 21, 19, 18, 27, 22\n*/\n \nCREATE TABLE match_season (\n\t\"Season\" REAL, \n\t\"Player\" TEXT, \n\t\"Position\" TEXT, \n\t\"Country\" INTEGER, \n\t\"Team\" INTEGER, \n\t\"Draft_Pick_Number\" INTEGER, \n\t\"Draft_Class\" TEXT, \n\t\"College\" TEXT, \n\tPRIMARY KEY (\"Season\"), \n\tFOREIGN KEY(\"Team\") REFERENCES team (\"Team_id\"), \n\tFOREIGN KEY(\"Country\") REFERENCES country (\"Country_id\")\n)\n/*\nColumns in match_season and 3 examples in each column for high cardinality columns :\nSeason : 2003.0, 2001.0, 2006.0\nPlayer : Carlos Bocanegra Category:Articles with hCards, Ben Olsen Category:Articles with hCards, Rodrigo Faria Category:Articles with hCards\nDraft_Pick_Number : 87, 1, 13\nDraft_Class : 2005 MLS SuperDraft, 2004 MLS SuperDraft, 1996 MLS Inaugural Player Draft\nCollege : Cal State Northridge, Duke, Furman\n*/\n/*\nColumns in match_season and all categories for low cardinality columns :\nPosition : Midfielder, Defender, Forward\nCountry : 1, 4, 6, 5\nTeam : 1, 2, 5, 4, 3, 10, 9\n*/\n \nCREATE TABLE enzyme (\n\tid INTEGER, \n\tname TEXT, \n\t\"Location\" TEXT, \n\t\"Product\" TEXT, \n\t\"Chromosome\" TEXT, \n\t\"OMIM\" INTEGER, \n\t\"Porphyria\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in enzyme and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3\nname : PBG deaminase, Coproporphyrinogen III oxidase, ALA dehydratase, Uroporphyrinogen III decarboxylase, Ferrochelatase, Uroporphyrinogen III synthase, Protoporphyrinogen oxidase, ALA synthase\nLocation : Mitochondrion, Cytosol\nProduct : Coproporphyrinogen III, δ-Aminolevulinic acid, Hydroxymethyl bilane, Protoporphyrin IX, Heme, Uroporphyrinogen III, Protoporphyrinogen IX, Porphobilinogen\nChromosome : 9q34, 1q22, 18q21.3, 3p21.1, 3q12, 10q25.2-q26.3, 11q23.3, 1p34\nOMIM : 606938, 125270, 600923, 125290, 176000, 177000, 121300, 176100\nPorphyria : porphyria cutanea tarda, congenital erythropoietic porphyria, acute intermittent porphyria, erythropoietic protoporphyria, coproporphyria, none, ALA-Dehydratase deficiency, variegate porphyria\n*/\n \nCREATE TABLE editor (\n\t\"Editor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\tPRIMARY KEY (\"Editor_ID\")\n)\n/*\nColumns in editor and all categories for low cardinality columns :\nEditor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Maria Góralczyk, Władysław Grzywna, Grażyna Wolszczak, Szymon Wydra, Piotr Pręgowski, Kamila Porczyk, Marek Siudym, Anna Powierza, Mariusz Zalejski\nAge : 43.0, 24.0, 25.0, 34.0, 38.0, 54.0, 35.0, 21.0, 20.0\n*/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Year_Join\" INTEGER, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/*\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nName : Nick Price, John Daly, Paul Azinger, Mark Brooks, Larry Nelson, Jeff Sluman, Vijay Singh\nCountry : Zimbabwe, United States, Fiji\nYear_Join : 1993, 1994, 1991, 1996, 1998, 1981, 1988\nAge : 46, 45, 48, 50, 47, 57\n*/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER, \n\tdate_of_registration DATETIME, \n\tdate_of_latest_logon DATETIME, \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(10), \n\tpersonal_name VARCHAR(40), \n\tmiddle_name VARCHAR(40), \n\tfamily_name VARCHAR(40), \n\tPRIMARY KEY (student_id)\n)\n/*\nColumns in Students and 3 examples in each column for high cardinality columns :\nstudent_id : 1, 13, 11\ndate_of_registration : 2015-10-11 03:23:27, 2016-03-25 18:58:58, 2015-04-27 10:25:31\ndate_of_latest_logon : 2017-11-25 03:14:32, 2017-12-11 14:29:41, 2017-09-15 08:10:04\nlogin_name : eichmann.lera, myron.bergnaum, kiarra28\npassword : 5bc0d35e75, aedd08a3b9, 2e05a1e6a3\npersonal_name : Mariela, Eliza, Alicia\nmiddle_name : Casimir, Camilla, Marianne\nfamily_name : Ziemann, Zieme, Hartmann\n*/\n\n \nCREATE TABLE \"Complaints\" (\n\tcomplaint_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tcomplaint_outcome_code VARCHAR(20) NOT NULL, \n\tcomplaint_status_code VARCHAR(20) NOT NULL, \n\tcomplaint_type_code VARCHAR(20) NOT NULL, \n\tdate_complaint_raised DATETIME, \n\tdate_complaint_closed DATETIME, \n\tstaff_id INTEGER NOT NULL, \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/*\nColumns in Complaints and 3 examples in each column for high cardinality columns :\ncomplaint_id : 1, 11, 2\n*/\n/*\nColumns in Complaints and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\ncustomer_id : 120, 114, 113, 116, 117, 115, 118\ncomplaint_outcome_code : OK\ncomplaint_status_code : Open, Closed, New\ncomplaint_type_code : Product Failure, Product Unusable\ndate_complaint_raised : 2006-10-29 07:08:46, 2002-07-18 10:59:35, 1977-08-06 00:31:19, 1987-07-11 14:40:30, 1973-02-10 22:55:56, 2007-10-14 21:50:43\ndate_complaint_closed : 2013-09-14 02:59:10, 1975-10-11 05:54:30, 1970-10-14 00:57:25, 1976-04-19 11:03:06, 1995-09-11 14:48:46, 2000-08-17 17:02:48\nstaff_id : 120, 114, 116, 117, 115, 118\n*/\n \nCREATE TABLE record (\n\t\"ID\" INTEGER, \n\t\"Result\" TEXT, \n\t\"Swimmer_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\tPRIMARY KEY (\"Swimmer_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Swimmer_ID\") REFERENCES swimmer (\"ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"ID\")\n)\n/*\nColumns in record and 3 examples in each column for high cardinality columns :\nID : 1, 13, 11\n*/\n/*\nColumns in record and all categories for low cardinality columns :\nResult : Loss, Win, NC\nSwimmer_ID : 1, 2, 5, 4, 6, 3\nEvent_ID : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Home Town\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Gary Goodner, Mike Murphy, Tyrone Brayan\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nHeight : 6.6, 6.5, 6.7, 6.1, 6.4, 6.3, 6.8\nWeight : 215.0, 185.0, 170.0, 200.0, 220.0, 205.0, 160.0, 190.0\nHome Town : Beaver Dam, KY, San Antonio, TX, Placentia, CA, Indianapolis, IN, Westport, CT, Denton, TX, Austin, TX, Baton Rouge, LA, Altoona, PA, Los Angeles, CA\n*/\n \nCREATE TABLE county (\n\t\"County_Id\" INTEGER, \n\t\"County_name\" TEXT, \n\t\"Population\" REAL, \n\t\"Zip_code\" TEXT, \n\tPRIMARY KEY (\"County_Id\")\n)\n/*\nColumns in county and all categories for low cardinality columns :\nCounty_Id : 1, 2, 5, 4, 3\nCounty_name : Baltimore County, Howard, Colony, Manning, Mansfield\nPopulation : 87200.0, 13300.0, 21000.0, 79000.0, 90000.0\nZip_code : D09, D02, D21, D11, D08\n*/\n \nCREATE TABLE \"Procedures\" (\n\t\"Code\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Cost\" REAL NOT NULL, \n\tPRIMARY KEY (\"Code\")\n)\n/*\nColumns in Procedures and all categories for low cardinality columns :\nCode : 1, 2, 5, 7, 4, 6, 3\nName : Obfuscated Dermogastrotomy, Obtuse Pyloric Recombobulation, Follicular Demiectomy, Reverse Rhinopodoplasty, Folded Demiophtalmectomy, Complete Walletectomy, Reversible Pancreomyoplasty\nCost : 5600.0, 1500.0, 10000.0, 25.0, 4500.0, 3750.0, 4899.0\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n" }, { "role": "user", "content": "Show all book categories and the number of books in each category." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: category.\nThe SQL query I'll be generating is:\nSELECT category , count(*) FROM book_club GROUP BY category" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResName\" VARCHAR(100), \n\t\"Address\" VARCHAR(100), \n\t\"Rating\" INTEGER, \n\tPRIMARY KEY (\"ResID\")\n)\n/*\nColumns in Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResName : Subway, Honeygrow\nAddress : 3212 St Paul St, Baltimore, MD 21218, 3233 St Paul St, Baltimore, MD 21218\nRating : 4, 3\n*/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/*\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n*/\n \nCREATE TABLE operate_company (\n\tid INTEGER, \n\tname TEXT, \n\t\"Type\" TEXT, \n\t\"Principal_activities\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in operate_company and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : China Pacific Laundry Services, Cathay Pacific Holidays, CLS Catering Services Limited\n*/\n/*\nColumns in operate_company and all categories for low cardinality columns :\nType : Joint Venture, Subsidiary, Corporate\nPrincipal_activities : Laundry, Airline, Catering services, Travel agency, Ground handling, Cargo, Cargo airline\nIncorporated_in : Canada, China, Hong Kong, Vietnam, Taiwan\nGroup_Equity_Shareholding : 45.0, 60.0, 30.0, 49.0, 100.0, 40.0, 18.77\n*/\n \nCREATE TABLE perpetrator (\n\t\"Perpetrator_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Year\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Killed\" INTEGER, \n\t\"Injured\" INTEGER, \n\tPRIMARY KEY (\"Perpetrator_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in perpetrator and all categories for low cardinality columns :\nPerpetrator_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 8, 4, 6, 3\nDate : 05.21 May 21, 04.26 April 26/27, 04.00 April, 11.18 Nov. 18, 09.20 Sep. 20\nYear : 1995.0, 1982.0, 1938.0, 1994.0, 1950.0\nLocation : Beijing, Uiryeong, Kaio, Zhaodong, Nainital\nCountry : Japan, South Korea, India, China\nKilled : 56, 30, 23, 32, 22\nInjured : 16, 37, 80, 3, 0\n*/\n \nCREATE TABLE actor (\n\tactor_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(45) NOT NULL, \n\tlast_name VARCHAR(45) NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (actor_id)\n)\n/*\nColumns in actor and 3 examples in each column for high cardinality columns :\nactor_id : 87, 56, 65\nfirst_name : WALTER, KIM, REESE\nlast_name : WITHERSPOON, OLIVIER, ALLEN\n*/\n/*\nColumns in actor and all categories for low cardinality columns :\nlast_update : 2006-02-15 04:34:33\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n*/\n/*\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE journal (\n\t\"Journal_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Theme\" TEXT, \n\t\"Sales\" INTEGER, \n\tPRIMARY KEY (\"Journal_ID\")\n)\n/*\nColumns in journal and 3 examples in each column for high cardinality columns :\nJournal_ID : 1, 16, 13\nDate : September 23, 2001, November 25, 2001, October 21, 2001\nTheme : Cleveland Browns, at Baltimore Ravens, Baltimore Ravens\nSales : 3798, 5342, 2804\n*/\n\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE musical (\n\t\"Musical_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Award\" TEXT, \n\t\"Category\" TEXT, \n\t\"Nominee\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Musical_ID\")\n)\n/*\nColumns in musical and all categories for low cardinality columns :\nMusical_ID : 1, 2, 5, 7, 4, 6, 3\nName : The Book of Mormon, Les Misérables, Rent, Chicago, West Side Story, The Phantom of the Opera, Wicked\nYear : 1986\nAward : Drama Desk Award, Tony Award\nCategory : Outstanding Director of a Musical, Best Direction of a Musical, Best Choreography, Best Performance by a Leading Actor in a Musical, Outstanding Choreography, Best Book of a Musical, Outstanding Actor in a Musical\nNominee : Bob Fosse, Cleavant Derricks\nResult : Nominated, Won\n*/\n \nCREATE TABLE host (\n\t\"Host_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\tPRIMARY KEY (\"Host_ID\")\n)\n/*\nColumns in host and all categories for low cardinality columns :\nHost_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Lloyd Daniels, Kornel David, Antonio Davis, Carlos Delfino, DeMar DeRozan, Ed Davis, Austin Daye, Derrick Dial, Justin Dentmon, Hubert Davis\nNationality : United States, Argentina, Hungary\nAge : 26, 45, 37, 40, 30, 60, 47, 43, 31\n*/\n \nCREATE TABLE \"match\" (\n\t\"Round\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Date\" TEXT, \n\t\"Fastest_Qualifying\" TEXT, \n\t\"Winning_Pilot\" TEXT, \n\t\"Winning_Aircraft\" TEXT, \n\tPRIMARY KEY (\"Round\"), \n\tFOREIGN KEY(\"Winning_Pilot\") REFERENCES pilot (\"Pilot_Id\"), \n\tFOREIGN KEY(\"Winning_Aircraft\") REFERENCES aircraft (\"Aircraft_ID\")\n)\n/*\nColumns in match and all categories for low cardinality columns :\nRound : 3.0, 1.0, 7.0, 2.0, 6.0, 4.0, 5.0\nLocation : EuroSpeedway Lausitz, Flamengo Beach , Rio de Janeiro, River Danube , Budapest, Swan River , Perth, Mina' Zayid , Abu Dhabi, New York City, Windsor , Ontario\nCountry : Canada, United States, Australia, Brazil, Germany, United Arab Emirates, Hungary\nDate : June 5–6, June 19–20, August 7–8, May 8–9, March 26–27, April 17–18, Cancelled\nFastest_Qualifying : Hannes Arch, Paul Bonhomme, Cancelled, Nigel Lamb\nWinning_Pilot : 1, 2, 4, 6, 9\nWinning_Aircraft : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE furniture (\n\t\"Furniture_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Num_of_Component\" INTEGER, \n\t\"Market_Rate\" REAL, \n\tPRIMARY KEY (\"Furniture_ID\")\n)\n/*\nColumns in furniture and all categories for low cardinality columns :\nFurniture_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dining set, Chabudai, Billiard table, Hatstand, Bookcase, Four-poster bed, Bench\nNum_of_Component : 5, 4, 6, 14, 3, 12\nMarket_Rate : 1.0, 3.5, 52.5, 0.5, 40.0, 2.0\n*/\n \nCREATE TABLE department (\n\t\"Department_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Creation\" TEXT, \n\t\"Ranking\" INTEGER, \n\t\"Budget_in_Billions\" REAL, \n\t\"Num_Employees\" REAL, \n\tPRIMARY KEY (\"Department_ID\")\n)\n/*\nColumns in department and 3 examples in each column for high cardinality columns :\nDepartment_ID : 1, 13, 11\nName : Energy, Interior, Health and Human Services\nCreation : 1913, 1979, 1989\nRanking : 1, 13, 11\nBudget_in_Billions : 10.7, 77.6, 59.7\nNum_Employees : 112557.0, 3000000.0, 235000.0\n*/\n\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n*/\n/*\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n*/\n" }, { "role": "user", "content": "How many books fall into each category?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: category.\nThe SQL query I'll be generating is:\nSELECT category , count(*) FROM book_club GROUP BY category" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n*/\n \nCREATE TABLE \"Documents_with_Expenses\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Budget_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Budget_Type_Code\") REFERENCES \"Ref_Budget_Codes\" (\"Budget_Type_Code\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/*\nColumns in Documents_with_Expenses and all categories for low cardinality columns :\nDocument_ID : 300, 240, 309, 226, 367, 371, 383, 227, 192, 57\nBudget_Type_Code : GV, SF, ORG\nDocument_Details : government, safety, organization\n*/\n \nCREATE TABLE candidate (\n\t\"Candidate_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Poll_Source\" TEXT, \n\t\"Date\" TEXT, \n\t\"Support_rate\" REAL, \n\t\"Consider_rate\" REAL, \n\t\"Oppose_rate\" REAL, \n\t\"Unsure_rate\" REAL, \n\tPRIMARY KEY (\"Candidate_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in candidate and all categories for low cardinality columns :\nCandidate_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 7, 4, 6, 3, 9\nPoll_Source : Newsweek Poll, FOX News/Opinion Dynamics Poll, WNBC/Marist Poll\nDate : Feb 12–15, 2007, Nov 9–10, 2006, Feb 13–14, 2007\nSupport_rate : 0.18, 0.25, 0.17, 0.33, 0.24\nConsider_rate : 0.34, 0.27, 0.42, 0.3, 0.2\nOppose_rate : 0.32, 0.44, 0.45, 0.43\nUnsure_rate : 0.4, 0.3, 0.2, 0.9\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/*\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n*/\n \nCREATE TABLE employees (\n\t\"EMPLOYEE_ID\" DECIMAL(6, 0) DEFAULT '0' NOT NULL, \n\t\"FIRST_NAME\" VARCHAR(20) DEFAULT NULL, \n\t\"LAST_NAME\" VARCHAR(25) NOT NULL, \n\t\"EMAIL\" VARCHAR(25) NOT NULL, \n\t\"PHONE_NUMBER\" VARCHAR(20) DEFAULT NULL, \n\t\"HIRE_DATE\" DATE NOT NULL, \n\t\"JOB_ID\" VARCHAR(10) NOT NULL, \n\t\"SALARY\" DECIMAL(8, 2) DEFAULT NULL, \n\t\"COMMISSION_PCT\" DECIMAL(2, 2) DEFAULT NULL, \n\t\"MANAGER_ID\" DECIMAL(6, 0) DEFAULT NULL, \n\t\"DEPARTMENT_ID\" DECIMAL(4, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"EMPLOYEE_ID\"), \n\tFOREIGN KEY(\"DEPARTMENT_ID\") REFERENCES departments (\"DEPARTMENT_ID\"), \n\tFOREIGN KEY(\"JOB_ID\") REFERENCES jobs (\"JOB_ID\")\n)\n/*\nColumns in employees and 3 examples in each column for high cardinality columns :\nEMPLOYEE_ID : 135, 187, 194\nFIRST_NAME : Randall, Adam, Susan\nLAST_NAME : Mourgos, Baida, Ande\nEMAIL : SSTILES, SMAVRIS, GHIMURO\nPHONE_NUMBER : 515.123.8080, 515.127.4563, 011.44.1346.629268\nHIRE_DATE : 1987-07-25, 1987-07-09, 1987-06-29\nJOB_ID : HR_REP, ST_MAN, AD_PRES\nSALARY : 2500.00, 8000.00, 8600.00\nMANAGER_ID : 102, 147, 122\nDEPARTMENT_ID : 110, 100, 20\n*/\n/*\nColumns in employees and all categories for low cardinality columns :\nCOMMISSION_PCT : 0.00, 0.35, 0.25, 0.10, 0.15, 0.20, 0.30, 0.40\n*/\n \nCREATE TABLE genre (\n\tg_name TEXT(20) NOT NULL, \n\trating TEXT(10), \n\tmost_popular_in TEXT(50), \n\tPRIMARY KEY (g_name)\n)\n/*\nColumns in genre and all categories for low cardinality columns :\ng_name : tagore, folk, modern, nazrul, blues, pop\nrating : 7, 8, 9\nmost_popular_in : America, Canada, Sylhet,Chittagong,Kustia, Bangladesh\n*/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n*/\n \nCREATE TABLE gas_station (\n\t\"Station_ID\" INTEGER, \n\t\"Open_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Manager_Name\" TEXT, \n\t\"Vice_Manager_Name\" TEXT, \n\t\"Representative_Name\" TEXT, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in gas_station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nOpen_Year : 2004, 2009, 2005\nLocation : Channel Hill, Newport Rd, Herne Ave\n*/\n/*\nColumns in gas_station and all categories for low cardinality columns :\nManager_Name : Simon Cope Derek Marloe, BryanDenman, Luke Rowe, BrianWingrave, Bryan Taylor, Jon Rowe, Tony Bristow, Tom Whit, SimonMarloe, Colin Denman\nVice_Manager_Name : TonyBristow, Russell Brown, Russell Denman, Martin Freeman, Simon Gaywood, James Holland-Leader, James Colin , JameMarloe, Steve Parsons, Martin Garnham\nRepresentative_Name : Andrew Russell, Chris Pyatt, Tim Read, Ray Hughes, Simon Gaywood, Tony Gibb, Clive Burr, Courtney Rowe, Rob Jefferies , Dave Edwards Roger \n*/\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/*\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n*/\n \nCREATE TABLE company (\n\t\"Company_ID\" REAL, \n\t\"Name\" TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Industry\" TEXT, \n\t\"Sales_in_Billion\" REAL, \n\t\"Profits_in_Billion\" REAL, \n\t\"Assets_in_Billion\" REAL, \n\t\"Market_Value_in_Billion\" REAL, \n\tPRIMARY KEY (\"Company_ID\")\n)\n/*\nColumns in company and 3 examples in each column for high cardinality columns :\nCompany_ID : 3.0, 8.0, 11.0\nName : PetroChina, Berkshire Hathaway, Petrobras\nSales_in_Billion : 82.6, 110.8, 143.7\nProfits_in_Billion : 15.7, 20.1, 25.1\nAssets_in_Billion : 213.0, 331.1, 1313.9\nMarket_Value_in_Billion : 237.4, 213.7, 164.3\n*/\n/*\nColumns in company and all categories for low cardinality columns :\nHeadquarters : UK, China, Brazil, France, Russia, USA, Germany, Netherlands\nIndustry : Retailing, Automotive, Conglomerate, Oil and gas, Banking\n*/\n \nCREATE TABLE book (\n\t\"Book_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Issues\" REAL, \n\t\"Writer\" TEXT, \n\tPRIMARY KEY (\"Book_ID\")\n)\n/*\nColumns in book and all categories for low cardinality columns :\nBook_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Bloody Mary, Cyberella, The Black Lamb, Sheva's War, BrainBanx, Dead Corps, Gemini Blood, Bloody Mary : Lady Liberty, Michael Moorcock's Multiverse, The Dome: Ground Zero\nIssues : 12.0, 1.0, 9.0, 6.0, 4.0, 5.0\nWriter : Christopher Hinz, Timothy Truman, Christopher Moeller, Dave Gibbons, Elaine Lee, Michael Moorcock, Garth Ennis, Howard Chaykin\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE volume (\n\t\"Volume_ID\" INTEGER, \n\t\"Volume_Issue\" TEXT, \n\t\"Issue_Date\" TEXT, \n\t\"Weeks_on_Top\" REAL, \n\t\"Song\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\tPRIMARY KEY (\"Volume_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in volume and all categories for low cardinality columns :\nVolume_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nVolume_Issue : 46:5, 46:16, 46:14-15, 45:15, 45:21-22, 45:16, 46:6-8, 45:14 §, 46:10, 46:9\nIssue_Date : 16 May - 30 May, 6 June, 27 December 1986 - 10 January, 28 February - 7 March, 13 June, 24 January, 9 May, 17 January, 11 July - 18 July, 25 July\nWeeks_on_Top : 3.0, 1.0, 2.0\nSong : Head to Toe , Always , With or Without You , Looking for a New Love, La Isla Bonita , The Way, Everybody Have Fun Tonight , Touch Me (I Want Your Body) , (I Just) Died in Your Arms , Walk Like an Egyptian \nArtist_ID : 1, 2, 5, 4, 6\n*/\n" }, { "role": "user", "content": "List categories that have at least two books after year 1989." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: category.\nThe SQL query I'll be generating is:\nSELECT category FROM book_club WHERE YEAR > 1989 GROUP BY category HAVING count(*) >= 2" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE takes (\n\t\"ID\" VARCHAR(5), \n\tcourse_id VARCHAR(8), \n\tsec_id VARCHAR(8), \n\tsemester VARCHAR(6), \n\tyear NUMERIC(4, 0), \n\tgrade VARCHAR(2), \n\tPRIMARY KEY (\"ID\", course_id, sec_id, semester, year), \n\tFOREIGN KEY(course_id, sec_id, semester, year) REFERENCES section (course_id, sec_id, semester, year), \n\tFOREIGN KEY(\"ID\") REFERENCES student (\"ID\")\n)\n/*\nColumns in takes and 3 examples in each column for high cardinality columns :\nID : 99189, 44706, 56058\ncourse_id : 843, 400, 349\n*/\n/*\nColumns in takes and all categories for low cardinality columns :\nsec_id : 1, 2, 3\nsemester : Fall, Spring\nyear : 2004, 2009, 2001, 2005, 2008, 2006, 2003, 2002, 2010, 2007\ngrade : B-, B , C , B+, A , A-, C-, C+, A+\n*/\n \nCREATE TABLE journal (\n\t\"Journal_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Theme\" TEXT, \n\t\"Sales\" INTEGER, \n\tPRIMARY KEY (\"Journal_ID\")\n)\n/*\nColumns in journal and 3 examples in each column for high cardinality columns :\nJournal_ID : 1, 16, 13\nDate : September 23, 2001, November 25, 2001, October 21, 2001\nTheme : Cleveland Browns, at Baltimore Ravens, Baltimore Ravens\nSales : 3798, 5342, 2804\n*/\n\n \nCREATE TABLE \"Claims\" (\n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Date_Claim_Made\" DATE, \n\t\"Date_Claim_Settled\" DATE, \n\t\"Amount_Claimed\" INTEGER, \n\t\"Amount_Settled\" INTEGER, \n\tPRIMARY KEY (\"Claim_ID\"), \n\tFOREIGN KEY(\"Policy_ID\") REFERENCES \"Customer_Policies\" (\"Policy_ID\")\n)\n/*\nColumns in Claims and 3 examples in each column for high cardinality columns :\nClaim_ID : 843, 143, 563\nDate_Claim_Made : 2018-11-08, 2016-08-12, 2016-08-02\nDate_Claim_Settled : 2017-12-20, 2018-02-20, 2017-09-04\nAmount_Claimed : 49743, 70088, 46479\nAmount_Settled : 1372, 1652, 1528\n*/\n/*\nColumns in Claims and all categories for low cardinality columns :\nPolicy_ID : 858, 143, 141, 744, 473, 352, 119, 738, 552\n*/\n \nCREATE TABLE \"Shipment_Items\" (\n\tshipment_id INTEGER NOT NULL, \n\torder_item_id INTEGER NOT NULL, \n\tFOREIGN KEY(shipment_id) REFERENCES \"Shipments\" (shipment_id), \n\tFOREIGN KEY(order_item_id) REFERENCES \"Order_Items\" (order_item_id)\n)\n/*\nColumns in Shipment_Items and all categories for low cardinality columns :\nshipment_id : 13, 11, 2, 5, 15, 4, 14, 3, 12, 10\norder_item_id : 13, 11, 2, 5, 15, 7, 4, 12, 10\n*/\n \nCREATE TABLE \"Courses\" (\n\tcourse_id INTEGER, \n\tauthor_id INTEGER NOT NULL, \n\tsubject_id INTEGER NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tPRIMARY KEY (course_id), \n\tFOREIGN KEY(subject_id) REFERENCES \"Subjects\" (subject_id), \n\tFOREIGN KEY(author_id) REFERENCES \"Course_Authors_and_Tutors\" (author_id)\n)\n/*\nColumns in Courses and 3 examples in each column for high cardinality columns :\ncourse_id : 1, 13, 11\ncourse_name : modern Arts, AI, Writing in French\ncourse_description : modern Arts, AI, Writing in French\n*/\n/*\nColumns in Courses and all categories for low cardinality columns :\nauthor_id : 13, 11, 5, 8, 4, 6, 14, 12, 15, 9\nsubject_id : 1, 2, 3\n*/\n \nCREATE TABLE journal (\n\t\"Journal_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Theme\" TEXT, \n\t\"Sales\" INTEGER, \n\tPRIMARY KEY (\"Journal_ID\")\n)\n/*\nColumns in journal and 3 examples in each column for high cardinality columns :\nJournal_ID : 1, 16, 13\nDate : September 23, 2001, November 25, 2001, October 21, 2001\nTheme : Cleveland Browns, at Baltimore Ravens, Baltimore Ravens\nSales : 3798, 5342, 2804\n*/\n\n \nCREATE TABLE buildings (\n\tid INTEGER, \n\tname TEXT, \n\t\"City\" TEXT, \n\t\"Height\" INTEGER, \n\t\"Stories\" INTEGER, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in buildings and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Torre Mitikah, Residencial Vidalta Torre Altaire 2, Reforma 90\nStories : 67, 100, 20\n*/\n/*\nColumns in buildings and all categories for low cardinality columns :\nCity : Monterrey, Mexico City\nHeight : 330, 300, 150, 100, 210, 200, 50, 220, 73\nStatus : on-hold, under construction, proposed\n*/\n \nCREATE TABLE \"match\" (\n\t\"Round\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Date\" TEXT, \n\t\"Fastest_Qualifying\" TEXT, \n\t\"Winning_Pilot\" TEXT, \n\t\"Winning_Aircraft\" TEXT, \n\tPRIMARY KEY (\"Round\"), \n\tFOREIGN KEY(\"Winning_Pilot\") REFERENCES pilot (\"Pilot_Id\"), \n\tFOREIGN KEY(\"Winning_Aircraft\") REFERENCES aircraft (\"Aircraft_ID\")\n)\n/*\nColumns in match and all categories for low cardinality columns :\nRound : 3.0, 1.0, 7.0, 2.0, 6.0, 4.0, 5.0\nLocation : EuroSpeedway Lausitz, Flamengo Beach , Rio de Janeiro, River Danube , Budapest, Swan River , Perth, Mina' Zayid , Abu Dhabi, New York City, Windsor , Ontario\nCountry : Canada, United States, Australia, Brazil, Germany, United Arab Emirates, Hungary\nDate : June 5–6, June 19–20, August 7–8, May 8–9, March 26–27, April 17–18, Cancelled\nFastest_Qualifying : Hannes Arch, Paul Bonhomme, Cancelled, Nigel Lamb\nWinning_Pilot : 1, 2, 4, 6, 9\nWinning_Aircraft : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE stadium (\n\t\"ID\" INTEGER, \n\tname TEXT, \n\t\"Capacity\" INTEGER, \n\t\"City\" TEXT, \n\t\"Country\" TEXT, \n\t\"Opening_year\" INTEGER, \n\tPRIMARY KEY (\"ID\")\n)\n/*\nColumns in stadium and all categories for low cardinality columns :\nID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nname : Northumberland Development Project, Fisht Olympic Stadium, Ferenc Puskás Stadion, Nou Mestalla, Yubileyniy Stadium, Estadio La Peineta, Baku Olympic Stadium, Arena Baltika, Stade des Lumières, Gazprom Arena\nCapacity : 61556, 69501, 56250, 68000, 47659, 45015, 67500, 75000, 65000\nCity : London, Sochi, Budapest, Saint Petersburg, Baku, Kaliningrad, Madrid, Valencia, Lyon, Saransk\nCountry : Spain, France, England, Russia, Azerbaijan, Hungary\nOpening_year : 2004, 2005, 2007, 2006\n*/\n \nCREATE TABLE \"Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResName\" VARCHAR(100), \n\t\"Address\" VARCHAR(100), \n\t\"Rating\" INTEGER, \n\tPRIMARY KEY (\"ResID\")\n)\n/*\nColumns in Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResName : Subway, Honeygrow\nAddress : 3212 St Paul St, Baltimore, MD 21218, 3233 St Paul St, Baltimore, MD 21218\nRating : 4, 3\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE song (\n\tsong_name TEXT(50), \n\tartist_name TEXT(50), \n\tcountry TEXT(20), \n\tf_id NUMERIC(10), \n\tgenre_is TEXT(20), \n\trating NUMERIC(10), \n\tlanguages TEXT(20), \n\treleasedate DATE, \n\tresolution NUMERIC(10) NOT NULL, \n\tCONSTRAINT s_name PRIMARY KEY (song_name), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE, \n\tFOREIGN KEY(f_id) REFERENCES files (f_id) ON DELETE CASCADE, \n\tFOREIGN KEY(genre_is) REFERENCES genre (g_name) ON DELETE CASCADE, \n\tCHECK (rating>0 and rating<11)\n) \nCREATE TABLE stock (\n\t\"Shop_ID\" INTEGER, \n\t\"Device_ID\" INTEGER, \n\t\"Quantity\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\", \"Device_ID\"), \n\tFOREIGN KEY(\"Device_ID\") REFERENCES device (\"Device_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in stock and all categories for low cardinality columns :\nShop_ID : 1, 11, 2, 4, 3, 9\nDevice_ID : 4, 6\nQuantity : 110, 56, 124, 100, 200, 112, 134, 51\n*/\n \nCREATE TABLE photos (\n\tid INTEGER, \n\tcamera_lens_id INTEGER, \n\tmountain_id INTEGER, \n\tcolor TEXT, \n\tname TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(mountain_id) REFERENCES mountain (id), \n\tFOREIGN KEY(camera_lens_id) REFERENCES camera_lens (id)\n)\n/*\nColumns in photos and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\ncamera_lens_id : 1, 5, 7, 6, 10\nmountain_id : 1, 20, 2, 14, 12, 10\ncolor : Black/White, RBG\nname : life, wolfs, deers, grass, rabbits, sunset, cloud, river, monkey, the mountain\n*/\n \nCREATE TABLE \"Addresses\" (\n\t\"Address_ID\" INTEGER NOT NULL, \n\taddress_details VARCHAR(255), \n\tPRIMARY KEY (\"Address_ID\"), \n\tUNIQUE (\"Address_ID\")\n)\n/*\nColumns in Addresses and 3 examples in each column for high cardinality columns :\nAddress_ID : 1, 13, 11\naddress_details : 8220 Concepcion Neck Suite 394\nEast Beauview, LA 19968-4755, 465 Emely Bypass\nWest Mafalda, CO 23309, 11093 Balistreri Forge\nGaylordtown, VT 05705\n*/\n\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/*\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n*/\n" }, { "role": "user", "content": "What categories have two or more corresponding books that were made after 1989?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: category.\nThe SQL query I'll be generating is:\nSELECT category FROM book_club WHERE YEAR > 1989 GROUP BY category HAVING count(*) >= 2" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/*\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n*/\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(15) NOT NULL, \n\torder_date DATETIME, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\norder_date : 2018-03-21 11:20:46, 2018-03-22 14:57:30, 2018-03-17 07:13:53\n*/\n/*\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 11, 5, 15, 8, 4, 12, 3, 10\norder_status : Delivered, Cancelled\norder_details : None, Second time\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Sales\" (\n\tsales_transaction_id INTEGER, \n\tsales_details VARCHAR(255), \n\tPRIMARY KEY (sales_transaction_id), \n\tFOREIGN KEY(sales_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/*\nColumns in Sales and 3 examples in each column for high cardinality columns :\nsales_transaction_id : 1, 13, 11\n*/\n/*\nColumns in Sales and all categories for low cardinality columns :\nsales_details : t, f, s, e, y, n, x, p, o, a\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE debate (\n\t\"Debate_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Num_of_Audience\" INTEGER, \n\tPRIMARY KEY (\"Debate_ID\")\n)\n/*\nColumns in debate and all categories for low cardinality columns :\nDebate_ID : 1, 2, 5, 4, 6, 3\nDate : October 21, 2011, December 17, 2014, August 3, 2015, January 21, 2017, October 27, 2015, January 12, 2017\nVenue : Abu Dhabi , UAE, Doha , Qatar, Dubai , UAE, Manama , Bahrain\nNum_of_Audience : 342, 159, 90, 209, 313, 134\n*/\n \nCREATE TABLE farm_competition (\n\t\"Competition_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Theme\" TEXT, \n\t\"Host_city_ID\" INTEGER, \n\t\"Hosts\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\"), \n\tFOREIGN KEY(\"Host_city_ID\") REFERENCES city (\"City_ID\")\n)\n/*\nColumns in farm_competition and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 6, 3\nYear : 2004, 2013, 2005, 2006, 2003, 2002\nTheme : MTV Cube, Valentine's Day, Codehunters, Carnival M is back!, Aliens, MTV Asia Aid\nHost_city_ID : 1, 2, 5, 4, 3\nHosts : Mandy Moore and Ronan Keating, Alicia Keys, Shaggy and Coco Lee, Leehom Wang and Kelly Rowland, Miley Cyrus Jared Leto and Karen Mok, Vanness Wu and Michelle Branch\n*/\n \nCREATE TABLE \"ACCOUNTS\" (\n\tcustid BIGINT NOT NULL, \n\tname VARCHAR(64) NOT NULL, \n\tPRIMARY KEY (custid)\n)\n/*\nColumns in ACCOUNTS and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nname : Wang, O'mahony, Granger, Wesley, Weeks, Brown, Porter\n*/\n \nCREATE TABLE workshop (\n\t\"Workshop_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Workshop_ID\")\n)\n/*\nColumns in workshop and all categories for low cardinality columns :\nWorkshop_ID : 1, 2, 5, 4, 6, 3\nDate : July 5, 2011, August 21, 2007, October 8, 2007, January 14, 2008, August 25, 2007, August 18, 2007\nVenue : London UK, New York USA, Istanbul Turkey, New Jersey USA\nName : Workshop 2007, 2008 qualification, Anual Workshop 2011, ABC 2007, 2007 qualification, Conference 2007\n*/\n \nCREATE TABLE city (\n\tcity_id INTEGER NOT NULL, \n\tcity VARCHAR(50) NOT NULL, \n\tcountry_id INTEGER NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (city_id), \n\tFOREIGN KEY(country_id) REFERENCES country (country_id)\n)\n/*\nColumns in city and 3 examples in each column for high cardinality columns :\ncity_id : 87, 56, 65\ncity : Guaruj, Coacalco de Berriozbal, Almirante Brown\ncountry_id : 87, 78, 75\n*/\n/*\nColumns in city and all categories for low cardinality columns :\nlast_update : 2006-02-15 04:45:25\n*/\n \nCREATE TABLE \"Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Address_ID\" INTEGER, \n\t\"Channel_ID\" INTEGER NOT NULL, \n\t\"Event_Type_Code\" CHAR(15), \n\t\"Finance_ID\" INTEGER NOT NULL, \n\t\"Location_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Location_ID\") REFERENCES \"Locations\" (\"Location_ID\"), \n\tFOREIGN KEY(\"Address_ID\") REFERENCES \"Addresses\" (\"Address_ID\"), \n\tFOREIGN KEY(\"Finance_ID\") REFERENCES \"Finances\" (\"Finance_ID\"), \n\tUNIQUE (\"Event_ID\")\n)\n/*\nColumns in Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 1, 13, 11\nChannel_ID : 1, 13, 11\nFinance_ID : 1, 13, 10\n*/\n/*\nColumns in Events and all categories for low cardinality columns :\nAddress_ID : 13, 10, 2, 12, 3, 14, 15, 9\nEvent_Type_Code : Press Conferenc, Seminar, Ceremonies, Conference, Trade Show\nLocation_ID : 13, 11, 10, 5, 7, 8, 6, 12, 15, 9\n*/\n \nCREATE TABLE \"Engineer_Skills\" (\n\tengineer_id INTEGER NOT NULL, \n\tskill_id INTEGER NOT NULL, \n\tFOREIGN KEY(skill_id) REFERENCES \"Skills\" (skill_id), \n\tFOREIGN KEY(engineer_id) REFERENCES \"Maintenance_Engineers\" (engineer_id)\n)\n/*\nColumns in Engineer_Skills and 3 examples in each column for high cardinality columns :\nengineer_id : 13, 11, 2\n*/\n/*\nColumns in Engineer_Skills and all categories for low cardinality columns :\nskill_id : 1, 2, 3\n*/\n \nCREATE TABLE \"Participants_in_Events\" (\n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Participant_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Event_ID\", \"Participant_ID\"), \n\tFOREIGN KEY(\"Participant_ID\") REFERENCES \"Participants\" (\"Participant_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/*\nColumns in Participants_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 16, 95, 13\n*/\n/*\nColumns in Participants_in_Events and all categories for low cardinality columns :\nParticipant_ID : 26, 86, 37, 90, 36, 96, 66, 63, 60, 64\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Institution\" (\n\t\"Institution_id\" TEXT, \n\t\"Institution\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Type\" TEXT, \n\t\"Enrollment\" INTEGER, \n\t\"Team\" TEXT, \n\t\"Primary_Conference\" TEXT, \n\tbuilding_id TEXT, \n\tPRIMARY KEY (\"Institution_id\"), \n\tFOREIGN KEY(building_id) REFERENCES building (building_id)\n)\n/*\nColumns in Institution and 3 examples in each column for high cardinality columns :\nInstitution_id : 1, 2, 5\nInstitution : Ave Maria University, Lindenwood University–Belleville, Point University\nLocation : Mayville, North Dakota, Jacksonville, Florida, Babson Park, Florida\nEnrollment : 967, 616, 3102\nTeam : Gyrenes, Comets, Warriors\n*/\n/*\nColumns in Institution and all categories for low cardinality columns :\nFounded : 1937.0, 1881.0, 1927.0, 2003.0, 1883.0, 1866.0, 1998.0, 1884.0, 1889.0, 1890.0\nType : Public, Tribal, Private\nPrimary_Conference : MCAC, CalPac, Gulf Coast (GCAC), AAC, none, The Sun\nbuilding_id : 1, 2, 5, 7, 4, 3, 0\n*/\n \nCREATE TABLE exhibition (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Theme\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\t\"Ticket_Price\" REAL, \n\tPRIMARY KEY (\"Exhibition_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in exhibition and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 6, 3\nYear : 2004, 2009, 2005, 2008, 2006, 2007\nTheme : Christmas Tree, Santa Claus and Rudolph the Red-Nosed Reindeer, Summer, Christmas stocking, Spring, Santa Claus\nArtist_ID : 1, 2, 4, 6, 3\nTicket_Price : 19.95, 9.95, 29.95, 14.95, 16.95\n*/\n \nCREATE TABLE \"Dorm_amenity\" (\n\tamenid INTEGER, \n\tamenity_name VARCHAR(25)\n)\n/*\nColumns in Dorm_amenity and 3 examples in each column for high cardinality columns :\namenid : 922, 955, 900\namenity_name : Study Room, Allows Pets, Roof\n*/\n\n \nCREATE TABLE stadium (\n\tid INTEGER, \n\tname TEXT, \n\t\"Home_Games\" INTEGER, \n\t\"Average_Attendance\" REAL, \n\t\"Total_Attendance\" REAL, \n\t\"Capacity_Percentage\" REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in stadium and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : Gillette Stadium, Lincoln Financial Field, New Meadowlands Stadium\nAverage_Attendance : 70038.0, 87047.0, 71227.0\nTotal_Attendance : 553144.0, 566362.0, 550048.0\n*/\n/*\nColumns in stadium and all categories for low cardinality columns :\nHome_Games : 8\nCapacity_Percentage : 96.0, 108.8, 100.3, 100.0, 95.8, 90.7, 102.3, 98.4, 97.1, 95.3\n*/\n" }, { "role": "user", "content": "Show publishers with a book published in 1989 and a book in 1990." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher FROM book_club WHERE YEAR = 1989 INTERSECT SELECT publisher FROM book_club WHERE YEAR = 1990" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Dorm\" (\n\tdormid INTEGER, \n\tdorm_name VARCHAR(20), \n\tstudent_capacity INTEGER, \n\tgender VARCHAR(1)\n)\n/*\nColumns in Dorm and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\ndorm_name : University Hovels, Fawlty Towers, Anonymous Donor Hall, Smith Hall, Bud Jones Hall, Dorm-plex 2000, Grad Student Asylum\nstudent_capacity : 116, 400, 355, 40, 128, 85, 256\ngender : F, X, M\n*/\n \nCREATE TABLE \"Problem_Status_Codes\" (\n\tproblem_status_code VARCHAR(20), \n\tproblem_status_description VARCHAR(80), \n\tPRIMARY KEY (problem_status_code)\n)\n/*\nColumns in Problem_Status_Codes and all categories for low cardinality columns :\nproblem_status_code : Solved, Reported\nproblem_status_description : Solved, Reported\n*/\n \nCREATE TABLE \"Ship\" (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Built_Year\" REAL, \n\t\"Class\" TEXT, \n\t\"Flag\" TEXT, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/*\nColumns in Ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : HMS Trojan, HMS Destiny, HMS Phalarope, HMS Undine, HMS Manxman, HM Cutter Avenger, HM Sloop Sparrow, HM Schooner Hotspur, HMS Gorgon\nType : Panamax\nBuilt_Year : 1997.0, 1998.0\nClass : GL, KR\nFlag : Panama, Malta\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Royal_Family\" (\n\t\"Royal_Family_ID\" INTEGER NOT NULL, \n\t\"Royal_Family_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Royal_Family_ID\"), \n\tFOREIGN KEY(\"Royal_Family_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/*\nColumns in Royal_Family and all categories for low cardinality columns :\nRoyal_Family_ID : 9919, 9561\nRoyal_Family_Details : None\n*/\n \nCREATE TABLE albums (\n\tid INTEGER, \n\ttitle VARCHAR(160) NOT NULL, \n\tartist_id INTEGER NOT NULL, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(artist_id) REFERENCES artists (id)\n)\n/*\nColumns in albums and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\ntitle : The Number of The Beast, One By One, Dance Of Death\nartist_id : 87, 56, 95\n*/\n\n \nCREATE TABLE company (\n\t\"Company_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Main_Industry\" TEXT, \n\t\"Sales_billion\" REAL, \n\t\"Profits_billion\" REAL, \n\t\"Assets_billion\" REAL, \n\t\"Market_Value\" REAL, \n\tPRIMARY KEY (\"Company_ID\")\n)\n/*\nColumns in company and all categories for low cardinality columns :\nCompany_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nRank : 1, 11, 5, 7, 8, 4, 6, 3, 10, 9\nCompany : ExxonMobil, HSBC, General Electric, PetroChina, Industrial and Commercial Bank of China, Wells Fargo, Berkshire Hathaway, Petrobras, Royal Dutch Shell, BP\nHeadquarters : UK, China, Brazil, USA, Netherlands\nMain_Industry : Conglomerate, Banking, Oil and gas\nSales_billion : 143.7, 310.1, 433.5, 147.3, 470.2, 145.9, 87.6, 82.6, 375.5, 102.0\nProfits_billion : 20.1, 41.1, 30.9, 25.1, 14.2, 25.7, 20.6, 16.2, 15.9, 10.3\nAssets_billion : 1313.9, 319.4, 717.2, 340.5, 331.1, 2039.1, 292.5, 304.7, 392.6, 2550.0\nMarket_Value : 237.4, 213.7, 227.6, 147.4, 164.3, 202.2, 294.7, 180.0, 407.4, 178.7\n*/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/*\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n*/\n \nCREATE TABLE constructors (\n\t\"constructorId\" INTEGER, \n\t\"constructorRef\" TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\turl TEXT, \n\tPRIMARY KEY (\"constructorId\")\n)\n/*\nColumns in constructors and 3 examples in each column for high cardinality columns :\nconstructorId : 87, 56, 65\nconstructorRef : mf1, prost, lambo\nname : McLaren, Protos, Eagle-Climax\nnationality : Mexican, Russian, British\nurl : http://en.wikipedia.org/wiki/Minardi, http://en.wikipedia.org/wiki/Officine_Specializate_Costruzione_Automobili, http://en.wikipedia.org/wiki/Scirocco-Powell\n*/\n\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/*\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n*/\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/*\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n*/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Counties_Represented\" TEXT, \n\t\"District\" INTEGER, \n\t\"Delegate\" TEXT, \n\t\"Party\" INTEGER, \n\t\"First_Elected\" REAL, \n\t\"Committee\" TEXT, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"District\") REFERENCES county (\"County_Id\"), \n\tFOREIGN KEY(\"Party\") REFERENCES party (\"Party_ID\")\n)\n/*\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 7, 8, 4, 6, 3\nCounties_Represented : 09.1 9A, 13, 12.1 12A, 12.2 12B\nDistrict : 1, 2, 4, 3\nDelegate : Miller, Warren E. Warren E. Miller, Bobo, Elizabeth Elizabeth Bobo, Pendergrass, Shane E. Shane Pendergrass, Bates, Gail H. Gail H. Bates, DeBoy, Steven J. Sr. Steven J. DeBoy, Sr., Guzzone, Guy Guy Guzzone, Turner, Frank S. Frank S. Turner, Malone, James E. Jr. James E. Malone, Jr.\nParty : 1, 2, 7, 4, 3\nFirst_Elected : 2002.0, 2006.0, 1994.0, 2003.0\nCommittee : Environmental Matters, Economic Matters, Ways and Means, Environmental Matters (Vice-Chair), Health and Government Operations, Appropriations\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE wrestler (\n\t\"Wrestler_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Reign\" TEXT, \n\t\"Days_held\" TEXT, \n\t\"Location\" TEXT, \n\t\"Event\" TEXT, \n\tPRIMARY KEY (\"Wrestler_ID\")\n)\n/*\nColumns in wrestler and all categories for low cardinality columns :\nWrestler_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Fishman, El Samurai §, Rey Misterio Sr., Último Dragón §, Shinjiro Otani §, Gran Hamada, Jushin Liger §, Villaño IV, The Great Sasuke §, El Samurai\nReign : 1, 2\nDays_held : 1, 113, 35, 56, 183, 1285, 960, 344, 99, 54\nLocation : Nagoya , Japan, Tijuana , Mexico, Sapporo , Japan, Tokyo , Japan, Osaka , Japan\nEvent : Wrestling World 1997, Live event\n*/\n \nCREATE TABLE musical (\n\t\"Musical_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Award\" TEXT, \n\t\"Category\" TEXT, \n\t\"Nominee\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Musical_ID\")\n)\n/*\nColumns in musical and all categories for low cardinality columns :\nMusical_ID : 1, 2, 5, 7, 4, 6, 3\nName : The Book of Mormon, Les Misérables, Rent, Chicago, West Side Story, The Phantom of the Opera, Wicked\nYear : 1986\nAward : Drama Desk Award, Tony Award\nCategory : Outstanding Director of a Musical, Best Direction of a Musical, Best Choreography, Best Performance by a Leading Actor in a Musical, Outstanding Choreography, Best Book of a Musical, Outstanding Actor in a Musical\nNominee : Bob Fosse, Cleavant Derricks\nResult : Nominated, Won\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Part_Faults\" (\n\tpart_fault_id INTEGER, \n\tpart_id INTEGER NOT NULL, \n\tfault_short_name VARCHAR(20), \n\tfault_description VARCHAR(255), \n\tother_fault_details VARCHAR(255), \n\tPRIMARY KEY (part_fault_id), \n\tFOREIGN KEY(part_id) REFERENCES \"Parts\" (part_id)\n)\n/*\nColumns in Part_Faults and 3 examples in each column for high cardinality columns :\npart_fault_id : 1, 13, 11\n*/\n/*\nColumns in Part_Faults and all categories for low cardinality columns :\npart_id : 1, 2, 3\nfault_short_name : PW, TW, MW\nfault_description : Medium Scale Wrong, Top Parts Wrong, Package Wrong\nother_fault_details : None\n*/\n" }, { "role": "user", "content": "What are the publishers who have published a book in both 1989 and 1990?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher FROM book_club WHERE YEAR = 1989 INTERSECT SELECT publisher FROM book_club WHERE YEAR = 1990" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE competition_record (\n\t\"Competition_ID\" INTEGER, \n\t\"Farm_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\tPRIMARY KEY (\"Competition_ID\", \"Farm_ID\"), \n\tFOREIGN KEY(\"Farm_ID\") REFERENCES farm (\"Farm_ID\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES farm_competition (\"Competition_ID\")\n)\n/*\nColumns in competition_record and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 3\nFarm_ID : 1, 2, 5, 7, 8, 4, 3\nRank : 1, 2, 4, 3\n*/\n \nCREATE TABLE review (\n\ta_id INTEGER NOT NULL, \n\tu_id INTEGER NOT NULL, \n\ti_id INTEGER NOT NULL, \n\trating INTEGER DEFAULT NULL, \n\trank INTEGER DEFAULT NULL, \n\tPRIMARY KEY (a_id), \n\tFOREIGN KEY(i_id) REFERENCES item (i_id), \n\tFOREIGN KEY(u_id) REFERENCES useracct (u_id)\n)\n/*\nColumns in review and all categories for low cardinality columns :\na_id : 1, 2, 5, 7, 4, 6, 3\nu_id : 1, 2\ni_id : 1, 5, 7, 4, 3\nrating : 7, 10, 5, 6\nrank : 1, 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Track\" (\n\t\"TrackId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(200) NOT NULL, \n\t\"AlbumId\" INTEGER DEFAULT NULL, \n\t\"MediaTypeId\" INTEGER NOT NULL, \n\t\"GenreId\" INTEGER DEFAULT NULL, \n\t\"Composer\" VARCHAR(220) DEFAULT NULL, \n\t\"Milliseconds\" INTEGER NOT NULL, \n\t\"Bytes\" INTEGER DEFAULT NULL, \n\t\"UnitPrice\" DECIMAL(10, 2) NOT NULL, \n\tPRIMARY KEY (\"TrackId\"), \n\tFOREIGN KEY(\"MediaTypeId\") REFERENCES \"MediaType\" (\"MediaTypeId\"), \n\tFOREIGN KEY(\"GenreId\") REFERENCES \"Genre\" (\"GenreId\"), \n\tFOREIGN KEY(\"AlbumId\") REFERENCES \"Album\" (\"AlbumId\")\n)\n/*\nColumns in Track and 3 examples in each column for high cardinality columns :\nTrackId : 87, 56, 65\nName : Snoopy's search-Red baron, The Winner Loses, Leave My Girl Alone\nAlbumId : 17, 9, 16\nComposer : Ned Fairchild, Tony Iommi, Bill Ward, Geezer Butler, Ozzy Osbourne, Berry Gordy, Jr./Janie Bradford\nMilliseconds : 263497, 307617, 204721\nBytes : 6859518, 2301989, 6420530\n*/\n/*\nColumns in Track and all categories for low cardinality columns :\nMediaTypeId : 1, 2\nGenreId : 1, 2, 5, 4, 6, 3\nUnitPrice : 0.99\n*/\n \nCREATE TABLE \"Inst\" (\n\t\"instID\" INTEGER, \n\tname TEXT, \n\tcountry TEXT, \n\tPRIMARY KEY (\"instID\")\n)\n/*\nColumns in Inst and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\nname : Northeastern University, INRIA, University of Oxford, Indiana University, Tohoku University, University of Pennsylvania, Portland State University, Google\ncountry : Japan, UK, USA, France\n*/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/*\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n*/\n \nCREATE TABLE flight (\n\tflno NUMERIC(4, 0), \n\torigin TEXT(20), \n\tdestination TEXT(20), \n\tdistance NUMERIC(6, 0), \n\tdeparture_date DATE, \n\tarrival_date DATE, \n\tprice NUMERIC(7, 2), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (flno), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid)\n) \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/*\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n*/\n \nCREATE TABLE basketball_match (\n\t\"Team_ID\" INTEGER, \n\t\"School_ID\" INTEGER, \n\t\"Team_Name\" TEXT, \n\t\"ACC_Regular_Season\" TEXT, \n\t\"ACC_Percent\" TEXT, \n\t\"ACC_Home\" TEXT, \n\t\"ACC_Road\" TEXT, \n\t\"All_Games\" TEXT, \n\t\"All_Games_Percent\" INTEGER, \n\t\"All_Home\" TEXT, \n\t\"All_Road\" TEXT, \n\t\"All_Neutral\" TEXT, \n\tPRIMARY KEY (\"Team_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES university (\"School_ID\")\n)\n/*\nColumns in basketball_match and all categories for low cardinality columns :\nTeam_ID : 1, 2, 4, 3\nSchool_ID : 1, 2, 4, 5\nTeam_Name : Virginia Tech, North Carolina, Clemson, Duke\nACC_Regular_Season : 9–7, 14–2, 10–6, 13–3\nACC_Percent : .813, .625, .563, .875\nACC_Home : 7–1, 6–2\nACC_Road : 3–5, 6–2, 8–0\nAll_Games : 21–14, 35–2, 24–10, 28–6\nAll_Games_Percent : 0.824, 0.6, 0.706, 0.946\nAll_Home : 14–3, 14–2, 15–1\nAll_Road : 4–8, 8–2, 13–0, 6–5\nAll_Neutral : 9–1, 4–3, 3–3, 5–3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Institution\" (\n\t\"Institution_id\" TEXT, \n\t\"Institution\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Type\" TEXT, \n\t\"Enrollment\" INTEGER, \n\t\"Team\" TEXT, \n\t\"Primary_Conference\" TEXT, \n\tbuilding_id TEXT, \n\tPRIMARY KEY (\"Institution_id\"), \n\tFOREIGN KEY(building_id) REFERENCES building (building_id)\n)\n/*\nColumns in Institution and 3 examples in each column for high cardinality columns :\nInstitution_id : 1, 2, 5\nInstitution : Ave Maria University, Lindenwood University–Belleville, Point University\nLocation : Mayville, North Dakota, Jacksonville, Florida, Babson Park, Florida\nEnrollment : 967, 616, 3102\nTeam : Gyrenes, Comets, Warriors\n*/\n/*\nColumns in Institution and all categories for low cardinality columns :\nFounded : 1937.0, 1881.0, 1927.0, 2003.0, 1883.0, 1866.0, 1998.0, 1884.0, 1889.0, 1890.0\nType : Public, Tribal, Private\nPrimary_Conference : MCAC, CalPac, Gulf Coast (GCAC), AAC, none, The Sun\nbuilding_id : 1, 2, 5, 7, 4, 3, 0\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"STUDENT\" (\n\t\"STU_NUM\" INTEGER, \n\t\"STU_LNAME\" VARCHAR(15), \n\t\"STU_FNAME\" VARCHAR(15), \n\t\"STU_INIT\" VARCHAR(1), \n\t\"STU_DOB\" DATETIME, \n\t\"STU_HRS\" INTEGER, \n\t\"STU_CLASS\" VARCHAR(2), \n\t\"STU_GPA\" FLOAT, \n\t\"STU_TRANSFER\" NUMERIC, \n\t\"DEPT_CODE\" VARCHAR(18), \n\t\"STU_PHONE\" VARCHAR(4), \n\t\"PROF_NUM\" INTEGER, \n\tPRIMARY KEY (\"STU_NUM\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n) \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/*\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n*/\n \nCREATE TABLE \"Instruments\" (\n\t\"SongId\" INTEGER, \n\t\"BandmateId\" INTEGER, \n\t\"Instrument\" TEXT, \n\tPRIMARY KEY (\"SongId\", \"BandmateId\", \"Instrument\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"BandmateId\") REFERENCES \"Band\" (\"Id\")\n)\n/*\nColumns in Instruments and all categories for low cardinality columns :\nSongId : \nBandmateId : \nInstrument : \n*/\n \nCREATE TABLE \"Financial_Transactions\" (\n\ttransaction_id INTEGER NOT NULL, \n\tprevious_transaction_id INTEGER, \n\taccount_id INTEGER NOT NULL, \n\tcard_id INTEGER NOT NULL, \n\ttransaction_type VARCHAR(15) NOT NULL, \n\ttransaction_date DATETIME, \n\ttransaction_amount DOUBLE, \n\ttransaction_comment VARCHAR(255), \n\tother_transaction_details VARCHAR(255), \n\tFOREIGN KEY(account_id) REFERENCES \"Accounts\" (account_id), \n\tFOREIGN KEY(card_id) REFERENCES \"Customers_Cards\" (card_id)\n)\n/*\nColumns in Financial_Transactions and 3 examples in each column for high cardinality columns :\ntransaction_id : 1, 13, 11\nprevious_transaction_id : 925, 947, 986\naccount_id : 1, 13, 11\ntransaction_date : 2018-03-24 10:39:09, 2018-03-23 21:59:28, 2018-03-24 05:45:57\ntransaction_amount : 486.56, 1336.21, 945.43\n*/\n/*\nColumns in Financial_Transactions and all categories for low cardinality columns :\ncard_id : 1, 11, 2, 5, 7, 4, 6, 12, 3, 9\ntransaction_type : Refund, Payment\ntransaction_comment : None\nother_transaction_details : None\n*/\n" }, { "role": "user", "content": "Show all publishers which do not have a book in 1989." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher FROM book_club EXCEPT SELECT publisher FROM book_club WHERE YEAR = 1989" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE train (\n\tid INTEGER, \n\ttrain_number INTEGER, \n\tname TEXT, \n\torigin TEXT, \n\tdestination TEXT, \n\ttime TEXT, \n\tinterval TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in train and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\ntrain_number : 16526, 56700, 56701\ntime : 10:38, 16:59, 11:15\n*/\n/*\nColumns in train and all categories for low cardinality columns :\nname : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\norigin : Quilon, Mumbai, Bangalore, Madurai, Nagercoil, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ndestination : Mumbai, Mangalore, Bangalore, Madurai, Quilon Junction, Chennai, Guruvayur, Kanniyakumari, Trivandrum\ninterval : Daily\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE mission (\n\t\"Mission_ID\" INTEGER, \n\t\"Ship_ID\" INTEGER, \n\t\"Code\" TEXT, \n\t\"Launched_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Speed_knots\" INTEGER, \n\t\"Fate\" TEXT, \n\tPRIMARY KEY (\"Mission_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES ship (\"Ship_ID\")\n)\n/*\nColumns in mission and all categories for low cardinality columns :\nMission_ID : 1, 2, 5, 7, 4, 6, 3\nShip_ID : 1, 2, 5, 7, 8, 6, 3\nCode : VMV-3, VMV-5, VMV-6, VMV-4 Former: Sterling, VMV-2, VMV-7, VMV-1\nLaunched_Year : 1932, 1916, 1930, 1931\nLocation : Turku , Finland, Helsinki , Finland, Norway, Germany, Uusikaupunki , Finland\nSpeed_knots : 16, 25, 23\nFate : Retired 1939, Decommissioned 1950, Lost (burned and sunk) 1933, Lost (burned) 1931, Decommissioned 1959, Decommissioned 1960\n*/\n \nCREATE TABLE repair_assignment (\n\ttechnician_id INTEGER, \n\t\"repair_ID\" INTEGER, \n\t\"Machine_ID\" INTEGER, \n\tPRIMARY KEY (technician_id, \"repair_ID\", \"Machine_ID\"), \n\tFOREIGN KEY(\"Machine_ID\") REFERENCES machine (\"Machine_ID\"), \n\tFOREIGN KEY(\"repair_ID\") REFERENCES repair (\"repair_ID\"), \n\tFOREIGN KEY(technician_id) REFERENCES technician (technician_id)\n)\n/*\nColumns in repair_assignment and all categories for low cardinality columns :\ntechnician_id : 1, 2, 5, 7, 3\nrepair_ID : 1, 2, 5, 8, 4, 3\nMachine_ID : 1, 2, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResName\" VARCHAR(100), \n\t\"Address\" VARCHAR(100), \n\t\"Rating\" INTEGER, \n\tPRIMARY KEY (\"ResID\")\n)\n/*\nColumns in Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResName : Subway, Honeygrow\nAddress : 3212 St Paul St, Baltimore, MD 21218, 3233 St Paul St, Baltimore, MD 21218\nRating : 4, 3\n*/\n \nCREATE TABLE \"Order_Items\" (\n\torder_item_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\torder_id INTEGER NOT NULL, \n\torder_item_status VARCHAR(10) NOT NULL, \n\torder_item_details VARCHAR(255), \n\tPRIMARY KEY (order_item_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/*\nColumns in Order_Items and 3 examples in each column for high cardinality columns :\norder_item_id : 1, 13, 11\n*/\n/*\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 1, 3, 11, 7, 8, 4, 12, 14, 15\norder_id : 11, 5, 15, 7, 8, 6, 14, 10, 9\norder_item_status : Finish, Cancel, Payed\norder_item_details : None\n*/\n \nCREATE TABLE \"Bookings\" (\n\tbooking_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tbooking_status_code VARCHAR(10) NOT NULL, \n\treturned_damaged_yn VARCHAR(40), \n\tbooking_start_date DATETIME, \n\tbooking_end_date DATETIME, \n\tcount_hired VARCHAR(40), \n\tamount_payable DECIMAL(19, 4), \n\tamount_of_discount DECIMAL(19, 4), \n\tamount_outstanding DECIMAL(19, 4), \n\tamount_of_refund DECIMAL(19, 4), \n\tPRIMARY KEY (booking_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Bookings and 3 examples in each column for high cardinality columns :\nbooking_id : 1, 13, 11\nbooking_start_date : 2016-04-25 11:04:18, 2016-11-06 20:54:26, 2017-04-28 08:35:56\nbooking_end_date : 2018-03-04 21:42:45, 2018-02-19 21:53:31, 2017-10-02 07:28:09\ncount_hired : 843, 298, 236\namount_payable : 214.3900, 306.2600, 386.9200\namount_of_discount : 48.7300, 61.5500, 45.0600\namount_outstanding : 26.0400, 66.0100, 93.8800\namount_of_refund : 135.9400, 126.1000, 124.9500\n*/\n/*\nColumns in Bookings and all categories for low cardinality columns :\ncustomer_id : 11, 10, 7, 8, 3, 15, 9\nbooking_status_code : Provisional, Confirmed\nreturned_damaged_yn : 1, 0\n*/\n \nCREATE TABLE company (\n\t\"Company_ID\" INTEGER, \n\t\"Rank\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Main_Industry\" TEXT, \n\t\"Sales_billion\" REAL, \n\t\"Profits_billion\" REAL, \n\t\"Assets_billion\" REAL, \n\t\"Market_Value\" REAL, \n\tPRIMARY KEY (\"Company_ID\")\n)\n/*\nColumns in company and all categories for low cardinality columns :\nCompany_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nRank : 1, 11, 5, 7, 8, 4, 6, 3, 10, 9\nCompany : ExxonMobil, HSBC, General Electric, PetroChina, Industrial and Commercial Bank of China, Wells Fargo, Berkshire Hathaway, Petrobras, Royal Dutch Shell, BP\nHeadquarters : UK, China, Brazil, USA, Netherlands\nMain_Industry : Conglomerate, Banking, Oil and gas\nSales_billion : 143.7, 310.1, 433.5, 147.3, 470.2, 145.9, 87.6, 82.6, 375.5, 102.0\nProfits_billion : 20.1, 41.1, 30.9, 25.1, 14.2, 25.7, 20.6, 16.2, 15.9, 10.3\nAssets_billion : 1313.9, 319.4, 717.2, 340.5, 331.1, 2039.1, 292.5, 304.7, 392.6, 2550.0\nMarket_Value : 237.4, 213.7, 227.6, 147.4, 164.3, 202.2, 294.7, 180.0, 407.4, 178.7\n*/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Train_Num\" TEXT, \n\t\"Name\" TEXT, \n\t\"From\" TEXT, \n\t\"Arrival\" TEXT, \n\t\"Railway_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/*\nColumns in train and all categories for low cardinality columns :\nTrain_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nTrain_Num : 57136, 57135, 16032, 12140, 51195, 12139, 16031, 11401, 16094\nName : Wardha-Ballarshah Pass, Nagpur-Kazipet Pass, Ballarshah-Mumbai Pass, Nandigram Exp, Lucknow-Chennai Exp, Sewagram Exp, Andaman Exp, Kazipet-Nagpur Pass\nFrom : Lucknow, Ballarshah, Nagpur, Kazipet, Mumbai CST, Jammu Tawi, Wardha, Chennai\nArrival : 23:39, 08:54, 23:44, 05:09, 09:48, 13:28, 13:04, 09:08\nRailway_ID : 1, 2, 5, 7, 3, 10, 9\n*/\n \nCREATE TABLE \"Customers\" (\n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Customer_Details\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Customer_ID\")\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\nCustomer_ID : 1, 13, 11\nCustomer_Details : Miss Felicita Reichel, Selena Gerhold, Mrs. Liza Heller V\n*/\n\n \nCREATE TABLE club (\n\t\"Club_ID\" INTEGER, \n\tname TEXT, \n\t\"Region\" TEXT, \n\t\"Start_year\" TEXT, \n\tPRIMARY KEY (\"Club_ID\")\n)\n/*\nColumns in club and all categories for low cardinality columns :\nClub_ID : 1, 2, 5, 4, 6, 3\nname : AIB, IFG, HGS2, HSBIF, BK Slide, ASC\nRegion : Japan, UK, China, Brazil, England, USA\nStart_year : 2009, 2001, 2005, 2000, 1998, 2011\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_gender VARCHAR(1), \n\tstaff_name VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 1, 13, 11\nstaff_name : Yolanda, Tom, Melody\n*/\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_gender : 1, 0\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"COURSE\" (\n\t\"CRS_CODE\" VARCHAR(10), \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"CRS_DESCRIPTION\" VARCHAR(35), \n\t\"CRS_CREDIT\" FLOAT, \n\tPRIMARY KEY (\"CRS_CODE\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/*\nColumns in COURSE and all categories for low cardinality columns :\nCRS_CODE : ACCT-212, QM-362, QM-261, CIS-420, CIS-220, ACCT-211\nDEPT_CODE : CIS, ACCT\nCRS_DESCRIPTION : Statistical Applications, Accounting I, Accounting II, Database Design and Implementation, Intro. to Microcomputing, Intro. to Statistics\nCRS_CREDIT : 3.0, 4.0\n*/\n \nCREATE TABLE management (\n\t\"department_ID\" INTEGER, \n\t\"head_ID\" INTEGER, \n\ttemporary_acting TEXT, \n\tPRIMARY KEY (\"department_ID\", \"head_ID\"), \n\tFOREIGN KEY(\"head_ID\") REFERENCES head (\"head_ID\"), \n\tFOREIGN KEY(\"department_ID\") REFERENCES department (\"Department_ID\")\n)\n/*\nColumns in management and all categories for low cardinality columns :\ndepartment_ID : 7, 15, 2, 11\nhead_ID : 5, 4, 6, 3, 10\ntemporary_acting : Yes, No\n*/\n \nCREATE TABLE \"Has_Allergy\" (\n\t\"StuID\" INTEGER, \n\t\"Allergy\" VARCHAR(20), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"Allergy\") REFERENCES \"Allergy_Type\" (\"Allergy\")\n)\n/*\nColumns in Has_Allergy and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nAllergy : Soy, Milk, Eggs\n*/\n\n \nCREATE TABLE \"League\" (\n\tid INTEGER, \n\tcountry_id INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(country_id) REFERENCES \"Country\" (id)\n)\n/*\nColumns in League and 3 examples in each column for high cardinality columns :\nid : 1, 19694, 7809\ncountry_id : 1, 19694, 7809\nname : Portugal Liga ZON Sagres, England Premier League, Belgium Jupiler League\n*/\n\n" }, { "role": "user", "content": "Which publishers did not publish a book in 1989?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: book_club.\nFrom these tables, I'll be using the following columns: publisher.\nThe SQL query I'll be generating is:\nSELECT publisher FROM book_club EXCEPT SELECT publisher FROM book_club WHERE YEAR = 1989" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Claim_Headers\" (\n\t\"Claim_Header_ID\" INTEGER NOT NULL, \n\t\"Claim_Status_Code\" CHAR(15) NOT NULL, \n\t\"Claim_Type_Code\" CHAR(15) NOT NULL, \n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Date_of_Claim\" DATETIME, \n\t\"Date_of_Settlement\" DATETIME, \n\t\"Amount_Claimed\" DECIMAL(20, 4), \n\t\"Amount_Piad\" DECIMAL(20, 4), \n\tPRIMARY KEY (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Policy_ID\") REFERENCES \"Policies\" (\"Policy_ID\")\n)\n/*\nColumns in Claim_Headers and 3 examples in each column for high cardinality columns :\nClaim_Header_ID : 69, 56, 45\nDate_of_Claim : 2016-06-12 23:04:58, 2016-09-26 04:03:48, 2016-09-29 02:42:22\nDate_of_Settlement : 2018-01-16 06:35:15, 2017-12-06 17:10:03, 2017-11-21 09:06:04\nAmount_Claimed : 783.4200, 349.1500, 756.2700\nAmount_Piad : 309.2000, 536.9900, 643.8200\n*/\n/*\nColumns in Claim_Headers and all categories for low cardinality columns :\nClaim_Status_Code : Disputed, In Progress, Settled\nClaim_Type_Code : Child Birth, Overtime Meal Subsidy, Handphone Subsidy\nPolicy_ID : 287, 507, 628, 125, 626, 518\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Membership_card\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Time_of_purchase\" INTEGER, \n\t\"Level_of_membership\" INTEGER, \n\t\"Address\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Peeler, Russell, Rizzo, Todd, Campbell, Jessie, Breton, Robert, Komisarjevsky, Joshua, Webb, Daniel, Ashby, Lazale, Hayes, Steven, Reynolds, Richard, Cobb, Sedrick\nMembership_card : White, Black\nAge : 67, 45, 33, 50, 34, 42, 29, 51, 35\nTime_of_purchase : 26, 20, 44, 24, 18, 27, 41\nLevel_of_membership : 1, 2, 5, 4, 6, 3, 22\nAddress : Hartford, Bridgeport, Cheshire, Waterbury\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Products_for_Hire\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(15) NOT NULL, \n\tdaily_hire_cost DECIMAL(19, 4), \n\tproduct_name VARCHAR(80), \n\tproduct_description VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products_for_Hire and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 4, 3\nproduct_type_code : Din_Plates, Cutlery\ndaily_hire_cost : 18.5000, 39.5800, 15.6200, 39.7300, 26.1500\nproduct_name : DVD collection B, DVD collection A, Book collection C, Book collection A, Book collection B\nproduct_description : The Great Gatsby, Anna Karenina, One Hundred Years of Solitude, War and Peace, Twilight\n*/\n \nCREATE TABLE weather (\n\tdate TEXT, \n\tmax_temperature_f INTEGER, \n\tmean_temperature_f INTEGER, \n\tmin_temperature_f INTEGER, \n\tmax_dew_point_f INTEGER, \n\tmean_dew_point_f INTEGER, \n\tmin_dew_point_f INTEGER, \n\tmax_humidity INTEGER, \n\tmean_humidity INTEGER, \n\tmin_humidity INTEGER, \n\tmax_sea_level_pressure_inches NUMERIC, \n\tmean_sea_level_pressure_inches NUMERIC, \n\tmin_sea_level_pressure_inches NUMERIC, \n\tmax_visibility_miles INTEGER, \n\tmean_visibility_miles INTEGER, \n\tmin_visibility_miles INTEGER, \n\t\"max_wind_Speed_mph\" INTEGER, \n\tmean_wind_speed_mph INTEGER, \n\tmax_gust_speed_mph INTEGER, \n\tprecipitation_inches INTEGER, \n\tcloud_cover INTEGER, \n\tevents TEXT, \n\twind_dir_degrees INTEGER, \n\tzip_code INTEGER\n)\n/*\nColumns in weather and 3 examples in each column for high cardinality columns :\ndate : 10/28/2013, 9/8/2013, 9/27/2013\nmax_temperature_f : 87, 53, 56\nmean_temperature_f : 53, 56, 65\nmin_temperature_f : 53, 56, 49\nmax_dew_point_f : 53, 56, 49\nmean_dew_point_f : 53, 56, 49\nmin_dew_point_f : 53, 56, 49\nmax_humidity : 87, 53, 56\nmean_humidity : 79, 53, 87\nmin_humidity : 53, 56, 65\nmax_sea_level_pressure_inches : 30.1500000000, 30.1800000000, 30.0700000000\nmean_sea_level_pressure_inches : 29.4300000000, 30.1500000000, 30.1800000000\nmin_sea_level_pressure_inches : 30.1800000000, 30.0700000000, 30.0600000000\nmin_visibility_miles : 1, 2, 5\nmax_wind_Speed_mph : 36, 17, 21\nmean_wind_speed_mph : 19, 21, 9\nmax_gust_speed_mph : , 36, 17\nprecipitation_inches : 0.42, 0.09, 0.64\nwind_dir_degrees : 75, 291, 304\n*/\n/*\nColumns in weather and all categories for low cardinality columns :\nmax_visibility_miles : 10, 9\nmean_visibility_miles : 5, 7, 8, 6, 10, 9\ncloud_cover : 1, 2, 5, 7, 8, 4, 6, 3, 0\nevents : , rain, Rain, Fog-Rain, Fog\nzip_code : 94107, 94063\n*/\n \nCREATE TABLE gas_station (\n\t\"Station_ID\" INTEGER, \n\t\"Open_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Manager_Name\" TEXT, \n\t\"Vice_Manager_Name\" TEXT, \n\t\"Representative_Name\" TEXT, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in gas_station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nOpen_Year : 2004, 2009, 2005\nLocation : Channel Hill, Newport Rd, Herne Ave\n*/\n/*\nColumns in gas_station and all categories for low cardinality columns :\nManager_Name : Simon Cope Derek Marloe, BryanDenman, Luke Rowe, BrianWingrave, Bryan Taylor, Jon Rowe, Tony Bristow, Tom Whit, SimonMarloe, Colin Denman\nVice_Manager_Name : TonyBristow, Russell Brown, Russell Denman, Martin Freeman, Simon Gaywood, James Holland-Leader, James Colin , JameMarloe, Steve Parsons, Martin Garnham\nRepresentative_Name : Andrew Russell, Chris Pyatt, Tim Read, Ray Hughes, Simon Gaywood, Tony Gibb, Clive Burr, Courtney Rowe, Rob Jefferies , Dave Edwards Roger \n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE \"Room\" (\n\t\"RoomNumber\" INTEGER NOT NULL, \n\t\"RoomType\" VARCHAR(30) NOT NULL, \n\t\"BlockFloor\" INTEGER NOT NULL, \n\t\"BlockCode\" INTEGER NOT NULL, \n\t\"Unavailable\" BOOLEAN NOT NULL, \n\tPRIMARY KEY (\"RoomNumber\"), \n\tCONSTRAINT \"fk_Room_Block_PK\" FOREIGN KEY(\"BlockFloor\", \"BlockCode\") REFERENCES \"Block\" (\"BlockFloor\", \"BlockCode\")\n)\n/*\nColumns in Room and 3 examples in each column for high cardinality columns :\nRoomNumber : 303, 102, 312\n*/\n/*\nColumns in Room and all categories for low cardinality columns :\nRoomType : Single\nBlockFloor : 1, 2, 4, 3\nBlockCode : 1, 2, 3\nUnavailable : False, True\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/*\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Age\" REAL, \n\t\"Height\" REAL, \n\t\"Hometown\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Rosa Clarissa Ortíz Melo, Elizabeth Quiñónez Aroyo, Paul Hamm, Nadia Caba Rodríguez, Eve Tatiana Cruz Oviedo, Clary Sermina Delgado Cid, Lorraine Súarez Carmona, Ashley Pérez Cabrera, Marina Castro Medina, Endis de los Santos Álvarez\nAge : 24.0, 19.0, 21.0, 23.0, 22.0, 20.0\nHeight : 1.7, 1.76, 1.72, 1.79, 1.75, 1.71, 1.81\nHometown : Santo Domingo, La Romana, Santiago de los Caballeros, Bonao, Los Alcarrizos, Miami\n*/\n" }, { "role": "user", "content": "Show all movie titles, years, and directors, ordered by budget." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: title, YEAR, director, budget_million.\nThe SQL query I'll be generating is:\nSELECT title , YEAR , director FROM movie ORDER BY budget_million" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Companies\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Headquarters\" TEXT, \n\t\"Industry\" TEXT, \n\t\"Sales_billion\" REAL, \n\t\"Profits_billion\" REAL, \n\t\"Assets_billion\" REAL, \n\t\"Market_Value_billion\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Companies and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : PetroChina, Berkshire Hathaway, Petrobras\nSales_billion : 69.2, 189.6, 421.8\nProfits_billion : 16.4, 19.9, 17.4\nAssets_billion : 2467.9, 192.8, 1913.9\nMarket_Value_billion : 239.5, 186.5, 224.8\n*/\n/*\nColumns in Companies and all categories for low cardinality columns :\nHeadquarters : Spain, UK, China, Brazil, France, Russia, USA, Netherlands\nIndustry : Retailing, Conglomerate, Oil and gas, Telecommunications, Banking\n*/\n \nCREATE TABLE dept_locations (\n\t\"Dnumber\" INTEGER, \n\t\"Dlocation\" TEXT, \n\tPRIMARY KEY (\"Dnumber\", \"Dlocation\")\n)\n/*\nColumns in dept_locations and all categories for low cardinality columns :\nDnumber : 1, 4, 5\nDlocation : Stafford, Sugarland, Bellaire, Houston\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/*\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n*/\n/*\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n*/\n \nCREATE TABLE \"Detention\" (\n\tdetention_id INTEGER, \n\tdetention_type_code VARCHAR(10) NOT NULL, \n\tteacher_id INTEGER, \n\tdatetime_detention_start DATETIME, \n\tdatetime_detention_end DATETIME, \n\tdetention_summary VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (detention_id), \n\tFOREIGN KEY(teacher_id) REFERENCES \"Teachers\" (teacher_id), \n\tFOREIGN KEY(detention_type_code) REFERENCES \"Ref_Detention_Type\" (detention_type_code)\n)\n/*\nColumns in Detention and 3 examples in each column for high cardinality columns :\ndetention_id : 1, 13, 11\ndatetime_detention_start : 2017-09-05 00:38:25, 2018-01-29 20:43:45, 2017-08-25 12:00:46\ndatetime_detention_end : 2018-03-13 20:37:39, 2018-03-22 20:15:47, 2018-03-05 03:31:24\n*/\n/*\nColumns in Detention and all categories for low cardinality columns :\ndetention_type_code : LUNCH, AFTER, BREAK \nteacher_id : 11, 10, 5, 7, 8, 14, 3, 12, 15\ndetention_summary : None\nother_details : None\n*/\n \nCREATE TABLE \"Functional_Areas\" (\n\tfunctional_area_code VARCHAR(15), \n\tparent_functional_area_code VARCHAR(15), \n\tfunctional_area_description VARCHAR(80) NOT NULL, \n\tPRIMARY KEY (functional_area_code)\n)\n/*\nColumns in Functional_Areas and all categories for low cardinality columns :\nfunctional_area_code : 1, 8, 9\nparent_functional_area_code : 8\nfunctional_area_description : Keep blank, Signature, Acknowledgement\n*/\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER, \n\tdate_of_registration DATETIME, \n\tdate_of_latest_logon DATETIME, \n\tlogin_name VARCHAR(40), \n\tpassword VARCHAR(10), \n\tpersonal_name VARCHAR(40), \n\tmiddle_name VARCHAR(40), \n\tfamily_name VARCHAR(40), \n\tPRIMARY KEY (student_id)\n)\n/*\nColumns in Students and 3 examples in each column for high cardinality columns :\nstudent_id : 1, 13, 11\ndate_of_registration : 2015-10-11 03:23:27, 2016-03-25 18:58:58, 2015-04-27 10:25:31\ndate_of_latest_logon : 2017-11-25 03:14:32, 2017-12-11 14:29:41, 2017-09-15 08:10:04\nlogin_name : eichmann.lera, myron.bergnaum, kiarra28\npassword : 5bc0d35e75, aedd08a3b9, 2e05a1e6a3\npersonal_name : Mariela, Eliza, Alicia\nmiddle_name : Casimir, Camilla, Marianne\nfamily_name : Ziemann, Zieme, Hartmann\n*/\n\n \nCREATE TABLE \"Video_Games\" (\n\t\"GameID\" INTEGER, \n\t\"GName\" VARCHAR(40), \n\t\"GType\" VARCHAR(40), \n\tPRIMARY KEY (\"GameID\")\n)\n/*\nColumns in Video_Games and all categories for low cardinality columns :\nGameID : 1, 2, 5, 4, 6, 3\nGName : Call of Destiny, Grand Term Assignment, The Vanishing of Eric Calder, Europe is the Universe, Works of Widenius, RNG Stone\nGType : Role-playing game, Collectible card game, Frist-person shooter, Walking Simulator, Grand strategy, Massively multiplayer online game\n*/\n \nCREATE TABLE dept_locations (\n\t\"Dnumber\" INTEGER, \n\t\"Dlocation\" TEXT, \n\tPRIMARY KEY (\"Dnumber\", \"Dlocation\")\n)\n/*\nColumns in dept_locations and all categories for low cardinality columns :\nDnumber : 1, 4, 5\nDlocation : Stafford, Sugarland, Bellaire, Houston\n*/\n \nCREATE TABLE tweets (\n\tid BIGINT NOT NULL, \n\tuid INTEGER NOT NULL, \n\ttext CHAR(140) NOT NULL, \n\tcreatedate DATETIME DEFAULT CURRENT_TIMESTAMP, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(uid) REFERENCES user_profiles (uid)\n)\n/*\nColumns in tweets and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 9\nuid : 1, 5, 4, 6, 3\ntext : Today I have went shopping at Laffayette., Let’s celebrate women, fight for equality and support each other, not just today, but everyday!, Oh, I only have a few fans., I love my new boyfriend., I feel tired and don't want to write SQLs., My company is hiring interns., Hello I'm Tony Stark., I had a pretty rough time during the last couple of weeks\ncreatedate : 2018-03-09 20:00:14, 2018-03-12 02:30:30, 2018-03-09 20:01:02\n*/\n \nCREATE TABLE \"Ref_Budget_Codes\" (\n\t\"Budget_Type_Code\" CHAR(15) NOT NULL, \n\t\"Budget_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Budget_Type_Code\")\n)\n/*\nColumns in Ref_Budget_Codes and all categories for low cardinality columns :\nBudget_Type_Code : GV, SF, ORG\nBudget_Type_Description : Self founded, Government, Organisation\n*/\n \nCREATE TABLE \"Claims\" (\n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Date_Claim_Made\" DATE, \n\t\"Date_Claim_Settled\" DATE, \n\t\"Amount_Claimed\" INTEGER, \n\t\"Amount_Settled\" INTEGER, \n\tPRIMARY KEY (\"Claim_ID\"), \n\tFOREIGN KEY(\"Policy_ID\") REFERENCES \"Customer_Policies\" (\"Policy_ID\")\n)\n/*\nColumns in Claims and 3 examples in each column for high cardinality columns :\nClaim_ID : 843, 143, 563\nDate_Claim_Made : 2018-11-08, 2016-08-12, 2016-08-02\nDate_Claim_Settled : 2017-12-20, 2018-02-20, 2017-09-04\nAmount_Claimed : 49743, 70088, 46479\nAmount_Settled : 1372, 1652, 1528\n*/\n/*\nColumns in Claims and all categories for low cardinality columns :\nPolicy_ID : 858, 143, 141, 744, 473, 352, 119, 738, 552\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Student_Tests_Taken\" (\n\tregistration_id INTEGER NOT NULL, \n\tdate_test_taken DATETIME NOT NULL, \n\ttest_result VARCHAR(255), \n\tFOREIGN KEY(registration_id) REFERENCES \"Student_Course_Enrolment\" (registration_id)\n)\n/*\nColumns in Student_Tests_Taken and 3 examples in each column for high cardinality columns :\ndate_test_taken : 2018-03-19 02:04:26, 2018-03-25 03:27:16, 2018-03-25 21:41:51\n*/\n/*\nColumns in Student_Tests_Taken and all categories for low cardinality columns :\nregistration_id : 16, 2, 5, 7, 17, 4, 12, 19, 10, 9\ntest_result : Fail, Pass\n*/\n \nCREATE TABLE operate_company (\n\tid INTEGER, \n\tname TEXT, \n\t\"Type\" TEXT, \n\t\"Principal_activities\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in operate_company and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : China Pacific Laundry Services, Cathay Pacific Holidays, CLS Catering Services Limited\n*/\n/*\nColumns in operate_company and all categories for low cardinality columns :\nType : Joint Venture, Subsidiary, Corporate\nPrincipal_activities : Laundry, Airline, Catering services, Travel agency, Ground handling, Cargo, Cargo airline\nIncorporated_in : Canada, China, Hong Kong, Vietnam, Taiwan\nGroup_Equity_Shareholding : 45.0, 60.0, 30.0, 49.0, 100.0, 40.0, 18.77\n*/\n \nCREATE TABLE \"Student_Addresses\" (\n\tstudent_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_address_from DATETIME NOT NULL, \n\tdate_address_to DATETIME, \n\tmonthly_rental DECIMAL(19, 4), \n\tother_details VARCHAR(255), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/*\nColumns in Student_Addresses and 3 examples in each column for high cardinality columns :\nstudent_id : 1, 13, 11\naddress_id : 1, 16, 13\ndate_address_from : 2017-09-23 05:16:17, 2017-03-29 18:22:55, 2017-09-10 19:41:10\ndate_address_to : 2018-03-05 21:12:37, 2018-03-07 04:29:28, 2018-03-14 09:12:05\nmonthly_rental : 1032.8717, 1007.2597, 756.6745\n*/\n/*\nColumns in Student_Addresses and all categories for low cardinality columns :\nother_details : house, apartment\n*/\n \nCREATE TABLE performance (\n\t\"Performance_ID\" REAL, \n\t\"Date\" TEXT, \n\t\"Host\" TEXT, \n\t\"Location\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Performance_ID\")\n)\n/*\nColumns in performance and all categories for low cardinality columns :\nPerformance_ID : 3.0, 1.0, 2.0, 6.0, 4.0, 5.0\nDate : February 7, February 4, February 2, February 5, February 10, February 11\nHost : Ottawa Senators, New York Rangers, Pittsburgh Penguins, Atlanta Thrashers, Montreal Canadiens, Boston Bruins\nLocation : Madison Square Garden, Scotiabank Place, Verizon Center, TD Garden, Bell Centre\nAttendance : 2173, 1878, 1877, 1820, 1982, 165\n*/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/*\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n*/\n" }, { "role": "user", "content": "What are the titles, years, and directors of all movies, ordered by budget in millions?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: title, YEAR, director, budget_million.\nThe SQL query I'll be generating is:\nSELECT title , YEAR , director FROM movie ORDER BY budget_million" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Ref_Calendar\" (\n\t\"Calendar_Date\" DATETIME NOT NULL, \n\t\"Day_Number\" INTEGER, \n\tPRIMARY KEY (\"Calendar_Date\")\n)\n/*\nColumns in Ref_Calendar and 3 examples in each column for high cardinality columns :\nCalendar_Date : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1972-03-31 09:47:22\n*/\n/*\nColumns in Ref_Calendar and all categories for low cardinality columns :\nDay_Number : 1, 2, 5, 7, 8, 3, 9\n*/\n \nCREATE TABLE representative (\n\t\"Representative_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"State\" TEXT, \n\t\"Party\" TEXT, \n\t\"Lifespan\" TEXT, \n\tPRIMARY KEY (\"Representative_ID\")\n)\n/*\nColumns in representative and all categories for low cardinality columns :\nRepresentative_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dan Quayle, James M. Quigley, Al Quie, James L. Quinn, Jack Quinn, John Quayle, Jimmy Quillen\nState : Pennsylvania, Tennessee, New York, Indiana, Minnesota\nParty : Democratic, Republican\nLifespan : 1947–, 1923–, 1916–2003, 1868–1930, 1951–, 1875–1960, 1918–\n*/\n \nCREATE TABLE \"Ref_Document_Types\" (\n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Type_Name\" VARCHAR(255) NOT NULL, \n\t\"Document_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Document_Type_Code\")\n)\n/*\nColumns in Ref_Document_Types and all categories for low cardinality columns :\nDocument_Type_Code : RV, BK, PR, CV\nDocument_Type_Name : Book, Review, CV, Paper\nDocument_Type_Description : \n*/\n \nCREATE TABLE follows (\n\tf1 INTEGER NOT NULL, \n\tf2 INTEGER NOT NULL, \n\tPRIMARY KEY (f1, f2), \n\tFOREIGN KEY(f2) REFERENCES user_profiles (uid), \n\tFOREIGN KEY(f1) REFERENCES user_profiles (uid)\n)\n/*\nColumns in follows and all categories for low cardinality columns :\nf1 : 1, 2, 5, 7, 3\nf2 : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE chip_model (\n\t\"Model_name\" TEXT, \n\t\"Launch_year\" REAL, \n\t\"RAM_MiB\" REAL, \n\t\"ROM_MiB\" REAL, \n\t\"Slots\" TEXT, \n\t\"WiFi\" TEXT, \n\t\"Bluetooth\" TEXT, \n\tPRIMARY KEY (\"Model_name\")\n)\n/*\nColumns in chip_model and 3 examples in each column for high cardinality columns :\nModel_name : X30 mid-range, X50 Advanced, X51 mid-range\n*/\n/*\nColumns in chip_model and all categories for low cardinality columns :\nLaunch_year : 2002.0, 2005.0, 2004.0, 2003.0\nRAM_MiB : 32.0, 64.0\nROM_MiB : 48.0, 256.0, 128.0, 32.0, 64.0\nSlots : 1CFII,1SD, 1SD\nWiFi : 802.11b, No\nBluetooth : 1.2, Yes, No, 1.1\n*/\n \nCREATE TABLE \"Skills_Required_To_Fix\" (\n\tpart_fault_id INTEGER NOT NULL, \n\tskill_id INTEGER NOT NULL, \n\tFOREIGN KEY(skill_id) REFERENCES \"Skills\" (skill_id), \n\tFOREIGN KEY(part_fault_id) REFERENCES \"Part_Faults\" (part_fault_id)\n)\n/*\nColumns in Skills_Required_To_Fix and 3 examples in each column for high cardinality columns :\npart_fault_id : 1, 13, 10\n*/\n/*\nColumns in Skills_Required_To_Fix and all categories for low cardinality columns :\nskill_id : 1, 2, 3\n*/\n \nCREATE TABLE aircraft (\n\t\"Aircraft_ID\" INTEGER, \n\t\"Order_Year\" INTEGER, \n\t\"Manufacturer\" TEXT, \n\t\"Model\" TEXT, \n\t\"Fleet_Series\" TEXT, \n\t\"Powertrain\" TEXT, \n\t\"Fuel_Propulsion\" TEXT, \n\tPRIMARY KEY (\"Aircraft_ID\")\n)\n/*\nColumns in aircraft and all categories for low cardinality columns :\nAircraft_ID : 1, 2, 5, 7, 4, 6, 3\nOrder_Year : 1992, 2000, 1996, 2002, 1998, 2011, 2010\nManufacturer : NFI, Gillig\nModel : C40LFR, GE40LFR, Phantom (High Floor), Advantage (Low Floor)\nFleet_Series : 310-329 (20), 465-467 (3), 468-473 (6), 444-464 (21), 474-481 (8), 300-309 (10), 482-492 (11)\nPowertrain : Cummins Westport ISL-G Allison WB-400R, Cummins ISC Allison WB-400R, DD S50 Allison WB-400R, Cummins ISL Allison WB-400R, Ford Triton V10 ISE-Thundervolt TB40-HG, DD S50EGR Allison WB-400R\nFuel_Propulsion : Hybrid, Diesel, CNG\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE phone_market (\n\t\"Market_ID\" INTEGER, \n\t\"Phone_ID\" TEXT, \n\t\"Num_of_stock\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\", \"Phone_ID\"), \n\tFOREIGN KEY(\"Phone_ID\") REFERENCES phone (\"Phone_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/*\nColumns in phone_market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 6\nPhone_ID : 1, 2, 4, 3\nNum_of_stock : 2232, 874, 4324, 682, 908, 1632\n*/\n \nCREATE TABLE \"Enrolled_in\" (\n\t\"StuID\" INTEGER, \n\t\"CID\" VARCHAR(7), \n\t\"Grade\" VARCHAR(2), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"CID\") REFERENCES \"Course\" (\"CID\"), \n\tFOREIGN KEY(\"Grade\") REFERENCES \"Gradeconversion\" (lettergrade)\n)\n/*\nColumns in Enrolled_in and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nCID : 550.413, 520.345, 600.437\nGrade : D+, B-, C\n*/\n\n \nCREATE TABLE body_builder (\n\t\"Body_Builder_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Snatch\" REAL, \n\t\"Clean_Jerk\" REAL, \n\t\"Total\" REAL, \n\tPRIMARY KEY (\"Body_Builder_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in body_builder and all categories for low cardinality columns :\nBody_Builder_ID : 1, 2, 5, 4, 3\nPeople_ID : 1, 2, 5, 6, 3\nSnatch : 142.5, 137.5, 130.0, 140.0\nClean_Jerk : 162.5, 177.5, 175.0\nTotal : 315.0, 317.5, 312.5, 292.5\n*/\n \nCREATE TABLE musical (\n\t\"Musical_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Award\" TEXT, \n\t\"Category\" TEXT, \n\t\"Nominee\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Musical_ID\")\n)\n/*\nColumns in musical and all categories for low cardinality columns :\nMusical_ID : 1, 2, 5, 7, 4, 6, 3\nName : The Book of Mormon, Les Misérables, Rent, Chicago, West Side Story, The Phantom of the Opera, Wicked\nYear : 1986\nAward : Drama Desk Award, Tony Award\nCategory : Outstanding Director of a Musical, Best Direction of a Musical, Best Choreography, Best Performance by a Leading Actor in a Musical, Outstanding Choreography, Best Book of a Musical, Outstanding Actor in a Musical\nNominee : Bob Fosse, Cleavant Derricks\nResult : Nominated, Won\n*/\n \nCREATE TABLE list (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Grade\" INTEGER, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/*\nColumns in list and 3 examples in each column for high cardinality columns :\nLastName : HOUTCHENS, GELL, FLACHS\nFirstName : RAY, EMILE, PATRINA\nClassroom : 109, 110, 106\n*/\n/*\nColumns in list and all categories for low cardinality columns :\nGrade : 1, 2, 5, 4, 6, 3, 0\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE \"Ref_Document_Types\" (\n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Document_Type_Name\" VARCHAR(255) NOT NULL, \n\t\"Document_Type_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Document_Type_Code\")\n)\n/*\nColumns in Ref_Document_Types and all categories for low cardinality columns :\nDocument_Type_Code : FM, PT, PP, CV, BK\nDocument_Type_Name : Book, Presentation, Paper, Film, CV\nDocument_Type_Description : fun, excellent, very good, good\n*/\n \nCREATE TABLE review (\n\ta_id INTEGER NOT NULL, \n\tu_id INTEGER NOT NULL, \n\ti_id INTEGER NOT NULL, \n\trating INTEGER DEFAULT NULL, \n\trank INTEGER DEFAULT NULL, \n\tPRIMARY KEY (a_id), \n\tFOREIGN KEY(i_id) REFERENCES item (i_id), \n\tFOREIGN KEY(u_id) REFERENCES useracct (u_id)\n)\n/*\nColumns in review and all categories for low cardinality columns :\na_id : 1, 2, 5, 7, 4, 6, 3\nu_id : 1, 2\ni_id : 1, 5, 7, 4, 3\nrating : 7, 10, 5, 6\nrank : 1, 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Discount_Coupons\" (\n\tcoupon_id INTEGER, \n\tdate_issued DATETIME, \n\tcoupon_amount DECIMAL(19, 4), \n\tPRIMARY KEY (coupon_id)\n)\n/*\nColumns in Discount_Coupons and 3 examples in each column for high cardinality columns :\ncoupon_id : 1, 13, 11\ndate_issued : 2018-02-24 01:40:52, 2017-09-06 01:33:27, 2018-02-10 21:18:23\ncoupon_amount : 245.3600, 501.3000, 508.4400\n*/\n\n \nCREATE TABLE \"Financial_Transactions\" (\n\ttransaction_id INTEGER NOT NULL, \n\tprevious_transaction_id INTEGER, \n\taccount_id INTEGER NOT NULL, \n\tcard_id INTEGER NOT NULL, \n\ttransaction_type VARCHAR(15) NOT NULL, \n\ttransaction_date DATETIME, \n\ttransaction_amount DOUBLE, \n\ttransaction_comment VARCHAR(255), \n\tother_transaction_details VARCHAR(255), \n\tFOREIGN KEY(account_id) REFERENCES \"Accounts\" (account_id), \n\tFOREIGN KEY(card_id) REFERENCES \"Customers_Cards\" (card_id)\n)\n/*\nColumns in Financial_Transactions and 3 examples in each column for high cardinality columns :\ntransaction_id : 1, 13, 11\nprevious_transaction_id : 925, 947, 986\naccount_id : 1, 13, 11\ntransaction_date : 2018-03-24 10:39:09, 2018-03-23 21:59:28, 2018-03-24 05:45:57\ntransaction_amount : 486.56, 1336.21, 945.43\n*/\n/*\nColumns in Financial_Transactions and all categories for low cardinality columns :\ncard_id : 1, 11, 2, 5, 7, 4, 6, 12, 3, 9\ntransaction_type : Refund, Payment\ntransaction_comment : None\nother_transaction_details : None\n*/\n" }, { "role": "user", "content": "How many movie directors are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: director.\nThe SQL query I'll be generating is:\nSELECT COUNT (DISTINCT director) FROM movie" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE works_on (\n\t\"Essn\" INTEGER, \n\t\"Pno\" INTEGER, \n\t\"Hours\" REAL, \n\tPRIMARY KEY (\"Essn\", \"Pno\")\n)\n/*\nColumns in works_on and all categories for low cardinality columns :\nEssn : 987987987, 333445555, 453453453, 666884444, 123456789, 987654321, 888665555, 999887777\nPno : 1, 20, 2, 30, 3, 10\nHours : 30.0, 15.0, 32.5, 10.0, 7.5, 40.0, 35.0, None, 20.0, 5.0\n*/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"White\" REAL, \n\t\"Black\" REAL, \n\t\"Amerindian\" REAL, \n\t\"Asian\" REAL, \n\t\"Multiracial\" REAL, \n\t\"Hispanic\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"County_ID\") REFERENCES county_public_safety (\"County_ID\")\n)\n/*\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 16, 13\nName : Aguadilla, Barranquitas, Bayamón\nWhite : 70.7, 78.3, 93.1\nBlack : 4.1, 22.8, 7.2\nMultiracial : 10.7, 12.1, 11.7\n*/\n/*\nColumns in city and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nAmerindian : 0.4, 0.6, 1.0, 0.3, 0.2, 0.9\nAsian : 0.1, 0.4, 0.3, 0.0, 0.2\nHispanic : 99.6, 98.5, 99.1, 99.5, 99.2, 99.4, 98.6, 98.9, 99.0, 99.3\n*/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/*\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n*/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/*\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n*/\n \nCREATE TABLE screen_mode (\n\t\"Graphics_mode\" REAL, \n\t\"Char_cells\" TEXT, \n\t\"Pixels\" TEXT, \n\t\"Hardware_colours\" REAL, \n\tused_kb REAL, \n\tmap TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"Graphics_mode\")\n)\n/*\nColumns in screen_mode and all categories for low cardinality columns :\nGraphics_mode : 3.0, 1.0, 0.0, 2.0, 6.0, 4.0, 5.0\nChar_cells : 40 × 32, 20 × 32, 80 × 25, 40 × 25, 80 × 32\nPixels : 320 × 200, 640 × 200, 320 × 256, 640 × 256, 160 × 256\nHardware_colours : 8.0, 2.0, 4.0\nused_kb : 8.0, 10.0, 16.0, 20.0\nmap : 4000–7FFF, 3000–7FFF, 5800–7FFF, 6000–7FFF\nType : Text, Graphics\n*/\n \nCREATE TABLE \"Office_locations\" (\n\tbuilding_id INTEGER, \n\tcompany_id INTEGER, \n\tmove_in_year INTEGER, \n\tPRIMARY KEY (building_id, company_id), \n\tFOREIGN KEY(building_id) REFERENCES buildings (id), \n\tFOREIGN KEY(company_id) REFERENCES \"Companies\" (id)\n)\n/*\nColumns in Office_locations and 3 examples in each column for high cardinality columns :\nbuilding_id : 1, 11, 2\nmove_in_year : 2023, 2020, 2022\n*/\n/*\nColumns in Office_locations and all categories for low cardinality columns :\ncompany_id : 1, 11, 2, 5, 19, 7, 4, 3, 10, 9\n*/\n \nCREATE TABLE tweets (\n\tid BIGINT NOT NULL, \n\tuid INTEGER NOT NULL, \n\ttext CHAR(140) NOT NULL, \n\tcreatedate DATETIME DEFAULT CURRENT_TIMESTAMP, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(uid) REFERENCES user_profiles (uid)\n)\n/*\nColumns in tweets and all categories for low cardinality columns :\nid : 1, 2, 5, 7, 8, 4, 6, 9\nuid : 1, 5, 4, 6, 3\ntext : Today I have went shopping at Laffayette., Let’s celebrate women, fight for equality and support each other, not just today, but everyday!, Oh, I only have a few fans., I love my new boyfriend., I feel tired and don't want to write SQLs., My company is hiring interns., Hello I'm Tony Stark., I had a pretty rough time during the last couple of weeks\ncreatedate : 2018-03-09 20:00:14, 2018-03-12 02:30:30, 2018-03-09 20:01:02\n*/\n \nCREATE TABLE \"Detention\" (\n\tdetention_id INTEGER, \n\tdetention_type_code VARCHAR(10) NOT NULL, \n\tteacher_id INTEGER, \n\tdatetime_detention_start DATETIME, \n\tdatetime_detention_end DATETIME, \n\tdetention_summary VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (detention_id), \n\tFOREIGN KEY(teacher_id) REFERENCES \"Teachers\" (teacher_id), \n\tFOREIGN KEY(detention_type_code) REFERENCES \"Ref_Detention_Type\" (detention_type_code)\n)\n/*\nColumns in Detention and 3 examples in each column for high cardinality columns :\ndetention_id : 1, 13, 11\ndatetime_detention_start : 2017-09-05 00:38:25, 2018-01-29 20:43:45, 2017-08-25 12:00:46\ndatetime_detention_end : 2018-03-13 20:37:39, 2018-03-22 20:15:47, 2018-03-05 03:31:24\n*/\n/*\nColumns in Detention and all categories for low cardinality columns :\ndetention_type_code : LUNCH, AFTER, BREAK \nteacher_id : 11, 10, 5, 7, 8, 14, 3, 12, 15\ndetention_summary : None\nother_details : None\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n*/\n/*\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n*/\n \nCREATE TABLE injury_accident (\n\tgame_id INTEGER, \n\tid INTEGER, \n\t\"Player\" TEXT, \n\t\"Injury\" TEXT, \n\t\"Number_of_matches\" TEXT, \n\t\"Source\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(game_id) REFERENCES game (id)\n)\n/*\nColumns in injury_accident and 3 examples in each column for high cardinality columns :\ngame_id : 1, 11, 2\nid : 1, 13, 11\nPlayer : Dejan Stanković, Thiago Motta (2), Iván Córdoba\nInjury : Sustained a biceps femoris strain in his left leg, First-degree strain left hamstring muscles, Sustained posterior thigh strains in his left leg\n*/\n/*\nColumns in injury_accident and all categories for low cardinality columns :\nNumber_of_matches : 1, 4 (6), 2, 7 (17), 1 (2), 4, 12, 3, 10\nSource : inter.it\n*/\n \nCREATE TABLE mountain (\n\t\"Mountain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (\"Mountain_ID\")\n)\n/*\nColumns in mountain and all categories for low cardinality columns :\nMountain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Ngaliema / Mt Stanley (Margherita Pk), Mount Kenya (Lenana), Kibo (Uhuru Pk), Ngaliema / Mt Stanley (Savoia Pk), Mount Kenya (Batian), Duwoni / Mt Speke (Vittorio Emanuele Pk), Mawenzi (Hans Meyer Pk)\nHeight : 5109.0, 5199.0, 5895.0, 4890.0, 4985.0, 4977.0, 5148.0\nProminence : 720.0, 850.0, 3951.0, 3825.0, 130.0, 5885.0, 110.0\nRange : Kilimanjaro, Mount Kenya, Rwenzori\nCountry : DR Congo Uganda, Uganda, Tanzania, Kenya\n*/\n \nCREATE TABLE \"Rent_Arrears\" (\n\tcouncil_tax_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (council_tax_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/*\nColumns in Rent_Arrears and all categories for low cardinality columns :\ncouncil_tax_id : 1, 7, 2, 6\ncmi_cross_ref_id : 8, 2, 59, 100\n*/\n \nCREATE TABLE endowment (\n\tendowment_id INTEGER, \n\t\"School_id\" INTEGER, \n\tdonator_name TEXT, \n\tamount REAL, \n\tPRIMARY KEY (endowment_id), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/*\nColumns in endowment and 3 examples in each column for high cardinality columns :\nendowment_id : 1, 11, 2\ndonator_name : Santo Domingo Este, Duarte, San Cristóbal\namount : 9.05, 8.82, 8.85\n*/\n/*\nColumns in endowment and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\n*/\n" }, { "role": "user", "content": "Count the number of different directors." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: director.\nThe SQL query I'll be generating is:\nSELECT COUNT (DISTINCT director) FROM movie" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Acceptance\" (\n\t\"Submission_ID\" INTEGER, \n\t\"Workshop_ID\" INTEGER, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (\"Submission_ID\", \"Workshop_ID\"), \n\tFOREIGN KEY(\"Workshop_ID\") REFERENCES workshop (\"Workshop_ID\"), \n\tFOREIGN KEY(\"Submission_ID\") REFERENCES submission (\"Submission_ID\")\n)\n/*\nColumns in Acceptance and all categories for low cardinality columns :\nSubmission_ID : 1, 2, 5, 4, 3\nWorkshop_ID : 1, 2, 5, 6, 3\nResult : Accepted, Rejected\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE schedule (\n\t\"Cinema_ID\" INTEGER, \n\t\"Film_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Show_times_per_day\" INTEGER, \n\t\"Price\" FLOAT, \n\tPRIMARY KEY (\"Cinema_ID\", \"Film_ID\"), \n\tFOREIGN KEY(\"Cinema_ID\") REFERENCES cinema (\"Cinema_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\")\n)\n/*\nColumns in schedule and all categories for low cardinality columns :\nCinema_ID : 1, 2, 6, 10, 9\nFilm_ID : 1, 2, 5, 4, 3\nDate : 20 May, 2 Aug, 11 July, 21 May, 19 May, 21 Jun\nShow_times_per_day : 2, 5, 4, 3\nPrice : 9.99, 8.99, 12.99, 15.99\n*/\n \nCREATE TABLE departments (\n\t\"DEPARTMENT_ID\" DECIMAL(4, 0) DEFAULT '0' NOT NULL, \n\t\"DEPARTMENT_NAME\" VARCHAR(30) NOT NULL, \n\t\"MANAGER_ID\" DECIMAL(6, 0) DEFAULT NULL, \n\t\"LOCATION_ID\" DECIMAL(4, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"DEPARTMENT_ID\")\n)\n/*\nColumns in departments and 3 examples in each column for high cardinality columns :\nDEPARTMENT_ID : 170, 160, 120\nDEPARTMENT_NAME : Shipping, Purchasing, Corporate Tax\nMANAGER_ID : 114, 201, 108\n*/\n/*\nColumns in departments and all categories for low cardinality columns :\nLOCATION_ID : 1700, 1800, 2700, 2400, 2500, 1500, 1400\n*/\n \nCREATE TABLE \"Has_amenity\" (\n\tdormid INTEGER, \n\tamenid INTEGER, \n\tFOREIGN KEY(amenid) REFERENCES \"Dorm_amenity\" (amenid), \n\tFOREIGN KEY(dormid) REFERENCES \"Dorm\" (dormid)\n)\n/*\nColumns in Has_amenity and 3 examples in each column for high cardinality columns :\namenid : 902, 955, 930\n*/\n/*\nColumns in Has_amenity and all categories for low cardinality columns :\ndormid : 109, 110, 100, 117, 140, 104, 160\n*/\n \nCREATE TABLE region (\n\t\"Region_ID\" INTEGER, \n\t\"Region_name\" TEXT, \n\t\"Date\" TEXT, \n\t\"Label\" TEXT, \n\t\"Format\" TEXT, \n\t\"Catalogue\" TEXT, \n\tPRIMARY KEY (\"Region_ID\")\n)\n/*\nColumns in region and all categories for low cardinality columns :\nRegion_ID : 1, 2, 5, 4, 3\nRegion_name : Japan, United Kingdom, United States\nDate : 1 July 2002, 16 July 2002, 3 July 2002\nLabel : Toshiba-EMI, Astralwerks, Parlophone\nFormat : CD digipak, 2× LP, CD\nCatalogue : ASW 40362, ASW 40522, 539 9821, TOCP-66045, 540 3622\n*/\n \nCREATE TABLE \"Stay\" (\n\t\"StayID\" INTEGER NOT NULL, \n\t\"Patient\" INTEGER NOT NULL, \n\t\"Room\" INTEGER NOT NULL, \n\t\"StayStart\" DATETIME NOT NULL, \n\t\"StayEnd\" DATETIME NOT NULL, \n\tPRIMARY KEY (\"StayID\"), \n\tCONSTRAINT \"fk_Stay_Patient_SSN\" FOREIGN KEY(\"Patient\") REFERENCES \"Patient\" (\"SSN\"), \n\tCONSTRAINT \"fk_Stay_Room_Number\" FOREIGN KEY(\"Room\") REFERENCES \"Room\" (\"RoomNumber\")\n)\n/*\nColumns in Stay and all categories for low cardinality columns :\nStayID : 3216, 3215, 3217\nPatient : 100000001, 100000004, 100000003\nRoom : 123, 111, 112\nStayStart : 2008-05-01 00:00:00, 2008-05-02 00:00:00, 2008-05-03 00:00:00\nStayEnd : 2008-05-14 00:00:00, 2008-05-04 00:00:00, 2008-05-03 00:00:00\n*/\n \nCREATE TABLE \"Skills\" (\n\tskill_id INTEGER, \n\tskill_code VARCHAR(20), \n\tskill_description VARCHAR(255), \n\tPRIMARY KEY (skill_id)\n)\n/*\nColumns in Skills and all categories for low cardinality columns :\nskill_id : 1, 2, 3\nskill_code : MECH, TV, ELEC\nskill_description : Mechanical, Electrical, TV, Video\n*/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/*\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n*/\n \nCREATE TABLE exhibition (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Theme\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\t\"Ticket_Price\" REAL, \n\tPRIMARY KEY (\"Exhibition_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in exhibition and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 6, 3\nYear : 2004, 2009, 2005, 2008, 2006, 2007\nTheme : Christmas Tree, Santa Claus and Rudolph the Red-Nosed Reindeer, Summer, Christmas stocking, Spring, Santa Claus\nArtist_ID : 1, 2, 4, 6, 3\nTicket_Price : 19.95, 9.95, 29.95, 14.95, 16.95\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Transactions_Lots\" (\n\ttransaction_id INTEGER NOT NULL, \n\tlot_id INTEGER NOT NULL, \n\tFOREIGN KEY(transaction_id) REFERENCES \"Transactions\" (transaction_id), \n\tFOREIGN KEY(lot_id) REFERENCES \"Lots\" (lot_id)\n)\n/*\nColumns in Transactions_Lots and all categories for low cardinality columns :\ntransaction_id : 1, 2, 15, 7, 6, 12, 3, 14, 10\nlot_id : 1, 11, 15, 8, 4, 14, 3, 10, 9\n*/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/*\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n*/\n \nCREATE TABLE \"Documents_to_be_Destroyed\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Destruction_Authorised_by_Employee_ID\" INTEGER, \n\t\"Destroyed_by_Employee_ID\" INTEGER, \n\t\"Planned_Destruction_Date\" DATETIME, \n\t\"Actual_Destruction_Date\" DATETIME, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Destroyed_by_Employee_ID\") REFERENCES \"Employees\" (\"Employee_ID\"), \n\tFOREIGN KEY(\"Destruction_Authorised_by_Employee_ID\") REFERENCES \"Employees\" (\"Employee_ID\"), \n\tFOREIGN KEY(\"Planned_Destruction_Date\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Actual_Destruction_Date\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"All_Documents\" (\"Document_ID\")\n)\n/*\nColumns in Documents_to_be_Destroyed and 3 examples in each column for high cardinality columns :\nDocument_ID : 120, 11, 25\n*/\n/*\nColumns in Documents_to_be_Destroyed and all categories for low cardinality columns :\nDestruction_Authorised_by_Employee_ID : 38, 156, 183, 55, 30, 123\nDestroyed_by_Employee_ID : 173, 38, 156, 55, 138, 99, 136\nPlanned_Destruction_Date : 2009-08-18 03:29:08, 1972-03-31 09:47:22, 1987-11-05 06:11:22, 2017-01-06 23:17:22, 1976-06-15 03:40:06, 1988-02-01 14:41:52, 2010-11-26 19:22:50\nActual_Destruction_Date : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1988-02-01 14:41:52, 1995-01-01 03:52:11, 1985-05-13 12:19:43\nOther_Details : None\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Products\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Price\" DECIMAL NOT NULL, \n\t\"Manufacturer\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Manufacturer\") REFERENCES \"Manufacturers\" (\"Code\")\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nCode : 1, 11, 2\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nName : Printer, Floppy disk, Memory, Monitor, Toner cartridge, CD drive, DVD burner, Hard drive, ZIP drive, DVD drive\nPrice : 150.0000000000, 120.0000000000, 90.0000000000, 5.0000000000, 270.0000000000, 180.0000000000, 66.0000000000, 240.0000000000\nManufacturer : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status_code VARCHAR(10) NOT NULL, \n\torder_date DATETIME NOT NULL, \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\norder_date : 2018-03-16 22:42:46, 2018-01-31 17:49:18, 2018-02-16 19:42:39\n*/\n/*\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 1, 13, 11, 10, 7, 8, 4, 6, 12, 15\norder_status_code : Pending, Completed, PartFilled, Cancelled, New\n*/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/*\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n*/\n" }, { "role": "user", "content": "What is the title and director for the movie with highest worldwide gross in the year 2000 or before?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: title, director, gross_worldwide.\nThe SQL query I'll be generating is:\nSELECT title , director FROM movie WHERE YEAR <= 2000 ORDER BY gross_worldwide DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n*/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\taddress_content VARCHAR(80), \n\tcity VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tother_address_details VARCHAR(255), \n\tPRIMARY KEY (address_id)\n)\n/*\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\naddress_content : 92865 Margaretta Streets Suite 467, 78614 Maybell Alley Suite 057, 9443 Boyle Route Suite 857\ncity : South Meghanview, South Bellaland, Gleasonmouth\nzip_postcode : 721, 255, 416\nstate_province_county : RhodeIsland, Arizona, Mississippi\n*/\n/*\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\nother_address_details : None\n*/\n \nCREATE TABLE airlines (\n\talid INTEGER, \n\tname TEXT, \n\tiata VARCHAR(2), \n\ticao VARCHAR(3), \n\tcallsign TEXT, \n\tcountry TEXT, \n\tactive VARCHAR(2), \n\tPRIMARY KEY (alid)\n)\n/*\nColumns in airlines and 3 examples in each column for high cardinality columns :\nalid : 87, 56, 65\nname : Arab Agricultural Aviation Company, Avion Taxi, Amadeus Global Travel Distribution\niata : , U3, JP\nicao : , ADP, UVS\ncallsign : , ALGOMA, SECUREX\ncountry : , Afghanistan, Gabon\n*/\n/*\nColumns in airlines and all categories for low cardinality columns :\nactive : Y, N\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/*\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Sex\" TEXT, \n\t\"Name\" TEXT, \n\t\"Date_of_Birth\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nSex : F, M\nName : Vincent Montméat, Frantz Granvorka, Loïc De Kergret, Philippe Barça-Cysique, Guillaume Samica, Stéphane Antiga, Dominique Daquin, Laurent Capet, Hubert Henno\nDate_of_Birth : 20.08.1970, 10.03.1976, 05.05.1972, 28.09.1981, 22.04.1977, 01.09.1977, 10.11.1972, 06.10.1976, 03.02.1976\nHeight : 196.0, 195.0, 197.0, 188.0, 193.0, 200.0, 202.0, 194.0\nWeight : 89.0, 82.0, 85.0, 88.0, 90.0, 92.0, 83.0, 94.0\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE files (\n\tf_id NUMERIC(10) NOT NULL, \n\tartist_name TEXT(50), \n\tfile_size TEXT(20), \n\tduration TEXT(20), \n\tformats TEXT(20), \n\tPRIMARY KEY (f_id), \n\tFOREIGN KEY(artist_name) REFERENCES artist (artist_name) ON DELETE CASCADE\n)\n/*\nColumns in files and all categories for low cardinality columns :\nf_id : 1.0000000000, 5.0000000000, 6.0000000000, 3.0000000000, 2.0000000000, 4.0000000000\nartist_name : Prity, Michel, Topu, Shrikanta, Enrique, Farida\nfile_size : 4.58 MB, 5.10 MB, 4.10 MB, 3.69 MB, 3.78 MB, 4.12 MB\nduration : 4:30, 5:23, 2:56, 4:34, 3:45, 4:12\nformats : mp3, mp4\n*/\n \nCREATE TABLE \"Document_Locations\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Location_Code\" CHAR(15) NOT NULL, \n\t\"Date_in_Location_From\" DATETIME NOT NULL, \n\t\"Date_in_Locaton_To\" DATETIME, \n\tPRIMARY KEY (\"Document_ID\", \"Location_Code\", \"Date_in_Location_From\"), \n\tFOREIGN KEY(\"Location_Code\") REFERENCES \"Ref_Locations\" (\"Location_Code\"), \n\tFOREIGN KEY(\"Date_in_Location_From\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Date_in_Locaton_To\") REFERENCES \"Ref_Calendar\" (\"Calendar_Date\"), \n\tFOREIGN KEY(\"Document_ID\") REFERENCES \"All_Documents\" (\"Document_ID\")\n)\n/*\nColumns in Document_Locations and all categories for low cardinality columns :\nDocument_ID : 230, 11, 252, 170, 7, 119, 260, 111, 166, 81\nLocation_Code : b, e, c, n, x\nDate_in_Location_From : 2009-08-18 03:29:08, 1972-03-31 09:47:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1985-05-13 12:19:43, 2008-06-08 12:45:38\nDate_in_Locaton_To : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1987-11-05 06:11:22, 1986-10-14 17:53:39, 2017-01-06 23:17:22, 1976-06-15 03:40:06, 1997-03-10 15:24:00, 2010-11-26 19:22:50, 1995-01-01 03:52:11, 2008-06-08 12:45:38\n*/\n \nCREATE TABLE \"Video_Games\" (\n\t\"GameID\" INTEGER, \n\t\"GName\" VARCHAR(40), \n\t\"GType\" VARCHAR(40), \n\tPRIMARY KEY (\"GameID\")\n)\n/*\nColumns in Video_Games and all categories for low cardinality columns :\nGameID : 1, 2, 5, 4, 6, 3\nGName : Call of Destiny, Grand Term Assignment, The Vanishing of Eric Calder, Europe is the Universe, Works of Widenius, RNG Stone\nGType : Role-playing game, Collectible card game, Frist-person shooter, Walking Simulator, Grand strategy, Massively multiplayer online game\n*/\n \nCREATE TABLE player (\n\t\"Player_ID\" INTEGER, \n\t\"Player\" TEXT, \n\t\"Team\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Position\" TEXT, \n\t\"School_ID\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 17, 21, 9\nPlayer : Buster Posey, Brett Wallace, Timothy Beckham\nTeam : Los Angeles Dodgers, San Diego Padres, Toronto Blue Jays\n*/\n/*\nColumns in player and all categories for low cardinality columns :\nAge : 16, 18, 17, 14, 15\nPosition : Second baseman, Outfielder, Left-handed pitcher, Shortstop, Third baseman, First baseman, First Baseman, Catcher, Right-handed pitcher\nSchool_ID : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE \"Documents\" (\n\tdocument_code VARCHAR(15), \n\tdocument_structure_code VARCHAR(15) NOT NULL, \n\tdocument_type_code VARCHAR(15) NOT NULL, \n\taccess_count INTEGER, \n\tdocument_name VARCHAR(80), \n\tPRIMARY KEY (document_code), \n\tFOREIGN KEY(document_structure_code) REFERENCES \"Document_Structures\" (document_structure_code)\n)\n/*\nColumns in Documents and 3 examples in each column for high cardinality columns :\ndocument_code : 510, 714, 217\naccess_count : 8208, 3289, 2294\ndocument_name : Learning English, Summer Sails, Learning Database\n*/\n/*\nColumns in Documents and all categories for low cardinality columns :\ndocument_structure_code : 1, 5, 8, 6, 9\ndocument_type_code : Book, Advertisement, CV, Paper\n*/\n \nCREATE TABLE university (\n\t\"School_ID\" INTEGER, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Affiliation\" TEXT, \n\t\"Enrollment\" REAL, \n\t\"Nickname\" TEXT, \n\t\"Primary_conference\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in university and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 3\nSchool : University of Rhode Island, Rutgers University, University of Delaware, Stony Brook University, Lebanon Valley College\nLocation : New Brunswick, NJ, Annville, PA, Newark, DE, Stony Brook, NY, Kingston, RI\nFounded : 1866.0, 1892.0, 1957.0, 1766.0, 1743.0\nAffiliation : Private/Methodist, Public\nEnrollment : 2100.0, 19067.0, 23997.0, 19095.0, 56868.0\nNickname : Seawolves, Flying Dutchmen, Rams, Scarlet Knights, Fightin' Blue Hens\nPrimary_conference : Colonial Athletic Association ( D-I ), Atlantic 10 Conference ( D-I ), American Athletic Conference ( D-I ), America East Conference ( D-I ), MAC Commonwealth Conference ( D-III )\n*/\n \nCREATE TABLE \"Ref_Locations\" (\n\t\"Location_Code\" CHAR(15) NOT NULL, \n\t\"Location_Name\" VARCHAR(255) NOT NULL, \n\t\"Location_Description\" VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (\"Location_Code\")\n)\n/*\nColumns in Ref_Locations and all categories for low cardinality columns :\nLocation_Code : b, e, n, x, c\nLocation_Name : Canada, Xiamen, Nanjing, Brazil, Edinburgh\nLocation_Description : \n*/\n \nCREATE TABLE architect (\n\tid TEXT, \n\tname TEXT, \n\tnationality TEXT, \n\tgender TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in architect and all categories for low cardinality columns :\nid : 1, 2, 5, 4, 3\nname : Frank Lloyd Wright, Frank Gehry, Mies Van Der Rohe, Le Corbusier, Zaha Hadid\nnationality : American, Swiss, French, German, American, Canadian, Iraqi, British\ngender : female, male\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/*\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n*/\n \nCREATE TABLE country (\n\t\"Country_id\" INTEGER, \n\t\"Country_name\" TEXT, \n\t\"Capital\" TEXT, \n\t\"Official_native_language\" TEXT, \n\tPRIMARY KEY (\"Country_id\")\n)\n/*\nColumns in country and all categories for low cardinality columns :\nCountry_id : 1, 2, 5, 4, 6, 3\nCountry_name : Isle of Man, Iran, United States, Indonesia, Iraq, Ireland\nCapital : Jakarta, Baghdad, Dublin, Tehran, Douglas, Washington\nOfficial_native_language : Arabic ( Arabic script ) Kurdish, English Manx, Persian ( Arabic script ), English, Bahasa Indonesia, Irish English\n*/\n" }, { "role": "user", "content": "Return the title and director of the movie released in the year 2000 or earlier that had the highest worldwide gross." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: title, director, gross_worldwide.\nThe SQL query I'll be generating is:\nSELECT title , director FROM movie WHERE YEAR <= 2000 ORDER BY gross_worldwide DESC LIMIT 1" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"School\" (\n\t\"School_id\" TEXT, \n\t\"School_name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Mascot\" TEXT, \n\t\"Enrollment\" INTEGER, \n\t\"IHSAA_Class\" TEXT, \n\t\"IHSAA_Football_Class\" TEXT, \n\t\"County\" TEXT, \n\tPRIMARY KEY (\"School_id\")\n)\n/*\nColumns in School and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\nSchool_name : New Prairie 1, Triton, LaVille, Glenn, Culver Community, Jimtown, Knox Community, Bremen\nLocation : Bourbon, Walkerton, Lakeville, Knox, Culver, New Carlisle, Elkhart, Bremen\nMascot : Lancers, Cougars, Cavaliers, Trojans, Redskins, Falcons, Lions, Jimmies\nEnrollment : 601, 605, 287, 495, 620, 379, 852, 316\nIHSAA_Class : AA, A, AAA\nIHSAA_Football_Class : AA, A, AAA, AAAA\nCounty : 20 Elkhart, 50 Marshall, 75 Starke, 71 St. Joseph, 46 LaPorte 71 St. Joseph\n*/\n \nCREATE TABLE competition_result (\n\t\"Competition_ID\" INTEGER, \n\t\"Club_ID_1\" INTEGER, \n\t\"Club_ID_2\" INTEGER, \n\t\"Score\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\", \"Club_ID_1\", \"Club_ID_2\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES competition (\"Competition_ID\"), \n\tFOREIGN KEY(\"Club_ID_2\") REFERENCES club (\"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID_1\") REFERENCES club (\"Club_ID\")\n)\n/*\nColumns in competition_result and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 6, 10\nClub_ID_1 : 1, 4, 3\nClub_ID_2 : 2, 4, 6\nScore : 11:10, 10:11, 10:3, 13:10, 12:9, 25:2\n*/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Counties_Represented\" TEXT, \n\t\"District\" INTEGER, \n\t\"Delegate\" TEXT, \n\t\"Party\" INTEGER, \n\t\"First_Elected\" REAL, \n\t\"Committee\" TEXT, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"District\") REFERENCES county (\"County_Id\"), \n\tFOREIGN KEY(\"Party\") REFERENCES party (\"Party_ID\")\n)\n/*\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 7, 8, 4, 6, 3\nCounties_Represented : 09.1 9A, 13, 12.1 12A, 12.2 12B\nDistrict : 1, 2, 4, 3\nDelegate : Miller, Warren E. Warren E. Miller, Bobo, Elizabeth Elizabeth Bobo, Pendergrass, Shane E. Shane Pendergrass, Bates, Gail H. Gail H. Bates, DeBoy, Steven J. Sr. Steven J. DeBoy, Sr., Guzzone, Guy Guy Guzzone, Turner, Frank S. Frank S. Turner, Malone, James E. Jr. James E. Malone, Jr.\nParty : 1, 2, 7, 4, 3\nFirst_Elected : 2002.0, 2006.0, 1994.0, 2003.0\nCommittee : Environmental Matters, Economic Matters, Ways and Means, Environmental Matters (Vice-Chair), Health and Government Operations, Appropriations\n*/\n \nCREATE TABLE list (\n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Grade\" INTEGER, \n\t\"Classroom\" INTEGER, \n\tPRIMARY KEY (\"LastName\", \"FirstName\")\n)\n/*\nColumns in list and 3 examples in each column for high cardinality columns :\nLastName : HOUTCHENS, GELL, FLACHS\nFirstName : RAY, EMILE, PATRINA\nClassroom : 109, 110, 106\n*/\n/*\nColumns in list and all categories for low cardinality columns :\nGrade : 1, 2, 5, 4, 6, 3, 0\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tparent_product_id INTEGER, \n\tproduct_category_code VARCHAR(20) NOT NULL, \n\tdate_product_first_available DATETIME, \n\tdate_product_discontinued DATETIME, \n\tproduct_name VARCHAR(80), \n\tproduct_description VARCHAR(255), \n\tproduct_price DECIMAL(19, 4), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_id : 120, 119, 117, 118\nparent_product_id : 8, 4, 9, 3\nproduct_category_code : Food, Book, Hardware\ndate_product_first_available : 1988-09-29 17:54:50, 1998-06-20 15:04:11, 1994-12-18 15:13:19, 1974-06-25 12:26:47\ndate_product_discontinued : 1987-12-20 13:46:16, 1997-07-02 18:26:16, 1980-06-26 10:40:19, 1991-08-20 05:22:31\nproduct_name : Chocolate, The Great Gatsby, Mouse, Keyboard\nproduct_description : Designed for games, Handmade chocolate, American novel, Blue tooth mouse\nproduct_price : 23.3500, 2.8800, 109.9900, 35.0000\n*/\n \nCREATE TABLE \"Assets_in_Events\" (\n\t\"Asset_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Asset_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/*\nColumns in Assets_in_Events and all categories for low cardinality columns :\nAsset_ID : 1, 2, 3\nEvent_ID : 2, 5, 8, 4, 14, 12, 10, 9\n*/\n \nCREATE TABLE \"Employees\" (\n\temployee_id INTEGER NOT NULL, \n\trole_code CHAR(15) NOT NULL, \n\temployee_name VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (employee_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Roles\" (role_code)\n)\n/*\nColumns in Employees and all categories for low cardinality columns :\nemployee_id : 1, 2, 5, 7, 8, 3\nrole_code : MG, ED, PR, PT\nemployee_name : Koby, Erling, Kenyon, Haley, Jordyn, Clemens\nother_details : f, b, h, v, u\n*/\n \nCREATE TABLE \"Research_Outcomes\" (\n\toutcome_code VARCHAR(10), \n\toutcome_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (outcome_code)\n)\n/*\nColumns in Research_Outcomes and all categories for low cardinality columns :\noutcome_code : Patent, Paper\noutcome_description : Published Research Paper, Research Patent\n*/\n \nCREATE TABLE \"Department_Stores\" (\n\tdept_store_id INTEGER, \n\tdept_store_chain_id INTEGER, \n\tstore_name VARCHAR(80), \n\tstore_address VARCHAR(255), \n\tstore_phone VARCHAR(80), \n\tstore_email VARCHAR(80), \n\tPRIMARY KEY (dept_store_id), \n\tFOREIGN KEY(dept_store_chain_id) REFERENCES \"Department_Store_Chain\" (dept_store_chain_id)\n)\n/*\nColumns in Department_Stores and 3 examples in each column for high cardinality columns :\ndept_store_id : 1, 13, 11\nstore_address : 7081 Shanna Cape\nWest Zacheryshire, NC 17408, 082 Purdy Expressway\nO'Connellshire, IL 31732, 49708 Marcella Valleys Suite 181\nNinamouth, WA 86667\nstore_phone : 1-859-843-1957, 1-764-126-7567x0795, 670-466-6367\nstore_email : larissa10@example.org, katlynn62@example.com, ihamill@example.org\n*/\n/*\nColumns in Department_Stores and all categories for low cardinality columns :\ndept_store_chain_id : 1, 2, 4, 3\nstore_name : store_name\n*/\n \nCREATE TABLE \"Grants\" (\n\tgrant_id INTEGER, \n\torganisation_id INTEGER NOT NULL, \n\tgrant_amount DECIMAL(19, 4) DEFAULT 0 NOT NULL, \n\tgrant_start_date DATETIME NOT NULL, \n\tgrant_end_date DATETIME NOT NULL, \n\tother_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (grant_id), \n\tFOREIGN KEY(organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/*\nColumns in Grants and 3 examples in each column for high cardinality columns :\ngrant_id : 1, 13, 11\ngrant_amount : 24.7000, 1.9848, 0.0000\ngrant_start_date : 2016-11-20 00:18:51, 2011-05-10 22:44:08, 2015-12-14 13:02:11\ngrant_end_date : 2004-10-24 09:09:39, 1982-03-11 15:27:55, 2001-05-22 21:02:43\nother_details : aliquam, occaecati, qui\n*/\n/*\nColumns in Grants and all categories for low cardinality columns :\norganisation_id : 11, 2, 5, 7, 8, 14, 3, 12, 10, 9\n*/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Num_of_employees\" INTEGER, \n\t\"Num_of_shops\" REAL, \n\t\"Ranking\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/*\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nDistrict : New Brunswick, Quebec, Ontario, Nova Scotia, Alberta, British Columbia\nNum_of_employees : 1978, 1958, 1968, 1965, 1966\nNum_of_shops : 49.0, 10.0, 40.0, 32.0, 54.0\nRanking : 1, 5, 8, 4, 21, 3\n*/\n \nCREATE TABLE \"Sales\" (\n\tsales_transaction_id INTEGER, \n\tsales_details VARCHAR(255), \n\tPRIMARY KEY (sales_transaction_id), \n\tFOREIGN KEY(sales_transaction_id) REFERENCES \"Transactions\" (transaction_id)\n)\n/*\nColumns in Sales and 3 examples in each column for high cardinality columns :\nsales_transaction_id : 1, 13, 11\n*/\n/*\nColumns in Sales and all categories for low cardinality columns :\nsales_details : t, f, s, e, y, n, x, p, o, a\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE repair_assignment (\n\ttechnician_id INTEGER, \n\t\"repair_ID\" INTEGER, \n\t\"Machine_ID\" INTEGER, \n\tPRIMARY KEY (technician_id, \"repair_ID\", \"Machine_ID\"), \n\tFOREIGN KEY(\"Machine_ID\") REFERENCES machine (\"Machine_ID\"), \n\tFOREIGN KEY(\"repair_ID\") REFERENCES repair (\"repair_ID\"), \n\tFOREIGN KEY(technician_id) REFERENCES technician (technician_id)\n)\n/*\nColumns in repair_assignment and all categories for low cardinality columns :\ntechnician_id : 1, 2, 5, 7, 3\nrepair_ID : 1, 2, 5, 8, 4, 3\nMachine_ID : 1, 2, 7, 4, 6, 3\n*/\n \nCREATE TABLE instructor (\n\t\"ID\" VARCHAR(5), \n\tname VARCHAR(20) NOT NULL, \n\tdept_name VARCHAR(20), \n\tsalary NUMERIC(8, 2), \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(dept_name) REFERENCES department (dept_name), \n\tCHECK (salary > 29000)\n)\n/*\nColumns in instructor and 3 examples in each column for high cardinality columns :\nID : 99052, 6569, 79081\nname : McKinnon, Sarkar, Vicentino\ndept_name : Marketing, Comp. Sci., Statistics\nsalary : 43770.36, 35023.18, 117836.50\n*/\n\n" }, { "role": "user", "content": "Show all director names who have a movie in both year 1999 and 2000." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: director.\nThe SQL query I'll be generating is:\nSELECT director FROM movie WHERE YEAR = 2000 INTERSECT SELECT director FROM movie WHERE YEAR = 1999" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Parties\" (\n\t\"Party_ID\" INTEGER NOT NULL, \n\t\"Party_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Party_ID\")\n)\n/*\nColumns in Parties and all categories for low cardinality columns :\nParty_ID : 5, 7, 8, 4, 6, 3, 9\nParty_Details : European Alliance for Freedom, Alliance of Liberals and Democrats for Europe, European Free Alliance, European Christian Political Movement, EUDemocrats, European People's Party, Movement for a Europe of Nations and Freedom\n*/\n \nCREATE TABLE \"CHECKING\" (\n\tcustid BIGINT NOT NULL, \n\tbalance FLOAT NOT NULL, \n\tPRIMARY KEY (custid), \n\tFOREIGN KEY(custid) REFERENCES \"ACCOUNTS\" (custid)\n)\n/*\nColumns in CHECKING and all categories for low cardinality columns :\ncustid : 1, 2, 5, 7, 4, 6, 3\nbalance : 3000.0, 10000.0, 2000.0, 7.0, 7000.0, 77.0\n*/\n \nCREATE TABLE competition_result (\n\t\"Competition_ID\" INTEGER, \n\t\"Club_ID_1\" INTEGER, \n\t\"Club_ID_2\" INTEGER, \n\t\"Score\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\", \"Club_ID_1\", \"Club_ID_2\"), \n\tFOREIGN KEY(\"Competition_ID\") REFERENCES competition (\"Competition_ID\"), \n\tFOREIGN KEY(\"Club_ID_2\") REFERENCES club (\"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID_1\") REFERENCES club (\"Club_ID\")\n)\n/*\nColumns in competition_result and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 6, 10\nClub_ID_1 : 1, 4, 3\nClub_ID_2 : 2, 4, 6\nScore : 11:10, 10:11, 10:3, 13:10, 12:9, 25:2\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" TEXT, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Role\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and 3 examples in each column for high cardinality columns :\nMember_ID : 1, 11, 2\n*/\n/*\nColumns in member and all categories for low cardinality columns :\nName : Andrew Moten, Juan Espil, Luis González, Corey Allen, John Eubanks, Charlie Burke, Joseph Bunn, Héctor Campana, Joshua Pittman, Wilfredo Ruiz\nNationality : United States, Uruguay, Argentina\nRole : Cello, Viola, Bass, Prime Violin, Violin\n*/\n \nCREATE TABLE follows (\n\tf1 INTEGER NOT NULL, \n\tf2 INTEGER NOT NULL, \n\tPRIMARY KEY (f1, f2), \n\tFOREIGN KEY(f2) REFERENCES user_profiles (uid), \n\tFOREIGN KEY(f1) REFERENCES user_profiles (uid)\n)\n/*\nColumns in follows and all categories for low cardinality columns :\nf1 : 1, 2, 5, 7, 3\nf2 : 1, 2, 5, 4, 6, 3\n*/\n \nCREATE TABLE gymnast (\n\t\"Gymnast_ID\" INTEGER, \n\t\"Floor_Exercise_Points\" REAL, \n\t\"Pommel_Horse_Points\" REAL, \n\t\"Rings_Points\" REAL, \n\t\"Vault_Points\" REAL, \n\t\"Parallel_Bars_Points\" REAL, \n\t\"Horizontal_Bar_Points\" REAL, \n\t\"Total_Points\" REAL, \n\tPRIMARY KEY (\"Gymnast_ID\"), \n\tFOREIGN KEY(\"Gymnast_ID\") REFERENCES people (\"People_ID\")\n)\n/*\nColumns in gymnast and all categories for low cardinality columns :\nGymnast_ID : 1, 2, 7, 8, 4, 6, 10\nFloor_Exercise_Points : 9.762, 9.65, 9.412, 9.725, 9.7, 9.687, 8.987\nPommel_Horse_Points : 9.625, 9.325, 9.675, 9.525, 9.737, 9.75, 9.712\nRings_Points : 9.512, 9.625, 9.3, 9.712, 9.475, 9.75, 9.487\nVault_Points : 9.537, 9.762, 9.65, 9.637, 9.55, 9.575\nParallel_Bars_Points : 9.625, 9.787, 9.762, 9.562, 9.587, 9.725, 9.5\nHorizontal_Bar_Points : 9.55, 9.725, 9.412, 9.737, 9.5, 9.75\nTotal_Points : 57.398, 57.924, 57.649, 57.374, 57.436, 58.061, 57.424\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/*\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n*/\n \nCREATE TABLE \"Enrolled_in\" (\n\t\"StuID\" INTEGER, \n\t\"CID\" VARCHAR(7), \n\t\"Grade\" VARCHAR(2), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"CID\") REFERENCES \"Course\" (\"CID\"), \n\tFOREIGN KEY(\"Grade\") REFERENCES \"Gradeconversion\" (lettergrade)\n)\n/*\nColumns in Enrolled_in and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nCID : 550.413, 520.345, 600.437\nGrade : D+, B-, C\n*/\n\n \nCREATE TABLE match_result (\n\t\"Rank\" INTEGER, \n\t\"Club_ID\" INTEGER, \n\t\"Gold\" INTEGER, \n\t\"Big_Silver\" INTEGER, \n\t\"Small_Silver\" INTEGER, \n\t\"Bronze\" INTEGER, \n\t\"Points\" INTEGER, \n\tPRIMARY KEY (\"Rank\", \"Club_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/*\nColumns in match_result and all categories for low cardinality columns :\nRank : 1, 2, 5, 4, 6, 3\nClub_ID : 1, 2, 5, 4, 6, 3\nGold : 13, 20, 5, 7, 6, 12\nBig_Silver : 11, 7, 6, 12, 14, 9\nSmall_Silver : 16, 4, 6, 10, 9\nBronze : 7, 8, 6, 10, 9\nPoints : 89, 102, 84, 66, 139, 168\n*/\n \nCREATE TABLE \"College\" (\n\t\"cName\" VARCHAR(20) NOT NULL, \n\tstate VARCHAR(2), \n\tenr NUMERIC(5, 0), \n\tPRIMARY KEY (\"cName\")\n)\n/*\nColumns in College and all categories for low cardinality columns :\ncName : FSU, OU, ASU, LSU\nstate : AZ, FL, LA, OK\nenr : 22000, 19000, 12000, 18000\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"CLASS\" (\n\t\"CLASS_CODE\" VARCHAR(5), \n\t\"CRS_CODE\" VARCHAR(10), \n\t\"CLASS_SECTION\" VARCHAR(2), \n\t\"CLASS_TIME\" VARCHAR(20), \n\t\"CLASS_ROOM\" VARCHAR(8), \n\t\"PROF_NUM\" INTEGER, \n\tPRIMARY KEY (\"CLASS_CODE\"), \n\tFOREIGN KEY(\"CRS_CODE\") REFERENCES \"COURSE\" (\"CRS_CODE\"), \n\tFOREIGN KEY(\"PROF_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\")\n)\n/*\nColumns in CLASS and 3 examples in each column for high cardinality columns :\nCLASS_CODE : 10013, 10024, 10016\n*/\n/*\nColumns in CLASS and all categories for low cardinality columns :\nCRS_CODE : ACCT-212, QM-362, QM-261, CIS-420, CIS-220, ACCT-211\nCLASS_SECTION : 1, 2, 3\nCLASS_TIME : TTh 2:30-3:45 p.m., MWF 10:00-10:50 a.m., MWF 9:00-9:50 a.m., MWF 8:00-8:50 a.m., W 6:00-8:40 p.m., Th 6:00-8:40 p.m., TTh 1:00-2:15 p.m., MWF 11:00-11:50 a.m.\nCLASS_ROOM : KLR209, KLR211, BUS252, BUS311, KLR200, BUS200\nPROF_NUM : 114, 342, 301, 228, 105, 162\n*/\n \nCREATE TABLE train_station (\n\t\"Train_ID\" INTEGER, \n\t\"Station_ID\" INTEGER, \n\tPRIMARY KEY (\"Train_ID\", \"Station_ID\"), \n\tFOREIGN KEY(\"Train_ID\") REFERENCES train (\"Train_ID\"), \n\tFOREIGN KEY(\"Station_ID\") REFERENCES station (\"Station_ID\")\n)\n/*\nColumns in train_station and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\n*/\n/*\nColumns in train_station and all categories for low cardinality columns :\nStation_ID : 1, 2, 5, 8, 3, 10, 9\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n*/\n \nCREATE TABLE \"Projects\" (\n\t\"Code\" CHAR(4), \n\t\"Name\" CHAR(50) NOT NULL, \n\t\"Hours\" INTEGER, \n\tPRIMARY KEY (\"Code\")\n)\n/*\nColumns in Projects and 3 examples in each column for high cardinality columns :\nCode : Bte2, AeH6, Ast3\nName : Aerodynamics of Air Hockey, Winds: Studying Bernoullis Principle, Aerodynamics and Gas Mileage\nHours : 321, 189, 89\n*/\n\n \nCREATE TABLE \"Staff\" (\n\tstaff_id INTEGER, \n\tgender VARCHAR(1), \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (staff_id)\n)\n/*\nColumns in Staff and all categories for low cardinality columns :\nstaff_id : 120, 114, 116, 117, 115, 119, 118\ngender : 1, 0\nfirst_name : Dorian, Austin, Bradly, Ward, Dagmar, Mikel, Lucie\nlast_name : Zieme, Hahn, Oberbrunner, Lynch, Erdman, Boehm, Lowe\nemail_address : ohintz@example.org, brett99@example.net, glen.borer@example.com, reichel.armani@example.org, wrau@example.com, marcelle.ritchie@example.com, richard.gutkowski@example.com\nphone_number : 345-656-5571, 1-132-839-9409x288, 751-262-8424x575, (379)551-0838x146, 142-311-6503x206, (383)553-1035x20399, 155-811-6153\n*/\n" }, { "role": "user", "content": "Which directors had a movie both in the year 1999 and 2000?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: director.\nThe SQL query I'll be generating is:\nSELECT director FROM movie WHERE YEAR = 2000 INTERSECT SELECT director FROM movie WHERE YEAR = 1999" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Project_Outcomes\" (\n\tproject_id INTEGER NOT NULL, \n\toutcome_code VARCHAR(10) NOT NULL, \n\toutcome_details VARCHAR(255), \n\tFOREIGN KEY(outcome_code) REFERENCES \"Research_Outcomes\" (outcome_code), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/*\nColumns in Project_Outcomes and all categories for low cardinality columns :\nproject_id : 13, 11, 5, 7, 4, 6, 14, 3, 12, 9\noutcome_code : Patent, Paper\noutcome_details : None\n*/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Num_of_employees\" INTEGER, \n\t\"Num_of_shops\" REAL, \n\t\"Ranking\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/*\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nDistrict : New Brunswick, Quebec, Ontario, Nova Scotia, Alberta, British Columbia\nNum_of_employees : 1978, 1958, 1968, 1965, 1966\nNum_of_shops : 49.0, 10.0, 40.0, 32.0, 54.0\nRanking : 1, 5, 8, 4, 21, 3\n*/\n \nCREATE TABLE \"Policies\" (\n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Policy_Type_Code\" CHAR(15) NOT NULL, \n\t\"Start_Date\" DATETIME, \n\t\"End_Date\" DATETIME, \n\tPRIMARY KEY (\"Policy_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Customers\" (\"Customer_ID\")\n)\n/*\nColumns in Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 703, 151, 768\nStart_Date : 2018-03-13 12:30:19, 2018-02-10 08:56:30, 2018-07-21 10:36:53\nEnd_Date : 2017-10-07 08:29:25, 2018-01-19 22:45:33, 2018-03-07 13:52:47\n*/\n/*\nColumns in Policies and all categories for low cardinality columns :\nCustomer_ID : 588, 858, 808, 334, 252, 994, 380, 430, 857, 435\nPolicy_Type_Code : Uniformed, Normal, Jurisdiction, Deputy\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Payments\" (\n\t\"Payment_ID\" INTEGER NOT NULL, \n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Payment_Method_Code\" VARCHAR(255), \n\t\"Date_Payment_Made\" DATE, \n\t\"Amount_Payment\" INTEGER, \n\tPRIMARY KEY (\"Payment_ID\"), \n\tFOREIGN KEY(\"Settlement_ID\") REFERENCES \"Settlements\" (\"Settlement_ID\")\n)\n/*\nColumns in Payments and 3 examples in each column for high cardinality columns :\nPayment_ID : 754, 739, 542\nDate_Payment_Made : 2017-06-24, 2017-08-06, 2017-12-16\nAmount_Payment : 423154, 155654, 71246\n*/\n/*\nColumns in Payments and all categories for low cardinality columns :\nSettlement_ID : 527, 476, 564, 983, 682, 648, 597, 512, 516\nPayment_Method_Code : Visa, Discover Card, American Express, MasterCard\n*/\n \nCREATE TABLE \"Project_Staff\" (\n\tstaff_id DOUBLE, \n\tproject_id INTEGER NOT NULL, \n\trole_code VARCHAR(10) NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Staff_Roles\" (role_code), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/*\nColumns in Project_Staff and 3 examples in each column for high cardinality columns :\nstaff_id : 3.0, 5137097.0, 45.0\ndate_from : 1981-10-04 22:44:50, 2000-08-28 11:49:17, 2005-01-13 11:49:48\ndate_to : 1988-03-04 19:30:05, 2004-07-28 03:11:47, 1971-07-19 22:49:05\n*/\n/*\nColumns in Project_Staff and all categories for low cardinality columns :\nproject_id : 1, 11, 2, 5, 7, 8, 4, 3, 15, 9\nrole_code : researcher, leader\nother_details : None\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/*\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE train (\n\t\"Train_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Time\" TEXT, \n\t\"Service\" TEXT, \n\tPRIMARY KEY (\"Train_ID\")\n)\n/*\nColumns in train and 3 examples in each column for high cardinality columns :\nTrain_ID : 1, 11, 2\nTime : 10:38, 16:59, 11:15\n*/\n/*\nColumns in train and all categories for low cardinality columns :\nName : Parasuram Express, Island Express, Ananthapuri Express, Madurai Fast Passenger, Quilon Fast Passenger, Jayanthi Janatha Express, Guruvayur Express\nService : Daily\n*/\n \nCREATE TABLE endowment (\n\tendowment_id INTEGER, \n\t\"School_id\" INTEGER, \n\tdonator_name TEXT, \n\tamount REAL, \n\tPRIMARY KEY (endowment_id), \n\tFOREIGN KEY(\"School_id\") REFERENCES \"School\" (\"School_id\")\n)\n/*\nColumns in endowment and 3 examples in each column for high cardinality columns :\nendowment_id : 1, 11, 2\ndonator_name : Santo Domingo Este, Duarte, San Cristóbal\namount : 9.05, 8.82, 8.85\n*/\n/*\nColumns in endowment and all categories for low cardinality columns :\nSchool_id : 1, 2, 5, 7, 8, 4, 6, 3\n*/\n \nCREATE TABLE \"Movie\" (\n\t\"mID\" INTEGER, \n\ttitle TEXT, \n\tyear INTEGER, \n\tdirector TEXT, \n\tPRIMARY KEY (\"mID\")\n)\n/*\nColumns in Movie and all categories for low cardinality columns :\nmID : 108, 106, 103, 102, 101, 104, 107, 105\ntitle : Avatar, Raiders of the Lost Ark, Titanic, E.T., Gone with the Wind, Snow White, Star Wars, The Sound of Music\nyear : 1937, 2009, 1982, 1997, 1939, 1965, 1981, 1977\ndirector : Robert Wise, James Cameron, George Lucas, Victor Fleming, Steven Spielberg, None\n*/\n \nCREATE TABLE party (\n\t\"Party_ID\" INTEGER, \n\t\"Year\" REAL, \n\t\"Party\" TEXT, \n\t\"Governor\" TEXT, \n\t\"Lieutenant_Governor\" TEXT, \n\t\"Comptroller\" TEXT, \n\t\"Attorney_General\" TEXT, \n\t\"US_Senate\" TEXT, \n\tPRIMARY KEY (\"Party_ID\")\n)\n/*\nColumns in party and all categories for low cardinality columns :\nParty_ID : 1, 2, 5, 7, 4, 6, 3\nYear : 2002.0, 2006.0, 1998.0\nParty : Working Families, Democratic, Independence, Liberal\nGovernor : Betsy McCaughey Ross, Tom Golisano, Peter Vallone, Carl McCall, Eliot Spitzer\nLieutenant_Governor : Sandra Frankel, Mary Donohue, Dennis Mehiel, David Paterson, Jonathan Reiter\nComptroller : Carl McCall, Alan Hevesi, John Faso\nAttorney_General : Eliot Spitzer, Andrew Cuomo, Jeanine Pirro\nUS_Senate : Hillary Rodham Clinton, Charles Schumer, (no election)\n*/\n \nCREATE TABLE \"Properties\" (\n\tproperty_id INTEGER NOT NULL, \n\tproperty_type_code CHAR(15) NOT NULL, \n\tproperty_address VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (property_id)\n)\n/*\nColumns in Properties and 3 examples in each column for high cardinality columns :\nproperty_id : 120, 954, 108\nproperty_address : 5983 Fleta Throughway, 54591 Bernard Ridges Suite 864, 7713 Bode Burgs Apt. 113\n*/\n/*\nColumns in Properties and all categories for low cardinality columns :\nproperty_type_code : apartment, house, flat\nother_details : USA\n*/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\ttown_city VARCHAR(50), \n\tzip_postcode VARCHAR(20), \n\tstate_province_county VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (address_id)\n)\n/*\nColumns in Addresses and 3 examples in each column for high cardinality columns :\naddress_id : 1, 13, 11\nline_1_number_building : 90928 Garret Mall, 25518 Ortiz Centers, 3986 Bergstrom Stravenue\ntown_city : Robertsberg, East Clair, Dangelohaven\nzip_postcode : 250, 193, 021\nstate_province_county : Pennsylvania, Michigan, NewHampshire\n*/\n/*\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n*/\n \nCREATE TABLE volume (\n\t\"Volume_ID\" INTEGER, \n\t\"Volume_Issue\" TEXT, \n\t\"Issue_Date\" TEXT, \n\t\"Weeks_on_Top\" REAL, \n\t\"Song\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\tPRIMARY KEY (\"Volume_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in volume and all categories for low cardinality columns :\nVolume_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nVolume_Issue : 46:5, 46:16, 46:14-15, 45:15, 45:21-22, 45:16, 46:6-8, 45:14 §, 46:10, 46:9\nIssue_Date : 16 May - 30 May, 6 June, 27 December 1986 - 10 January, 28 February - 7 March, 13 June, 24 January, 9 May, 17 January, 11 July - 18 July, 25 July\nWeeks_on_Top : 3.0, 1.0, 2.0\nSong : Head to Toe , Always , With or Without You , Looking for a New Love, La Isla Bonita , The Way, Everybody Have Fun Tonight , Touch Me (I Want Your Body) , (I Just) Died in Your Arms , Walk Like an Egyptian \nArtist_ID : 1, 2, 5, 4, 6\n*/\n \nCREATE TABLE publication (\n\t\"Publication_ID\" INTEGER, \n\t\"Book_ID\" INTEGER, \n\t\"Publisher\" TEXT, \n\t\"Publication_Date\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Publication_ID\"), \n\tFOREIGN KEY(\"Book_ID\") REFERENCES book (\"Book_ID\")\n)\n/*\nColumns in publication and all categories for low cardinality columns :\nPublication_ID : 1, 2, 5, 7, 4, 6, 3\nBook_ID : 1, 5, 7, 4, 3, 10, 9\nPublisher : Thomson Reuters, Springer Nature, Bertelsmann, Pearson, Wiley\nPublication_Date : March 2008, October 2005, August 2008, June 2006, April 2007, March 2007\nPrice : 6000000.0, 3000000.0, 4100000.0, 2000000.0, 15000000.0\n*/\n" }, { "role": "user", "content": "Show all director names who have a movie in the year 1999 or 2000." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: director.\nThe SQL query I'll be generating is:\nSELECT director FROM movie WHERE YEAR = 1999 OR YEAR = 2000" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE gas_station (\n\t\"Station_ID\" INTEGER, \n\t\"Open_Year\" INTEGER, \n\t\"Location\" TEXT, \n\t\"Manager_Name\" TEXT, \n\t\"Vice_Manager_Name\" TEXT, \n\t\"Representative_Name\" TEXT, \n\tPRIMARY KEY (\"Station_ID\")\n)\n/*\nColumns in gas_station and 3 examples in each column for high cardinality columns :\nStation_ID : 1, 11, 2\nOpen_Year : 2004, 2009, 2005\nLocation : Channel Hill, Newport Rd, Herne Ave\n*/\n/*\nColumns in gas_station and all categories for low cardinality columns :\nManager_Name : Simon Cope Derek Marloe, BryanDenman, Luke Rowe, BrianWingrave, Bryan Taylor, Jon Rowe, Tony Bristow, Tom Whit, SimonMarloe, Colin Denman\nVice_Manager_Name : TonyBristow, Russell Brown, Russell Denman, Martin Freeman, Simon Gaywood, James Holland-Leader, James Colin , JameMarloe, Steve Parsons, Martin Garnham\nRepresentative_Name : Andrew Russell, Chris Pyatt, Tim Read, Ray Hughes, Simon Gaywood, Tony Gibb, Clive Burr, Courtney Rowe, Rob Jefferies , Dave Edwards Roger \n*/\n \nCREATE TABLE \"Inst\" (\n\t\"instID\" INTEGER, \n\tname TEXT, \n\tcountry TEXT, \n\tPRIMARY KEY (\"instID\")\n)\n/*\nColumns in Inst and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\nname : Northeastern University, INRIA, University of Oxford, Indiana University, Tohoku University, University of Pennsylvania, Portland State University, Google\ncountry : Japan, UK, USA, France\n*/\n \nCREATE TABLE ship (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Tonnage\" INTEGER, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/*\nColumns in ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Clan McTavish, Farringford, Appam, Author, Dromonby, Corbridge, Trader, Ariadne\nType : Battle ship, Cargo ship\nNationality : United States, United Kingdom\nTonnage : 3035, 3146, 7781, 3496, 3687, 5816, 3627, 3608\n*/\n \nCREATE TABLE \"Country\" (\n\tid INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Country and 3 examples in each column for high cardinality columns :\nid : 1, 19694, 7809\nname : Scotland, Italy, Spain\n*/\n\n \nCREATE TABLE film_market_estimation (\n\t\"Estimation_ID\" INTEGER, \n\t\"Low_Estimate\" REAL, \n\t\"High_Estimate\" REAL, \n\t\"Film_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Market_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\tPRIMARY KEY (\"Estimation_ID\"), \n\tFOREIGN KEY(\"Film_ID\") REFERENCES film (\"Film_ID\"), \n\tFOREIGN KEY(\"Market_ID\") REFERENCES market (\"Market_ID\")\n)\n/*\nColumns in film_market_estimation and all categories for low cardinality columns :\nEstimation_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nLow_Estimate : 80000.0, 39.0, 16.0, 3000.0, 300.0, 53.0, 960.0, 913.0, 8000.0\nHigh_Estimate : 39.0, 16.0, 1000.0, 53.0, 960.0, 913.0, 8000.0, 80400.0\nFilm_ID : 1, 2, 4, 3\nType : Mass human sacrifice, Mass suicide murder, Mass suicide\nMarket_ID : 1, 2, 3\nYear : 1978, 1945, 1973, 1994, 1995, 2000, 1997, 1487, 1944\n*/\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/*\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n*/\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status_code VARCHAR(10) NOT NULL, \n\torder_date DATETIME NOT NULL, \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\norder_date : 2018-03-16 22:42:46, 2018-01-31 17:49:18, 2018-02-16 19:42:39\n*/\n/*\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 1, 13, 11, 10, 7, 8, 4, 6, 12, 15\norder_status_code : Pending, Completed, PartFilled, Cancelled, New\n*/\n \nCREATE TABLE \"Gradeconversion\" (\n\tlettergrade VARCHAR(2), \n\tgradepoint FLOAT, \n\tPRIMARY KEY (lettergrade)\n)\n/*\nColumns in Gradeconversion and 3 examples in each column for high cardinality columns :\nlettergrade : D+, F, B-\ngradepoint : 3.7, 3.0, 2.7\n*/\n\n \nCREATE TABLE \"Grants\" (\n\tgrant_id INTEGER, \n\torganisation_id INTEGER NOT NULL, \n\tgrant_amount DECIMAL(19, 4) DEFAULT 0 NOT NULL, \n\tgrant_start_date DATETIME NOT NULL, \n\tgrant_end_date DATETIME NOT NULL, \n\tother_details VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (grant_id), \n\tFOREIGN KEY(organisation_id) REFERENCES \"Organisations\" (organisation_id)\n)\n/*\nColumns in Grants and 3 examples in each column for high cardinality columns :\ngrant_id : 1, 13, 11\ngrant_amount : 24.7000, 1.9848, 0.0000\ngrant_start_date : 2016-11-20 00:18:51, 2011-05-10 22:44:08, 2015-12-14 13:02:11\ngrant_end_date : 2004-10-24 09:09:39, 1982-03-11 15:27:55, 2001-05-22 21:02:43\nother_details : aliquam, occaecati, qui\n*/\n/*\nColumns in Grants and all categories for low cardinality columns :\norganisation_id : 11, 2, 5, 7, 8, 14, 3, 12, 10, 9\n*/\n \nCREATE TABLE routes (\n\trid INTEGER, \n\tdst_apid INTEGER, \n\tdst_ap VARCHAR(4), \n\tsrc_apid BIGINT, \n\tsrc_ap VARCHAR(4), \n\talid BIGINT, \n\tairline VARCHAR(4), \n\tcodeshare TEXT, \n\tPRIMARY KEY (rid), \n\tFOREIGN KEY(dst_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(src_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(alid) REFERENCES airlines (alid)\n)\n/*\nColumns in routes and 3 examples in each column for high cardinality columns :\nrid : 87, 56, 65\ndst_apid : 7165, 8076, 1044\ndst_ap : SYB, JKG, IKT\nsrc_apid : 8076, 1044, 2990\nsrc_ap : SYB, JKG, IKT\n*/\n/*\nColumns in routes and all categories for low cardinality columns :\nalid : 146, 8359, 470, 1338, 410, 3652, 897, 1654, 2750\nairline : 2G, 2P, 2, 2J, 2O, 2I, 2B, 2K\ncodeshare : None, Y\n*/\n \nCREATE TABLE \"Properties\" (\n\tproperty_id INTEGER NOT NULL, \n\tproperty_type_code CHAR(15) NOT NULL, \n\tproperty_address VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (property_id)\n)\n/*\nColumns in Properties and 3 examples in each column for high cardinality columns :\nproperty_id : 120, 954, 108\nproperty_address : 5983 Fleta Throughway, 54591 Bernard Ridges Suite 864, 7713 Bode Burgs Apt. 113\n*/\n/*\nColumns in Properties and all categories for low cardinality columns :\nproperty_type_code : apartment, house, flat\nother_details : USA\n*/\n \nCREATE TABLE \"Characteristics\" (\n\tcharacteristic_id INTEGER, \n\tcharacteristic_type_code VARCHAR(15) NOT NULL, \n\tcharacteristic_data_type VARCHAR(10), \n\tcharacteristic_name VARCHAR(80), \n\tother_characteristic_details VARCHAR(255), \n\tPRIMARY KEY (characteristic_id), \n\tFOREIGN KEY(characteristic_type_code) REFERENCES \"Ref_Characteristic_Types\" (characteristic_type_code)\n)\n/*\nColumns in Characteristics and 3 examples in each column for high cardinality columns :\ncharacteristic_id : 1, 13, 11\ncharacteristic_data_type : placeat, dolores, mollitia\n*/\n/*\nColumns in Characteristics and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_name : hot, error, cool, fast, warm, slow\nother_characteristic_details : None\n*/\n \nCREATE TABLE \"Ref_Calendar\" (\n\t\"Calendar_Date\" DATETIME NOT NULL, \n\t\"Day_Number\" INTEGER, \n\tPRIMARY KEY (\"Calendar_Date\")\n)\n/*\nColumns in Ref_Calendar and 3 examples in each column for high cardinality columns :\nCalendar_Date : 2009-08-18 03:29:08, 2012-07-03 09:48:46, 1972-03-31 09:47:22\n*/\n/*\nColumns in Ref_Calendar and all categories for low cardinality columns :\nDay_Number : 1, 2, 5, 7, 8, 3, 9\n*/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/*\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n*/\n \nCREATE TABLE \"Visits_Restaurant\" (\n\t\"StuID\" INTEGER, \n\t\"ResID\" INTEGER, \n\t\"Time\" TIMESTAMP, \n\t\"Spent\" FLOAT, \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\")\n)\n/*\nColumns in Visits_Restaurant and all categories for low cardinality columns :\nStuID : 1001, 1032\nResID : 1, 2\nTime : 2017-10-09 18:15:00, 2017-10-08 13:00:30\nSpent : 13.2, 6.53\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Person\" (\n\tname VARCHAR(20), \n\tage INTEGER, \n\tcity TEXT, \n\tgender TEXT, \n\tjob TEXT, \n\tPRIMARY KEY (name)\n)\n/*\nColumns in Person and all categories for low cardinality columns :\nname : Alice, Zach, Dan, Bob\nage : 26, 25, 45, 35\ncity : austin, salt lake city, chicago, new york city\ngender : female, male\njob : student, engineer, doctor\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Member_of_club\" (\n\t\"StuID\" INTEGER, \n\t\"ClubID\" INTEGER, \n\t\"Position\" VARCHAR(40), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(\"ClubID\") REFERENCES \"Club\" (\"ClubID\")\n)\n/*\nColumns in Member_of_club and all categories for low cardinality columns :\nStuID : 1008, 1001, 1010, 1007\nClubID : 1, 2, 4\nPosition : Teaching Coordinator, CTO, Vice-President, President\n*/\n" }, { "role": "user", "content": "Which directors had a movie in either 1999 or 2000?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: director.\nThe SQL query I'll be generating is:\nSELECT director FROM movie WHERE YEAR = 1999 OR YEAR = 2000" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n*/\n \nCREATE TABLE \"Ref_Incident_Type\" (\n\tincident_type_code VARCHAR(10), \n\tincident_type_description VARCHAR(80), \n\tPRIMARY KEY (incident_type_code)\n)\n/*\nColumns in Ref_Incident_Type and all categories for low cardinality columns :\nincident_type_code : VIOLENCE, DISTURB, NOISE\nincident_type_description : Noise, Violence, Disturbance\n*/\n \nCREATE TABLE \"Parties_in_Events\" (\n\t\"Party_ID\" INTEGER NOT NULL, \n\t\"Event_ID\" INTEGER NOT NULL, \n\t\"Role_Code\" CHAR(15), \n\tPRIMARY KEY (\"Party_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES \"Parties\" (\"Party_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES \"Events\" (\"Event_ID\")\n)\n/*\nColumns in Parties_in_Events and 3 examples in each column for high cardinality columns :\nEvent_ID : 1, 13, 15\n*/\n/*\nColumns in Parties_in_Events and all categories for low cardinality columns :\nParty_ID : 5, 4, 6, 3, 9\nRole_Code : Organizer, Participant\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/*\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE machine (\n\t\"Machine_ID\" INTEGER, \n\t\"Making_Year\" INTEGER, \n\t\"Class\" TEXT, \n\t\"Team\" TEXT, \n\t\"Machine_series\" TEXT, \n\tvalue_points REAL, \n\tquality_rank INTEGER, \n\tPRIMARY KEY (\"Machine_ID\")\n)\n/*\nColumns in machine and all categories for low cardinality columns :\nMachine_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nMaking_Year : 1992, 1993, 1994, 1999, 1991, 1996, 1997, 1998, 1995\nClass : 125cc\nTeam : Honda, Team Givi- Honda LCR, Givi Racing- Honda, Marlboro Pileri - Honda, Hero Sports TS- Honda\nMachine_series : RS125\nvalue_points : 238.0, 105.0, 171.0, 129.0, 57.0, 62.0, 126.0, 194.0, 65.0\nquality_rank : 1, 13, 11, 2, 5, 7, 8, 4, 3\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"Catalogs\" (\n\tcatalog_id INTEGER, \n\tcatalog_name VARCHAR(50), \n\tcatalog_publisher VARCHAR(80), \n\tdate_of_publication DATETIME, \n\tdate_of_latest_revision DATETIME, \n\tPRIMARY KEY (catalog_id)\n)\n/*\nColumns in Catalogs and all categories for low cardinality columns :\ncatalog_id : 1, 2, 5, 7, 8, 4, 6, 3\ncatalog_name : Coffee Bean, Latte, Sparkling Water, Breakfast Tea, Jam, Lemonade, Chocolate, Coco powder\ncatalog_publisher : Russel-Gislason Lemon shop, Lidl, Koepp-Rutherford handmade chocolate store, Murray Coffee shop, Grady & Kautzer\ndate_of_publication : 2012-04-13 06:37:09, 2011-07-22 04:57:19, 2013-03-15 05:09:17, 2012-11-27 19:29:22\ndate_of_latest_revision : 2017-03-30 09:15:37, 2017-10-26 01:16:51, 2017-09-26 12:10:36, 2017-12-04 06:48:13\n*/\n \nCREATE TABLE \"Activity\" (\n\tactid INTEGER, \n\tactivity_name VARCHAR(25), \n\tPRIMARY KEY (actid)\n)\n/*\nColumns in Activity and 3 examples in each column for high cardinality columns :\nactid : 771, 782, 770\nactivity_name : Proselytizing, Spelunking, Extreme Canasta\n*/\n\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_address_id INTEGER NOT NULL, \n\tcustomer_status_code VARCHAR(15) NOT NULL, \n\tdate_became_customer DATETIME, \n\tdate_of_birth DATETIME, \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tamount_outstanding DOUBLE, \n\temail_address VARCHAR(250), \n\tphone_number VARCHAR(255), \n\tcell_mobile_phone_number VARCHAR(255), \n\tPRIMARY KEY (customer_id), \n\tFOREIGN KEY(customer_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ndate_became_customer : 2016-03-18 06:14:18, 2016-05-13 07:38:23, 2017-10-05 14:15:46\ndate_of_birth : 1994-05-07 01:32:16, 1991-12-05 02:50:15, 1998-09-18 04:45:01\nfirst_name : Millie, Dianna, Carole\nlast_name : Schmeler, Tromp, Goodwin\namount_outstanding : 7093.0, 8144.0, 9447.0\nemail_address : mariela28@example.org, wehner.harold@example.com, afranecki@example.com\nphone_number : 1-618-535-9750, 218.550.1362, 753.921.0871\ncell_mobile_phone_number : 578-518-4785x612, (780)719-4206x033, (630)964-2426\n*/\n/*\nColumns in Customers and all categories for low cardinality columns :\ncustomer_address_id : 1, 13, 2, 7, 8, 12, 10, 9\ncustomer_status_code : Bad Customer, Good Customer\n*/\n \nCREATE TABLE \"Instruments\" (\n\t\"SongId\" INTEGER, \n\t\"BandmateId\" INTEGER, \n\t\"Instrument\" TEXT, \n\tPRIMARY KEY (\"SongId\", \"BandmateId\", \"Instrument\"), \n\tFOREIGN KEY(\"SongId\") REFERENCES \"Songs\" (\"SongId\"), \n\tFOREIGN KEY(\"BandmateId\") REFERENCES \"Band\" (\"Id\")\n)\n/*\nColumns in Instruments and all categories for low cardinality columns :\nSongId : \nBandmateId : \nInstrument : \n*/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n*/\n \nCREATE TABLE \"MediaType\" (\n\t\"MediaTypeId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(120) DEFAULT NULL, \n\tPRIMARY KEY (\"MediaTypeId\")\n)\n/*\nColumns in MediaType and all categories for low cardinality columns :\nMediaTypeId : 1, 2, 5, 4, 3\nName : Protected AAC audio file, Protected MPEG-4 video file, Purchased AAC audio file, AAC audio file, MPEG audio file\n*/\n \nCREATE TABLE \"Office_locations\" (\n\tbuilding_id INTEGER, \n\tcompany_id INTEGER, \n\tmove_in_year INTEGER, \n\tPRIMARY KEY (building_id, company_id), \n\tFOREIGN KEY(building_id) REFERENCES buildings (id), \n\tFOREIGN KEY(company_id) REFERENCES \"Companies\" (id)\n)\n/*\nColumns in Office_locations and 3 examples in each column for high cardinality columns :\nbuilding_id : 1, 11, 2\nmove_in_year : 2023, 2020, 2022\n*/\n/*\nColumns in Office_locations and all categories for low cardinality columns :\ncompany_id : 1, 11, 2, 5, 19, 7, 4, 3, 10, 9\n*/\n \nCREATE TABLE shop (\n\t\"Shop_ID\" INTEGER, \n\t\"Address\" TEXT, \n\t\"Num_of_staff\" TEXT, \n\t\"Score\" REAL, \n\t\"Open_Year\" TEXT, \n\tPRIMARY KEY (\"Shop_ID\")\n)\n/*\nColumns in shop and all categories for low cardinality columns :\nShop_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAddress : 414 E. 12th Street, 324 E. 11th Street, 1330 Baltimore Street, 1201 Walnut Street, 909 Main Street, 1111 Main Street, 2345 McGee Street, 1200 Main Street, 1100 Main Street, 909 Walnut Street\nNum_of_staff : 16, 13, 28, 24, 34, 23, 19, 42, 27, 425\nScore : 36.0, 30.0, 42.0, 28.0, 38.0, 40.0, 32.0\nOpen_Year : 2008, 2010, 2011, 2006\n*/\n \nCREATE TABLE \"Problem_Status_Codes\" (\n\tproblem_status_code VARCHAR(20), \n\tproblem_status_description VARCHAR(80), \n\tPRIMARY KEY (problem_status_code)\n)\n/*\nColumns in Problem_Status_Codes and all categories for low cardinality columns :\nproblem_status_code : Solved, Reported\nproblem_status_description : Solved, Reported\n*/\n \nCREATE TABLE ship (\n\t\"Ship_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Tonnage\" INTEGER, \n\tPRIMARY KEY (\"Ship_ID\")\n)\n/*\nColumns in ship and all categories for low cardinality columns :\nShip_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Clan McTavish, Farringford, Appam, Author, Dromonby, Corbridge, Trader, Ariadne\nType : Battle ship, Cargo ship\nNationality : United States, United Kingdom\nTonnage : 3035, 3146, 7781, 3496, 3687, 5816, 3627, 3608\n*/\n" }, { "role": "user", "content": "What is the average, maximum, and minimum budget for all movies before 2000." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: budget_million.\nThe SQL query I'll be generating is:\nSELECT avg(budget_million) , max(budget_million) , min(budget_million) FROM movie WHERE YEAR < 2000" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Claims_Documents\" (\n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Created_by_Staff_ID\" INTEGER, \n\t\"Created_Date\" INTEGER, \n\tPRIMARY KEY (\"Claim_ID\", \"Document_Type_Code\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claim_Headers\" (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Created_by_Staff_ID\") REFERENCES \"Staff\" (\"Staff_ID\")\n)\n/*\nColumns in Claims_Documents and all categories for low cardinality columns :\nClaim_ID : 69, 45, 90, 24, 82, 62, 39, 27, 81, 73\nDocument_Type_Code : Medical, Document, Photo\nCreated_by_Staff_ID : 427, 771, 986, 673, 687, 589, 735, 803, 718\nCreated_Date : 1, 2, 7, 8, 6, 3, 9\n*/\n \nCREATE TABLE city (\n\t\"City_ID\" INTEGER, \n\t\"City\" TEXT, \n\t\"Hanzi\" TEXT, \n\t\"Hanyu_Pinyin\" TEXT, \n\t\"Regional_Population\" INTEGER, \n\t\"GDP\" REAL, \n\tPRIMARY KEY (\"City_ID\")\n)\n/*\nColumns in city and 3 examples in each column for high cardinality columns :\nCity_ID : 1, 13, 11\nCity : Shanghai, Changzhou ( Jiangsu ), Jinhua ( Zhejiang )\nHanzi : 台州, 金华/ 金華, 上海\nHanyu_Pinyin : Shàoxīng, Tāizhōu, Hángzhōu\nRegional_Population : 8700400, 7605689, 4912200\nGDP : 1919.57, 408.02, 266.81\n*/\n\n \nCREATE TABLE \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_category VARCHAR(15) NOT NULL, \n\tproduct_name VARCHAR(80), \n\tPRIMARY KEY (product_id)\n)\n/*\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : Coffee Bean, Learning French, Four Seasons\n*/\n/*\nColumns in Products and all categories for low cardinality columns :\nproduct_category : Food, Books, Electronics, Hardware\n*/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n*/\n \nCREATE TABLE \"Characteristics\" (\n\tcharacteristic_id INTEGER, \n\tcharacteristic_type_code VARCHAR(15) NOT NULL, \n\tcharacteristic_data_type VARCHAR(10), \n\tcharacteristic_name VARCHAR(80), \n\tother_characteristic_details VARCHAR(255), \n\tPRIMARY KEY (characteristic_id), \n\tFOREIGN KEY(characteristic_type_code) REFERENCES \"Ref_Characteristic_Types\" (characteristic_type_code)\n)\n/*\nColumns in Characteristics and 3 examples in each column for high cardinality columns :\ncharacteristic_id : 1, 13, 11\ncharacteristic_data_type : placeat, dolores, mollitia\n*/\n/*\nColumns in Characteristics and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_name : hot, error, cool, fast, warm, slow\nother_characteristic_details : None\n*/\n \nCREATE TABLE \"Inst\" (\n\t\"instID\" INTEGER, \n\tname TEXT, \n\tcountry TEXT, \n\tPRIMARY KEY (\"instID\")\n)\n/*\nColumns in Inst and all categories for low cardinality columns :\ninstID : 1060, 1010, 1000, 1040, 1050, 1030, 1020, 1070\nname : Northeastern University, INRIA, University of Oxford, Indiana University, Tohoku University, University of Pennsylvania, Portland State University, Google\ncountry : Japan, UK, USA, France\n*/\n \nCREATE TABLE trust (\n\tsource_u_id INTEGER NOT NULL, \n\ttarget_u_id INTEGER NOT NULL, \n\ttrust INTEGER NOT NULL, \n\tFOREIGN KEY(target_u_id) REFERENCES useracct (u_id), \n\tFOREIGN KEY(source_u_id) REFERENCES useracct (u_id)\n)\n/*\nColumns in trust and all categories for low cardinality columns :\nsource_u_id : 1, 2, 7, 6, 3\ntarget_u_id : 2, 5, 4, 6, 3\ntrust : 1, 2, 7, 8, 4, 6, 3, 10\n*/\n \nCREATE TABLE employment (\n\t\"Company_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Year_working\" INTEGER, \n\tPRIMARY KEY (\"Company_ID\", \"People_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\"), \n\tFOREIGN KEY(\"Company_ID\") REFERENCES company (\"Company_ID\")\n)\n/*\nColumns in employment and all categories for low cardinality columns :\nCompany_ID : 13, 11, 7, 17, 15\nPeople_ID : 1, 2, 7, 4, 3\nYear_working : 1, 2, 4, 3\n*/\n \nCREATE TABLE \"SportsInfo\" (\n\t\"StuID\" INTEGER, \n\t\"SportName\" VARCHAR(32), \n\t\"HoursPerWeek\" INTEGER, \n\t\"GamesPlayed\" INTEGER, \n\t\"OnScholarship\" VARCHAR(1), \n\tFOREIGN KEY(\"StuID\") REFERENCES \"Student\" (\"StuID\")\n)\n/*\nColumns in SportsInfo and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1033, 1023\nHoursPerWeek : 1, 45, 2\nGamesPlayed : 16, 56, 20\n*/\n/*\nColumns in SportsInfo and all categories for low cardinality columns :\nSportName : Tennis, Athletics, Football, Basketball, Baseball, Swimming, Curling, Soccer, Lacrosse, Cricket\nOnScholarship : Y, N\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"AssignedTo\" (\n\t\"Scientist\" INTEGER NOT NULL, \n\t\"Project\" CHAR(4) NOT NULL, \n\tPRIMARY KEY (\"Scientist\", \"Project\"), \n\tFOREIGN KEY(\"Scientist\") REFERENCES \"Scientists\" (\"SSN\"), \n\tFOREIGN KEY(\"Project\") REFERENCES \"Projects\" (\"Code\")\n)\n/*\nColumns in AssignedTo and 3 examples in each column for high cardinality columns :\nScientist : 546523478, 332569843, 845657246\n*/\n/*\nColumns in AssignedTo and all categories for low cardinality columns :\nProject : Ast3, AeH3, AeH1, Ast1, AeH4, Ast2, Bte1, Che1\n*/\n \nCREATE TABLE broadcast_share (\n\t\"Channel_ID\" INTEGER, \n\t\"Program_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Share_in_percent\" REAL, \n\tPRIMARY KEY (\"Channel_ID\", \"Program_ID\"), \n\tFOREIGN KEY(\"Program_ID\") REFERENCES program (\"Program_ID\"), \n\tFOREIGN KEY(\"Channel_ID\") REFERENCES channel (\"Channel_ID\")\n)\n/*\nColumns in broadcast_share and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nProgram_ID : 1, 2, 4, 3\nDate : 03,May, 04,April, 02,May, 10,Jun, 11,May, 01,May, 13,May\nShare_in_percent : 2.1, 1.9, 3.0, 1.1, 3.2, 4.2, 1.8, 3.1, 2.8\n*/\n \nCREATE TABLE race (\n\t\"Race_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Class\" TEXT, \n\t\"Date\" TEXT, \n\t\"Track_ID\" TEXT, \n\tPRIMARY KEY (\"Race_ID\"), \n\tFOREIGN KEY(\"Track_ID\") REFERENCES track (\"Track_ID\")\n)\n/*\nColumns in race and all categories for low cardinality columns :\nRace_ID : 1, 2, 5, 7, 4, 6, 3\nName : Bosch Engineering 250 at VIR, RumBum.com 250, Sahlen's Six Hours of the Glen, Lime Rock GT Classic 250, Gainsco Grand Prix of Miami, Mexico City 250, Rolex 24 At Daytona\nClass : GT, DP/GT\nDate : January 26 January 27, June 7, April 19, May 26, May 17, April 27, March 29\nTrack_ID : 1, 2, 5, 7, 4, 6\n*/\n \nCREATE TABLE election (\n\t\"Election_ID\" INTEGER, \n\t\"Representative_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Votes\" REAL, \n\t\"Vote_Percent\" REAL, \n\t\"Seats\" REAL, \n\t\"Place\" REAL, \n\tPRIMARY KEY (\"Election_ID\"), \n\tFOREIGN KEY(\"Representative_ID\") REFERENCES representative (\"Representative_ID\")\n)\n/*\nColumns in election and all categories for low cardinality columns :\nElection_ID : 1, 2, 5, 4, 3\nRepresentative_ID : 1, 2, 5, 7, 4\nDate : 1946, 1949, July 1942, October 1942, 1953\nVotes : 11059.0, 9423.0, 13049.0, 12422.0, 14077.0\nVote_Percent : 16.0, 19.5, 16.2, 18.5\nSeats : 10.0, 6.0, 7.0, 9.0\nPlace : 3.0, 1.0, 2.0\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n*/\n \nCREATE TABLE market (\n\t\"Market_ID\" INTEGER, \n\t\"Country\" TEXT, \n\t\"Number_cities\" INTEGER, \n\tPRIMARY KEY (\"Market_ID\")\n)\n/*\nColumns in market and all categories for low cardinality columns :\nMarket_ID : 1, 2, 5, 4, 6, 3\nCountry : Japan, China, France, Russia, USA, Poland\nNumber_cities : 700, 453, 231, 212, 209, 540\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Employees\" (\n\temployee_id INTEGER NOT NULL, \n\trole_code CHAR(15) NOT NULL, \n\temployee_name VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (employee_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Roles\" (role_code)\n)\n/*\nColumns in Employees and all categories for low cardinality columns :\nemployee_id : 1, 2, 5, 7, 8, 3\nrole_code : MG, ED, PR, PT\nemployee_name : Koby, Erling, Kenyon, Haley, Jordyn, Clemens\nother_details : f, b, h, v, u\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n" }, { "role": "user", "content": "Return the average, maximum, and minimum budgets in millions for movies made before the year 2000." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie.\nFrom these tables, I'll be using the following columns: budget_million.\nThe SQL query I'll be generating is:\nSELECT avg(budget_million) , max(budget_million) , min(budget_million) FROM movie WHERE YEAR < 2000" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE \"Apartments\" (\n\tapt_id INTEGER NOT NULL, \n\tbuilding_id INTEGER NOT NULL, \n\tapt_type_code CHAR(15), \n\tapt_number CHAR(10), \n\tbathroom_count INTEGER, \n\tbedroom_count INTEGER, \n\troom_count CHAR(5), \n\tPRIMARY KEY (apt_id), \n\tFOREIGN KEY(building_id) REFERENCES \"Apartment_Buildings\" (building_id), \n\tUNIQUE (apt_id)\n)\n/*\nColumns in Apartments and 3 examples in each column for high cardinality columns :\napt_id : 1, 13, 11\napt_number : Suite 307, Apt. 411, Apt. 585\n*/\n/*\nColumns in Apartments and all categories for low cardinality columns :\nbuilding_id : 153, 673, 808, 744, 624, 790, 191, 734, 225\napt_type_code : Studio, Flat, Duplex\nbathroom_count : 1, 2, 3\nbedroom_count : 5, 4, 6, 3\nroom_count : 5, 7, 8, 6, 3, 9\n*/\n \nCREATE TABLE status (\n\t\"statusId\" INTEGER, \n\tstatus TEXT, \n\tPRIMARY KEY (\"statusId\")\n)\n/*\nColumns in status and 3 examples in each column for high cardinality columns :\nstatusId : 87, 56, 65\nstatus : Safety concerns, Suspension, Spark plugs\n*/\n\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"PROFESSOR\" (\n\t\"EMP_NUM\" INTEGER, \n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"PROF_OFFICE\" VARCHAR(50), \n\t\"PROF_EXTENSION\" VARCHAR(4), \n\t\"PROF_HIGH_DEGREE\" VARCHAR(5), \n\tFOREIGN KEY(\"EMP_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\"), \n\tFOREIGN KEY(\"DEPT_CODE\") REFERENCES \"DEPARTMENT\" (\"DEPT_CODE\")\n)\n/*\nColumns in PROFESSOR and 3 examples in each column for high cardinality columns :\nEMP_NUM : 387, 301, 155\nDEPT_CODE : ECON/FIN, ART, HIST\nPROF_OFFICE : KLR 203E, BBG 208, AAK 230\nPROF_EXTENSION : 2248, 2851, 4436\n*/\n/*\nColumns in PROFESSOR and all categories for low cardinality columns :\nPROF_HIGH_DEGREE : Ph.D., MBA, MA, DBA\n*/\n \nCREATE TABLE \"Council_Tax\" (\n\tcouncil_tax_id INTEGER NOT NULL, \n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tPRIMARY KEY (council_tax_id), \n\tFOREIGN KEY(cmi_cross_ref_id) REFERENCES \"CMI_Cross_References\" (cmi_cross_ref_id)\n)\n/*\nColumns in Council_Tax and all categories for low cardinality columns :\ncouncil_tax_id : 1, 2, 7, 8, 3, 9\ncmi_cross_ref_id : 106, 103, 102, 101, 104, 105\n*/\n \nCREATE TABLE \"Product_Characteristics\" (\n\tproduct_id INTEGER NOT NULL, \n\tcharacteristic_id INTEGER NOT NULL, \n\tproduct_characteristic_value VARCHAR(50), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id), \n\tFOREIGN KEY(characteristic_id) REFERENCES \"Characteristics\" (characteristic_id)\n)\n/*\nColumns in Product_Characteristics and all categories for low cardinality columns :\nproduct_id : 1, 13, 11, 5, 7, 8, 6, 12, 14\ncharacteristic_id : 13, 10, 11, 2, 4, 6, 12, 3, 15\nproduct_characteristic_value : high, low, medium\n*/\n \nCREATE TABLE furniture_manufacte (\n\t\"Manufacturer_ID\" INTEGER, \n\t\"Furniture_ID\" INTEGER, \n\t\"Price_in_Dollar\" REAL, \n\tPRIMARY KEY (\"Manufacturer_ID\", \"Furniture_ID\"), \n\tFOREIGN KEY(\"Furniture_ID\") REFERENCES furniture (\"Furniture_ID\"), \n\tFOREIGN KEY(\"Manufacturer_ID\") REFERENCES manufacturer (\"Manufacturer_ID\")\n)\n/*\nColumns in furniture_manufacte and all categories for low cardinality columns :\nManufacturer_ID : 1, 7, 4, 5\nFurniture_ID : 1, 2, 7, 4, 3\nPrice_in_Dollar : 239.0, 1234.0, 443.0, 2124.0, 450.0\n*/\n \nCREATE TABLE \"Document_Functional_Areas\" (\n\tdocument_code VARCHAR(15) NOT NULL, \n\tfunctional_area_code VARCHAR(15) NOT NULL, \n\tFOREIGN KEY(functional_area_code) REFERENCES \"Functional_Areas\" (functional_area_code), \n\tFOREIGN KEY(document_code) REFERENCES \"Documents\" (document_code)\n)\n/*\nColumns in Document_Functional_Areas and 3 examples in each column for high cardinality columns :\ndocument_code : 217, 930, 958\n*/\n/*\nColumns in Document_Functional_Areas and all categories for low cardinality columns :\nfunctional_area_code : 1, 8, 9\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Customer_Event_Notes\" (\n\t\"Customer_Event_Note_ID\" INTEGER NOT NULL, \n\t\"Customer_Event_ID\" INTEGER NOT NULL, \n\tservice_type_code CHAR(15) NOT NULL, \n\tresident_id INTEGER NOT NULL, \n\tproperty_id INTEGER NOT NULL, \n\tdate_moved_in DATETIME NOT NULL, \n\tPRIMARY KEY (\"Customer_Event_Note_ID\"), \n\tFOREIGN KEY(\"Customer_Event_ID\") REFERENCES \"Customer_Events\" (\"Customer_Event_ID\")\n)\n/*\nColumns in Customer_Event_Notes and 3 examples in each column for high cardinality columns :\nCustomer_Event_Note_ID : 91, 56, 65\ndate_moved_in : 2016-08-08 07:58:26, 2016-08-04 01:06:05, 2016-12-11 01:05:14\n*/\n/*\nColumns in Customer_Event_Notes and all categories for low cardinality columns :\nCustomer_Event_ID : 428, 591, 606, 559, 70, 216, 817, 627\nservice_type_code : Cleanning, Check\nresident_id : 87, 67, 45, 37, 28, 88, 58, 43\nproperty_id : 120, 605, 791, 373, 849, 748, 669, 445, 879, 107\n*/\n \nCREATE TABLE jobs (\n\t\"JOB_ID\" VARCHAR(10) DEFAULT '' NOT NULL, \n\t\"JOB_TITLE\" VARCHAR(35) NOT NULL, \n\t\"MIN_SALARY\" DECIMAL(6, 0) DEFAULT NULL, \n\t\"MAX_SALARY\" DECIMAL(6, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"JOB_ID\")\n)\n/*\nColumns in jobs and 3 examples in each column for high cardinality columns :\nJOB_ID : HR_REP, ST_MAN, AD_PRES\nJOB_TITLE : Purchasing Clerk, Stock Clerk, Marketing Manager\nMIN_SALARY : 20000, 8000, 3000\nMAX_SALARY : 20000, 8500, 40000\n*/\n\n \nCREATE TABLE exhibition (\n\t\"Exhibition_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Theme\" TEXT, \n\t\"Artist_ID\" INTEGER, \n\t\"Ticket_Price\" REAL, \n\tPRIMARY KEY (\"Exhibition_ID\"), \n\tFOREIGN KEY(\"Artist_ID\") REFERENCES artist (\"Artist_ID\")\n)\n/*\nColumns in exhibition and all categories for low cardinality columns :\nExhibition_ID : 1, 2, 5, 4, 6, 3\nYear : 2004, 2009, 2005, 2008, 2006, 2007\nTheme : Christmas Tree, Santa Claus and Rudolph the Red-Nosed Reindeer, Summer, Christmas stocking, Spring, Santa Claus\nArtist_ID : 1, 2, 4, 6, 3\nTicket_Price : 19.95, 9.95, 29.95, 14.95, 16.95\n*/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n*/\n \nCREATE TABLE \"Player\" (\n\t\"pID\" NUMERIC(5, 0) NOT NULL, \n\t\"pName\" VARCHAR(20), \n\t\"yCard\" VARCHAR(3), \n\t\"HS\" NUMERIC(5, 0), \n\tPRIMARY KEY (\"pID\")\n)\n/*\nColumns in Player and all categories for low cardinality columns :\npID : 40002, 20002, 40004, 30003, 10001, 50005\npName : Charles, Drago, Eddie, Blake, Andrew, David\nyCard : yes, no\nHS : 1600, 1200, 300, 600\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE track (\n\t\"Track_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Location\" TEXT, \n\t\"Seating\" REAL, \n\t\"Year_Opened\" REAL, \n\tPRIMARY KEY (\"Track_ID\")\n)\n/*\nColumns in track and all categories for low cardinality columns :\nTrack_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Homestead-Miami Speedway, Darlington Raceway, Chicagoland Speedway, Auto Club Speedway, Phoenix International Raceway, Martinsville Speedway, Michigan International Speedway, Kansas Speedway, Daytona International Speedway\nLocation : Homestead, FL, Kansas City, KS, Brooklyn, MI, Avondale, AZ, Daytona Beach, FL, Joliet, IL, Darlington, SC, Ridgeway, VA, Fontana, CA\nSeating : 76812.0, 92000.0, 63000.0, 75000.0, 137243.0, 65000.0, 81687.0, 168000.0\nYear_Opened : 2001.0, 1947.0, 1995.0, 1968.0, 1997.0, 1964.0, 1959.0, 1950.0\n*/\n \nCREATE TABLE operate_company (\n\tid INTEGER, \n\tname TEXT, \n\t\"Type\" TEXT, \n\t\"Principal_activities\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in operate_company and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nname : China Pacific Laundry Services, Cathay Pacific Holidays, CLS Catering Services Limited\n*/\n/*\nColumns in operate_company and all categories for low cardinality columns :\nType : Joint Venture, Subsidiary, Corporate\nPrincipal_activities : Laundry, Airline, Catering services, Travel agency, Ground handling, Cargo, Cargo airline\nIncorporated_in : Canada, China, Hong Kong, Vietnam, Taiwan\nGroup_Equity_Shareholding : 45.0, 60.0, 30.0, 49.0, 100.0, 40.0, 18.77\n*/\n \nCREATE TABLE \"Behavior_Incident\" (\n\tincident_id INTEGER, \n\tincident_type_code VARCHAR(10) NOT NULL, \n\tstudent_id INTEGER NOT NULL, \n\tdate_incident_start DATETIME, \n\tdate_incident_end DATETIME, \n\tincident_summary VARCHAR(255), \n\trecommendations VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (incident_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id), \n\tFOREIGN KEY(incident_type_code) REFERENCES \"Ref_Incident_Type\" (incident_type_code)\n)\n/*\nColumns in Behavior_Incident and 3 examples in each column for high cardinality columns :\nincident_id : 1, 13, 11\nstudent_id : 1, 13, 11\ndate_incident_start : 2018-01-31 10:51:13, 2017-08-27 03:21:30, 2017-05-02 12:52:09\ndate_incident_end : 2018-03-22 02:10:35, 2018-03-06 14:44:37, 2018-03-16 14:37:20\n*/\n/*\nColumns in Behavior_Incident and all categories for low cardinality columns :\nincident_type_code : VIOLENCE, DISTURB, NOISE\nincident_summary : None\nrecommendations : None, Transfer schools\nother_details : None\n*/\n \nCREATE TABLE genre (\n\tg_name TEXT(20) NOT NULL, \n\trating TEXT(10), \n\tmost_popular_in TEXT(50), \n\tPRIMARY KEY (g_name)\n)\n/*\nColumns in genre and all categories for low cardinality columns :\ng_name : tagore, folk, modern, nazrul, blues, pop\nrating : 7, 8, 9\nmost_popular_in : America, Canada, Sylhet,Chittagong,Kustia, Bangladesh\n*/\n" }, { "role": "user", "content": "List all company names with a book published by Alyson." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: culture_company, book_club.\nFrom these tables, I'll be using the following columns: culture_company.company_name, culture_company.book_club_id, book_club.book_club_id, book_club.publisher.\nThe SQL query I'll be generating is:\nSELECT T1.company_name FROM culture_company AS T1 JOIN book_club AS T2 ON T1.book_club_id = T2.book_club_id WHERE T2.publisher = 'Alyson'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE camera_lens (\n\tid INTEGER, \n\tbrand TEXT, \n\tname TEXT, \n\tfocal_length_mm REAL, \n\tmax_aperture REAL, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in camera_lens and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Panasonic Leica DG Summilux 25mm f /1.4 Asph., Sigma 19mm f2.8 EX DN, Sigma 30mm f2.8 DN\n*/\n/*\nColumns in camera_lens and all categories for low cardinality columns :\nbrand : Sigma, Olympus, Panasonic, Schneider Kreuznach\nfocal_length_mm : 45.0, 30.0, 15.0, 25.0, 150.0, 19.0, 14.0, 42.5, 75.0\nmax_aperture : 1.2, 8.0, 1.4, 2.0, 1.8, 2.8\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"Is_Male\" TEXT, \n\t\"Age\" INTEGER, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and 3 examples in each column for high cardinality columns :\nPeople_ID : 1, 11, 2\nName : Summer Duval, Annie Mediate, Juli Hanson\n*/\n/*\nColumns in people and all categories for low cardinality columns :\nCountry : Sweden, Canada, United States, Australia, Northern Ireland\nIs_Male : T, F\nAge : 26, 25, 36, 30, 34, 32, 27, 31\n*/\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status VARCHAR(15) NOT NULL, \n\torder_date DATETIME, \n\torder_details VARCHAR(255), \n\tPRIMARY KEY (order_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id)\n)\n/*\nColumns in Customer_Orders and 3 examples in each column for high cardinality columns :\norder_id : 1, 13, 11\norder_date : 2018-03-21 11:20:46, 2018-03-22 14:57:30, 2018-03-17 07:13:53\n*/\n/*\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 11, 5, 15, 8, 4, 12, 3, 10\norder_status : Delivered, Cancelled\norder_details : None, Second time\n*/\n \nCREATE TABLE \"Apartment_Facilities\" (\n\tapt_id INTEGER NOT NULL, \n\tfacility_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (apt_id, facility_code), \n\tFOREIGN KEY(apt_id) REFERENCES \"Apartments\" (apt_id)\n)\n/*\nColumns in Apartment_Facilities and all categories for low cardinality columns :\napt_id : 1, 2, 5, 6, 3, 15, 9\nfacility_code : Gym, Swimming Pool, Boardband, Cable TV\n*/\n \nCREATE TABLE \"Manufacturers\" (\n\t\"Code\" INTEGER, \n\t\"Name\" VARCHAR(255) NOT NULL, \n\t\"Headquarter\" VARCHAR(255) NOT NULL, \n\t\"Founder\" VARCHAR(255) NOT NULL, \n\t\"Revenue\" REAL, \n\tPRIMARY KEY (\"Code\")\n)\n/*\nColumns in Manufacturers and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 6, 3\nName : Winchester, Fujitsu, Iomega, Hewlett-Packard, Creative Labs, Sony\nHeadquarter : Beijing, Los Angeles, Austin, Tokyo, Paris, Taiwan\nFounder : Owen, Mary, James, John, Robert, Andy\nRevenue : 30.0, 100.0, 130.0, 200.0, 50.0, 120.0\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_first_name VARCHAR(50), \n\tcustomer_middle_initial VARCHAR(1), \n\tcustomer_last_name VARCHAR(50), \n\tgender VARCHAR(1), \n\temail_address VARCHAR(255), \n\tlogin_name VARCHAR(80), \n\tlogin_password VARCHAR(20), \n\tphone_number VARCHAR(255), \n\ttown_city VARCHAR(50), \n\tstate_county_province VARCHAR(50), \n\tcountry VARCHAR(50), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_first_name : Devin, Ruby, Joesph\ncustomer_last_name : Muller, Weimann, Glover\nemail_address : roosevelt.collier@example.org, pyundt@example.org, anastacio45@example.org\nlogin_name : zdeckow, rubye.padberg, feeney.lauriane\nlogin_password : 180a37476c537e78d3de, 035f2ba1e2a675c4f426, d4ade599672bccdabeee\nphone_number : 241.796.1219x37862, (791)562-7792x45732, (193)465-6674x4952\ntown_city : North Nellie, Kenshire, West Khaliltown\nstate_county_province : Louisiana, SouthDakota, Kansas\n*/\n/*\nColumns in Customers and all categories for low cardinality columns :\ncustomer_middle_initial : E, K, H, A, G, L, V, M, B\ngender : 1, 0\ncountry : USA\n*/\n \nCREATE TABLE \"Catalog_Contents_Additional_Attributes\" (\n\tcatalog_entry_id INTEGER NOT NULL, \n\tcatalog_level_number INTEGER NOT NULL, \n\tattribute_id INTEGER NOT NULL, \n\tattribute_value VARCHAR(255) NOT NULL, \n\tFOREIGN KEY(catalog_level_number) REFERENCES \"Catalog_Structure\" (catalog_level_number), \n\tFOREIGN KEY(catalog_entry_id) REFERENCES \"Catalog_Contents\" (catalog_entry_id)\n)\n/*\nColumns in Catalog_Contents_Additional_Attributes and all categories for low cardinality columns :\ncatalog_entry_id : 1, 11, 2, 5, 8, 4, 6, 12, 14, 15\ncatalog_level_number : 1, 8, 9\nattribute_id : 1, 2, 4, 3\nattribute_value : 1, 0\n*/\n \nCREATE TABLE \"Payments\" (\n\t\"Payment_ID\" INTEGER NOT NULL, \n\t\"Settlement_ID\" INTEGER NOT NULL, \n\t\"Payment_Method_Code\" VARCHAR(255), \n\t\"Date_Payment_Made\" DATE, \n\t\"Amount_Payment\" INTEGER, \n\tPRIMARY KEY (\"Payment_ID\"), \n\tFOREIGN KEY(\"Settlement_ID\") REFERENCES \"Settlements\" (\"Settlement_ID\")\n)\n/*\nColumns in Payments and 3 examples in each column for high cardinality columns :\nPayment_ID : 754, 739, 542\nDate_Payment_Made : 2017-06-24, 2017-08-06, 2017-12-16\nAmount_Payment : 423154, 155654, 71246\n*/\n/*\nColumns in Payments and all categories for low cardinality columns :\nSettlement_ID : 527, 476, 564, 983, 682, 648, 597, 512, 516\nPayment_Method_Code : Visa, Discover Card, American Express, MasterCard\n*/\n \nCREATE TABLE \"League\" (\n\tid INTEGER, \n\tcountry_id INTEGER, \n\tname TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(country_id) REFERENCES \"Country\" (id)\n)\n/*\nColumns in League and 3 examples in each column for high cardinality columns :\nid : 1, 19694, 7809\ncountry_id : 1, 19694, 7809\nname : Portugal Liga ZON Sagres, England Premier League, Belgium Jupiler League\n*/\n\n \nCREATE TABLE \"Students\" (\n\tstudent_id INTEGER, \n\taddress_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(80), \n\tmiddle_name VARCHAR(40), \n\tlast_name VARCHAR(40), \n\tcell_mobile_number VARCHAR(40), \n\temail_address VARCHAR(40), \n\tdate_first_rental DATETIME, \n\tdate_left_university DATETIME, \n\tother_student_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/*\nColumns in Students and 3 examples in each column for high cardinality columns :\nstudent_id : 1, 13, 11\naddress_id : 1, 20, 2\nfirst_name : Louvenia, Isac, Emma\nmiddle_name : Gardner, Crystal, Cleta\nlast_name : Huels, Weimann, Fadel\ncell_mobile_number : 1-247-673-8446, 235.899.9744, 1-751-162-9676x115\nemail_address : frederique.mante@example.org, gbeatty@example.com, foster.zemlak@example.com\ndate_first_rental : 2017-07-20 18:20:27, 2017-12-05 15:20:04, 2017-05-24 05:00:18\ndate_left_university : 2018-03-03 03:33:05, 2018-03-12 15:05:53, 2018-03-15 01:47:11\n*/\n/*\nColumns in Students and all categories for low cardinality columns :\nother_student_details : None, first honor\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE \"PersonFriend\" (\n\tname VARCHAR(20), \n\tfriend VARCHAR(20), \n\tyear INTEGER, \n\tFOREIGN KEY(name) REFERENCES \"Person\" (name), \n\tFOREIGN KEY(friend) REFERENCES \"Person\" (name)\n)\n/*\nColumns in PersonFriend and all categories for low cardinality columns :\nname : Alice, Zach, Bob\nfriend : Alice, Dan, Zach, Bob\nyear : 10, 5, 6, 12\n*/\n \nCREATE TABLE county_public_safety (\n\t\"County_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Population\" INTEGER, \n\t\"Police_officers\" INTEGER, \n\t\"Residents_per_officer\" INTEGER, \n\t\"Case_burden\" INTEGER, \n\t\"Crime_rate\" REAL, \n\t\"Police_force\" TEXT, \n\t\"Location\" TEXT, \n\tPRIMARY KEY (\"County_ID\")\n)\n/*\nColumns in county_public_safety and all categories for low cardinality columns :\nCounty_ID : 1, 2, 5, 4, 6, 3\nName : Central Saanich, Campbell River, Chilliwack, Castlegar, Burnaby, Abbotsford\nPopulation : 16821, 204320, 128165, 73066, 7821, 30810\nPolice_officers : 91, 11, 187, 253, 40, 21\nResidents_per_officer : 711, 770, 801, 808, 803, 685\nCase_burden : 100, 137, 140, 39, 107, 81\nCrime_rate : 178.0, 150.0, 49.0, 118.0, 174.0, 123.0\nPolice_force : Abbotsford Police Department, Central Saanich Police, RCMP\nLocation : West, East, North\n*/\n \nCREATE TABLE \"Problem_Log\" (\n\tproblem_log_id INTEGER, \n\tassigned_to_staff_id INTEGER NOT NULL, \n\tproblem_id INTEGER NOT NULL, \n\tproblem_category_code VARCHAR(20) NOT NULL, \n\tproblem_status_code VARCHAR(20) NOT NULL, \n\tlog_entry_date DATETIME, \n\tlog_entry_description VARCHAR(255), \n\tlog_entry_fix VARCHAR(255), \n\tother_log_details VARCHAR(255), \n\tPRIMARY KEY (problem_log_id), \n\tFOREIGN KEY(problem_status_code) REFERENCES \"Problem_Status_Codes\" (problem_status_code), \n\tFOREIGN KEY(problem_id) REFERENCES \"Problems\" (problem_id), \n\tFOREIGN KEY(assigned_to_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(problem_category_code) REFERENCES \"Problem_Category_Codes\" (problem_category_code)\n)\n/*\nColumns in Problem_Log and 3 examples in each column for high cardinality columns :\nproblem_log_id : 1, 13, 11\nlog_entry_date : 1997-08-31 08:19:12, 1974-09-13 00:37:26, 2011-11-12 23:30:53\nlog_entry_description : t, d, b\nlog_entry_fix : t, i, s\nother_log_details : d, f, b\n*/\n/*\nColumns in Problem_Log and all categories for low cardinality columns :\nassigned_to_staff_id : 1, 13, 11, 2, 5, 8, 4, 6, 12, 10\nproblem_id : 1, 13, 11, 10, 7, 8, 4, 12, 15\nproblem_category_code : Datatabase, Middleware, GUI\nproblem_status_code : Solved, Reported\n*/\n \nCREATE TABLE party_host (\n\t\"Party_ID\" INTEGER, \n\t\"Host_ID\" INTEGER, \n\t\"Is_Main_in_Charge\" BOOLEAN, \n\tPRIMARY KEY (\"Party_ID\", \"Host_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\"), \n\tFOREIGN KEY(\"Host_ID\") REFERENCES host (\"Host_ID\")\n)\n/*\nColumns in party_host and all categories for low cardinality columns :\nParty_ID : 1, 2, 8, 4, 6\nHost_ID : 1, 2, 5, 7, 3, 10\nIs_Main_in_Charge : True\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n" }, { "role": "user", "content": "What are all the company names that have a book published by Alyson?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: culture_company, book_club.\nFrom these tables, I'll be using the following columns: culture_company.company_name, culture_company.book_club_id, book_club.book_club_id, book_club.publisher.\nThe SQL query I'll be generating is:\nSELECT T1.company_name FROM culture_company AS T1 JOIN book_club AS T2 ON T1.book_club_id = T2.book_club_id WHERE T2.publisher = 'Alyson'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE school_bus (\n\t\"School_ID\" INTEGER, \n\t\"Driver_ID\" INTEGER, \n\t\"Years_Working\" INTEGER, \n\t\"If_full_time\" BOOLEAN, \n\tPRIMARY KEY (\"School_ID\", \"Driver_ID\"), \n\tFOREIGN KEY(\"Driver_ID\") REFERENCES driver (\"Driver_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in school_bus and all categories for low cardinality columns :\nSchool_ID : 1, 5, 7, 4, 3\nDriver_ID : 7, 4, 3, 10, 9\nYears_Working : 2, 8, 6, 3, 10\nIf_full_time : True\n*/\n \nCREATE TABLE genre (\n\tg_name TEXT(20) NOT NULL, \n\trating TEXT(10), \n\tmost_popular_in TEXT(50), \n\tPRIMARY KEY (g_name)\n)\n/*\nColumns in genre and all categories for low cardinality columns :\ng_name : tagore, folk, modern, nazrul, blues, pop\nrating : 7, 8, 9\nmost_popular_in : America, Canada, Sylhet,Chittagong,Kustia, Bangladesh\n*/\n \nCREATE TABLE \"Track\" (\n\t\"TrackId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(200) NOT NULL, \n\t\"AlbumId\" INTEGER DEFAULT NULL, \n\t\"MediaTypeId\" INTEGER NOT NULL, \n\t\"GenreId\" INTEGER DEFAULT NULL, \n\t\"Composer\" VARCHAR(220) DEFAULT NULL, \n\t\"Milliseconds\" INTEGER NOT NULL, \n\t\"Bytes\" INTEGER DEFAULT NULL, \n\t\"UnitPrice\" DECIMAL(10, 2) NOT NULL, \n\tPRIMARY KEY (\"TrackId\"), \n\tFOREIGN KEY(\"MediaTypeId\") REFERENCES \"MediaType\" (\"MediaTypeId\"), \n\tFOREIGN KEY(\"GenreId\") REFERENCES \"Genre\" (\"GenreId\"), \n\tFOREIGN KEY(\"AlbumId\") REFERENCES \"Album\" (\"AlbumId\")\n)\n/*\nColumns in Track and 3 examples in each column for high cardinality columns :\nTrackId : 87, 56, 65\nName : Snoopy's search-Red baron, The Winner Loses, Leave My Girl Alone\nAlbumId : 17, 9, 16\nComposer : Ned Fairchild, Tony Iommi, Bill Ward, Geezer Butler, Ozzy Osbourne, Berry Gordy, Jr./Janie Bradford\nMilliseconds : 263497, 307617, 204721\nBytes : 6859518, 2301989, 6420530\n*/\n/*\nColumns in Track and all categories for low cardinality columns :\nMediaTypeId : 1, 2\nGenreId : 1, 2, 5, 4, 6, 3\nUnitPrice : 0.99\n*/\n \nCREATE TABLE language (\n\tlanguage_id INTEGER NOT NULL, \n\tname CHAR(20) NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (language_id)\n)\n/*\nColumns in language and all categories for low cardinality columns :\nlanguage_id : \nname : \nlast_update : \n*/\n \nCREATE TABLE \"Project_Outcomes\" (\n\tproject_id INTEGER NOT NULL, \n\toutcome_code VARCHAR(10) NOT NULL, \n\toutcome_details VARCHAR(255), \n\tFOREIGN KEY(outcome_code) REFERENCES \"Research_Outcomes\" (outcome_code), \n\tFOREIGN KEY(project_id) REFERENCES \"Projects\" (project_id)\n)\n/*\nColumns in Project_Outcomes and all categories for low cardinality columns :\nproject_id : 13, 11, 5, 7, 4, 6, 14, 3, 12, 9\noutcome_code : Patent, Paper\noutcome_details : None\n*/\n \nCREATE TABLE performance (\n\t\"Performance_ID\" REAL, \n\t\"Date\" TEXT, \n\t\"Host\" TEXT, \n\t\"Location\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Performance_ID\")\n)\n/*\nColumns in performance and all categories for low cardinality columns :\nPerformance_ID : 3.0, 1.0, 2.0, 6.0, 4.0, 5.0\nDate : February 7, February 4, February 2, February 5, February 10, February 11\nHost : Ottawa Senators, New York Rangers, Pittsburgh Penguins, Atlanta Thrashers, Montreal Canadiens, Boston Bruins\nLocation : Madison Square Garden, Scotiabank Place, Verizon Center, TD Garden, Bell Centre\nAttendance : 2173, 1878, 1877, 1820, 1982, 165\n*/\n \nCREATE TABLE building (\n\tbuilding_id TEXT, \n\t\"Name\" TEXT, \n\t\"Street_address\" TEXT, \n\t\"Years_as_tallest\" TEXT, \n\t\"Height_feet\" INTEGER, \n\t\"Floors\" INTEGER, \n\tPRIMARY KEY (building_id)\n)\n/*\nColumns in building and all categories for low cardinality columns :\nbuilding_id : 1, 2, 5, 7, 4, 6, 3, 0\nName : Bank of America Tower, Franklin Exchange Building, One Tampa City Center, 100 North Tampa, Park Tower, Citizens Bank Building, Floridan Hotel, Tampa City Hall\nStreet_address : 905 Franklin Street, 701 North Franklin Street, 655 North Franklin Street, 315 John F. Kennedy Boulevard, 101 East Kennedy Boulevard, 100 North Tampa Street, 400 North Tampa Street, 201 North Franklin Street\nYears_as_tallest : 1966–1972, 1981–1986, 1913–1915, 1992–present, 1986–1992, 1915–1926, 1926–1966, 1972–1981\nHeight_feet : 204, 537, 458, 577, 145, 579, 160, 280\nFloors : 42, 36, 17, 12, 39, 10, 22\n*/\n \nCREATE TABLE party (\n\t\"Party_ID\" INTEGER, \n\t\"Party_Theme\" TEXT, \n\t\"Location\" TEXT, \n\t\"First_year\" TEXT, \n\t\"Last_year\" TEXT, \n\t\"Number_of_hosts\" INTEGER, \n\tPRIMARY KEY (\"Party_ID\")\n)\n/*\nColumns in party and all categories for low cardinality columns :\nParty_ID : 1, 2, 5, 7, 8, 4, 6, 3\nParty_Theme : Qlubtempo, In Qontrol, Club Q-BASE, QrimeTime, Teqnology, Houseqlassics, Hardcore Resurrection, Spring\nLocation : Various locations, RAI Amsterdam, Hemkade 48 Zaandam, Heineken Music Hall Amsterdam, Hemkade 48 Zaandam, Heineken Music Hall Amsterdam\nFirst_year : 2004, 2001, 1999, 2000, 2002\nLast_year : 2004, 2001, 2002, 2003, 2010, 2007\nNumber_of_hosts : 5, 7, 23, 4, 6, 18, 31\n*/\n \nCREATE TABLE \"Department\" (\n\t\"DNO\" INTEGER, \n\t\"Division\" VARCHAR(2), \n\t\"DName\" VARCHAR(25), \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\t\"DPhone\" INTEGER, \n\tPRIMARY KEY (\"DNO\")\n)\n/*\nColumns in Department and 3 examples in each column for high cardinality columns :\nDNO : 170, 560, 540\nDName : Economics, Mechanical Engineering, English\nRoom : 206, 312, 440\nBuilding : Krieger, NEB, Latrobe\nDPhone : 7499, 7601, 7119\n*/\n/*\nColumns in Department and all categories for low cardinality columns :\nDivision : EN, AS\n*/\n \nCREATE TABLE accelerator_compatible_browser (\n\taccelerator_id INTEGER, \n\tbrowser_id INTEGER, \n\tcompatible_since_year INTEGER, \n\tPRIMARY KEY (accelerator_id, browser_id), \n\tFOREIGN KEY(browser_id) REFERENCES browser (id), \n\tFOREIGN KEY(accelerator_id) REFERENCES \"Web_client_accelerator\" (id)\n)\n/*\nColumns in accelerator_compatible_browser and all categories for low cardinality columns :\naccelerator_id : 1, 2, 4, 3, 9\nbrowser_id : 1, 2, 4, 3\ncompatible_since_year : 2009, 2005, 1995, 2008, 2000, 1996, 2010, 2007\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_address_id INTEGER NOT NULL, \n\tcustomer_status_code VARCHAR(15) NOT NULL, \n\tdate_became_customer DATETIME, \n\tdate_of_birth DATETIME, \n\tfirst_name VARCHAR(80), \n\tlast_name VARCHAR(80), \n\tamount_outstanding DOUBLE, \n\temail_address VARCHAR(250), \n\tphone_number VARCHAR(255), \n\tcell_mobile_phone_number VARCHAR(255), \n\tPRIMARY KEY (customer_id), \n\tFOREIGN KEY(customer_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ndate_became_customer : 2016-03-18 06:14:18, 2016-05-13 07:38:23, 2017-10-05 14:15:46\ndate_of_birth : 1994-05-07 01:32:16, 1991-12-05 02:50:15, 1998-09-18 04:45:01\nfirst_name : Millie, Dianna, Carole\nlast_name : Schmeler, Tromp, Goodwin\namount_outstanding : 7093.0, 8144.0, 9447.0\nemail_address : mariela28@example.org, wehner.harold@example.com, afranecki@example.com\nphone_number : 1-618-535-9750, 218.550.1362, 753.921.0871\ncell_mobile_phone_number : 578-518-4785x612, (780)719-4206x033, (630)964-2426\n*/\n/*\nColumns in Customers and all categories for low cardinality columns :\ncustomer_address_id : 1, 13, 2, 7, 8, 12, 10, 9\ncustomer_status_code : Bad Customer, Good Customer\n*/\n \nCREATE TABLE faculty (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Faculty\" REAL, \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/*\nColumns in faculty and 3 examples in each column for high cardinality columns :\nCampus : 17, 21, 9\nFaculty : 449.8, 117.7, 1027.6\n*/\n/*\nColumns in faculty and all categories for low cardinality columns :\nYear : 2002, 2003, 2004\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE program (\n\t\"Program_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Origin\" TEXT, \n\t\"Launch\" REAL, \n\t\"Owner\" TEXT, \n\tPRIMARY KEY (\"Program_ID\")\n)\n/*\nColumns in program and all categories for low cardinality columns :\nProgram_ID : 1, 2, 5, 4, 3\nName : Toonmax, Aniworld, Youman, Jiajia, Kaku\nOrigin : Beijing, Shanghai, Guangdong, Hunan, Jiangsu\nLaunch : 2007.0, 2005.0, 2010.0, 2004.0\nOwner : Jiangsu Broadcasting Corporation (JSBC), Shanghai Media Group (SMG), Beijing Television (BTV), Hunan Broadcasting System (HBS), Southern Media Corporation (SMC)\n*/\n \nCREATE TABLE trust (\n\tsource_u_id INTEGER NOT NULL, \n\ttarget_u_id INTEGER NOT NULL, \n\ttrust INTEGER NOT NULL, \n\tFOREIGN KEY(target_u_id) REFERENCES useracct (u_id), \n\tFOREIGN KEY(source_u_id) REFERENCES useracct (u_id)\n)\n/*\nColumns in trust and all categories for low cardinality columns :\nsource_u_id : 1, 2, 7, 6, 3\ntarget_u_id : 2, 5, 4, 6, 3\ntrust : 1, 2, 7, 8, 4, 6, 3, 10\n*/\n \nCREATE TABLE pilot (\n\t\"Pilot_ID\" INTEGER, \n\t\"Pilot_name\" TEXT, \n\t\"Rank\" INTEGER, \n\t\"Age\" INTEGER, \n\t\"Nationality\" TEXT, \n\t\"Position\" TEXT, \n\t\"Join_Year\" INTEGER, \n\t\"Team\" TEXT, \n\tPRIMARY KEY (\"Pilot_ID\")\n)\n/*\nColumns in pilot and all categories for low cardinality columns :\nPilot_ID : 1, 2, 5, 4, 3\nPilot_name : Patrick O'Bryant, Charles Oakley, Dan O'Sullivan, Hakeem Olajuwon, Jermaine O'Neal\nRank : 34, 13, 45, 6\nAge : 37, 33, 40, 32, 22\nNationality : United States, Nigeria, United Kindom\nPosition : Center Team, Forward Team, Forward-Center Team\nJoin_Year : 2009, 2001, 2008, 1999, 2010\nTeam : Fordham, Eau Claire High School, Bradley, Virginia Union, Houston\n*/\n" }, { "role": "user", "content": "Show the movie titles and book titles for all companies in China." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie, culture_company, book_club.\nFrom these tables, I'll be using the following columns: movie.title, book_club.book_title, movie.movie_id, culture_company.movie_id, book_club.book_club_id, culture_company.book_club_id, culture_company.incorporated_in.\nThe SQL query I'll be generating is:\nSELECT T1.title , T3.book_title FROM movie AS T1 JOIN culture_company AS T2 ON T1.movie_id = T2.movie_id JOIN book_club AS T3 ON T3.book_club_id = T2.book_club_id WHERE T2.incorporated_in = 'China'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE \"Rooms\" (\n\t\"RoomId\" TEXT, \n\t\"roomName\" TEXT, \n\tbeds INTEGER, \n\t\"bedType\" TEXT, \n\t\"maxOccupancy\" INTEGER, \n\t\"basePrice\" INTEGER, \n\tdecor TEXT, \n\tPRIMARY KEY (\"RoomId\")\n)\n/*\nColumns in Rooms and all categories for low cardinality columns :\nRoomId : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nroomName : Convoke and sanguine, Immutable before decorum, Abscond or bolster, Recluse and defiance, Thrift and accolade, Riddle to exculpate, Harbinger but bequest, Frugal not apropos, Interim but salutary, Mendicant with cryptic\nbeds : 1, 2\nbedType : King, Double, Queen\nmaxOccupancy : 2, 4\nbasePrice : 250, 75, 100, 150, 125, 175\ndecor : modern, rustic, traditional\n*/\n \nCREATE TABLE happy_hour (\n\t\"HH_ID\" INTEGER, \n\t\"Shop_ID\" INTEGER, \n\t\"Month\" TEXT, \n\t\"Num_of_shaff_in_charge\" INTEGER, \n\tPRIMARY KEY (\"HH_ID\", \"Shop_ID\", \"Month\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in happy_hour and all categories for low cardinality columns :\nHH_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nShop_ID : 1, 2, 5, 3, 10\nMonth : June, May, April, July\nNum_of_shaff_in_charge : 5, 15, 4, 12, 3, 10\n*/\n \nCREATE TABLE \"match\" (\n\t\"Round\" REAL, \n\t\"Location\" TEXT, \n\t\"Country\" TEXT, \n\t\"Date\" TEXT, \n\t\"Fastest_Qualifying\" TEXT, \n\t\"Winning_Pilot\" TEXT, \n\t\"Winning_Aircraft\" TEXT, \n\tPRIMARY KEY (\"Round\"), \n\tFOREIGN KEY(\"Winning_Pilot\") REFERENCES pilot (\"Pilot_Id\"), \n\tFOREIGN KEY(\"Winning_Aircraft\") REFERENCES aircraft (\"Aircraft_ID\")\n)\n/*\nColumns in match and all categories for low cardinality columns :\nRound : 3.0, 1.0, 7.0, 2.0, 6.0, 4.0, 5.0\nLocation : EuroSpeedway Lausitz, Flamengo Beach , Rio de Janeiro, River Danube , Budapest, Swan River , Perth, Mina' Zayid , Abu Dhabi, New York City, Windsor , Ontario\nCountry : Canada, United States, Australia, Brazil, Germany, United Arab Emirates, Hungary\nDate : June 5–6, June 19–20, August 7–8, May 8–9, March 26–27, April 17–18, Cancelled\nFastest_Qualifying : Hannes Arch, Paul Bonhomme, Cancelled, Nigel Lamb\nWinning_Pilot : 1, 2, 4, 6, 9\nWinning_Aircraft : 1, 2, 5, 4, 3\n*/\n \nCREATE TABLE \"Institution\" (\n\t\"Institution_id\" TEXT, \n\t\"Institution\" TEXT, \n\t\"Location\" TEXT, \n\t\"Founded\" REAL, \n\t\"Type\" TEXT, \n\t\"Enrollment\" INTEGER, \n\t\"Team\" TEXT, \n\t\"Primary_Conference\" TEXT, \n\tbuilding_id TEXT, \n\tPRIMARY KEY (\"Institution_id\"), \n\tFOREIGN KEY(building_id) REFERENCES building (building_id)\n)\n/*\nColumns in Institution and 3 examples in each column for high cardinality columns :\nInstitution_id : 1, 2, 5\nInstitution : Ave Maria University, Lindenwood University–Belleville, Point University\nLocation : Mayville, North Dakota, Jacksonville, Florida, Babson Park, Florida\nEnrollment : 967, 616, 3102\nTeam : Gyrenes, Comets, Warriors\n*/\n/*\nColumns in Institution and all categories for low cardinality columns :\nFounded : 1937.0, 1881.0, 1927.0, 2003.0, 1883.0, 1866.0, 1998.0, 1884.0, 1889.0, 1890.0\nType : Public, Tribal, Private\nPrimary_Conference : MCAC, CalPac, Gulf Coast (GCAC), AAC, none, The Sun\nbuilding_id : 1, 2, 5, 7, 4, 3, 0\n*/\n \nCREATE TABLE journal_committee (\n\t\"Editor_ID\" INTEGER, \n\t\"Journal_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"Editor_ID\", \"Journal_ID\"), \n\tFOREIGN KEY(\"Journal_ID\") REFERENCES journal (\"Journal_ID\"), \n\tFOREIGN KEY(\"Editor_ID\") REFERENCES editor (\"Editor_ID\")\n)\n/*\nColumns in journal_committee and all categories for low cardinality columns :\nEditor_ID : 1, 8, 4, 6, 3, 9\nJournal_ID : 13, 11, 2, 17, 4, 6, 12\nWork_Type : Title, Article, Photo\n*/\n \nCREATE TABLE user_profiles (\n\tuid INTEGER NOT NULL, \n\tname VARCHAR(255) DEFAULT NULL, \n\temail VARCHAR(255) DEFAULT NULL, \n\tpartitionid INTEGER DEFAULT NULL, \n\tfollowers INTEGER DEFAULT NULL, \n\tPRIMARY KEY (uid)\n)\n/*\nColumns in user_profiles and all categories for low cardinality columns :\nuid : 1, 2, 5, 7, 4, 6, 3\nname : Natalie Portman, Mary, Black Widow\n, Tyler Swift, Celine Dion, Iron Man, Susan\nemail : susan@gmail.com\n, ts@superstar.com\n, cd@superstar.com, np@superstar.com, ts@richest.com, bw@superhero.com, Mary@yale.edu\npartitionid : 1, 2, 5, 23, 10\nfollowers : 23927492, 100, 94375428, 35425845, 890, 99999998, 6662425\n*/\n \nCREATE TABLE \"Club\" (\n\t\"ClubID\" INTEGER, \n\t\"ClubName\" VARCHAR(40), \n\t\"ClubDesc\" VARCHAR(1024), \n\t\"ClubLocation\" VARCHAR(40), \n\tPRIMARY KEY (\"ClubID\")\n)\n/*\nColumns in Club and all categories for low cardinality columns :\nClubID : 1, 2, 4, 3\nClubName : Bootup Baltimore, Pen and Paper Gaming, Tennis Club, Hopkins Student Enterprises\nClubDesc : Venture capital fund for student business., A competitive tennis club., Refurbish computers; teach kids and adults about computer basics., Play pen and paper games on campus.\nClubLocation : HHH, AKW\n*/\n \nCREATE TABLE management (\n\t\"department_ID\" INTEGER, \n\t\"head_ID\" INTEGER, \n\ttemporary_acting TEXT, \n\tPRIMARY KEY (\"department_ID\", \"head_ID\"), \n\tFOREIGN KEY(\"head_ID\") REFERENCES head (\"head_ID\"), \n\tFOREIGN KEY(\"department_ID\") REFERENCES department (\"Department_ID\")\n)\n/*\nColumns in management and all categories for low cardinality columns :\ndepartment_ID : 7, 15, 2, 11\nhead_ID : 5, 4, 6, 3, 10\ntemporary_acting : Yes, No\n*/\n \nCREATE TABLE \"Dorm_amenity\" (\n\tamenid INTEGER, \n\tamenity_name VARCHAR(25)\n)\n/*\nColumns in Dorm_amenity and 3 examples in each column for high cardinality columns :\namenid : 922, 955, 900\namenity_name : Study Room, Allows Pets, Roof\n*/\n\n \nCREATE TABLE \"Documents\" (\n\t\"Document_ID\" INTEGER NOT NULL, \n\t\"Document_Type_Code\" CHAR(15) NOT NULL, \n\t\"Project_ID\" INTEGER NOT NULL, \n\t\"Document_Date\" DATETIME, \n\t\"Document_Name\" VARCHAR(255), \n\t\"Document_Description\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Document_ID\"), \n\tFOREIGN KEY(\"Document_Type_Code\") REFERENCES \"Ref_Document_Types\" (\"Document_Type_Code\"), \n\tFOREIGN KEY(\"Project_ID\") REFERENCES \"Projects\" (\"Project_ID\")\n)\n/*\nColumns in Documents and 3 examples in each column for high cardinality columns :\nDocument_ID : 121, 300, 240\nDocument_Date : 2007-09-26 02:39:11, 1981-11-29 10:23:01, 1970-01-30 10:53:35\nDocument_Name : Katheryn statement, Review on UK files, Noel CV\n*/\n/*\nColumns in Documents and all categories for low cardinality columns :\nDocument_Type_Code : FM, BK, PP, CV\nProject_ID : 195, 30, 134, 105, 35\nDocument_Description : None\nOther_Details : None\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE journalist (\n\t\"journalist_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Nationality\" TEXT, \n\t\"Age\" TEXT, \n\t\"Years_working\" INTEGER, \n\tPRIMARY KEY (\"journalist_ID\")\n)\n/*\nColumns in journalist and 3 examples in each column for high cardinality columns :\njournalist_ID : 1, 11, 2\nName : Jack Meaney, Herbert Swindells, Jackie Waring\n*/\n/*\nColumns in journalist and all categories for low cardinality columns :\nNationality : Northern Ireland, Wales, England\nAge : 37, 28, 25, 33, 34, 43, 27, 29\nYears_working : 1, 5, 7, 8, 21, 6, 3, 12, 10, 9\n*/\n \nCREATE TABLE performance (\n\t\"Performance_ID\" REAL, \n\t\"Date\" TEXT, \n\t\"Host\" TEXT, \n\t\"Location\" TEXT, \n\t\"Attendance\" INTEGER, \n\tPRIMARY KEY (\"Performance_ID\")\n)\n/*\nColumns in performance and all categories for low cardinality columns :\nPerformance_ID : 3.0, 1.0, 2.0, 6.0, 4.0, 5.0\nDate : February 7, February 4, February 2, February 5, February 10, February 11\nHost : Ottawa Senators, New York Rangers, Pittsburgh Penguins, Atlanta Thrashers, Montreal Canadiens, Boston Bruins\nLocation : Madison Square Garden, Scotiabank Place, Verizon Center, TD Garden, Bell Centre\nAttendance : 2173, 1878, 1877, 1820, 1982, 165\n*/\n \nCREATE TABLE artist (\n\t\"Artist_ID\" INTEGER, \n\t\"Artist\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Famous_Title\" TEXT, \n\t\"Famous_Release_date\" TEXT, \n\tPRIMARY KEY (\"Artist_ID\")\n)\n/*\nColumns in artist and all categories for low cardinality columns :\nArtist_ID : 1, 2, 5, 7, 4, 6, 3\nArtist : Gorgoroth, Tangorodrim, Triumfall, Black Flame, Ophiolatry\nAge : 49, 34, 18, 27, 22, 35\nFamous_Title : Unholy Metal Way (re-release), Antievangelistical Process (re-release), Imperivm, Those Who Unleashed (re-release), Antithesis of All Flesh, Bergen 1996, Transmutation\nFamous_Release_date : November 2007, 2009, June 15, 2009, January 21, 2008, June 23, 2008\n*/\n \nCREATE TABLE game (\n\tstadium_id INTEGER, \n\tid INTEGER, \n\t\"Season\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Home_team\" TEXT, \n\t\"Away_team\" TEXT, \n\t\"Score\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(stadium_id) REFERENCES stadium (id)\n)\n/*\nColumns in game and 3 examples in each column for high cardinality columns :\nstadium_id : 1, 11, 2\nid : 17, 9, 16\nDate : 30 June 2013, 18 May 2007, 8 August 2009\nScore : 0–0 (7:6), –, 1–3\n*/\n/*\nColumns in game and all categories for low cardinality columns :\nSeason : 2009, 2013, 2008, 2012, 2011, 2010, 2007\nHome_team : Pakhtakor, Bunyodkor, Quruvchi\nAway_team : Pakhtakor, Bunyodkor, Quruvchi\nCompetition : League, Supercup, Cup\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n" }, { "role": "user", "content": "What are the titles of movies and books corresponding to companies incorporated in China?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie, culture_company, book_club.\nFrom these tables, I'll be using the following columns: movie.title, book_club.book_title, movie.movie_id, culture_company.movie_id, book_club.book_club_id, culture_company.book_club_id, culture_company.incorporated_in.\nThe SQL query I'll be generating is:\nSELECT T1.title , T3.book_title FROM movie AS T1 JOIN culture_company AS T2 ON T1.movie_id = T2.movie_id JOIN book_club AS T3 ON T3.book_club_id = T2.book_club_id WHERE T2.incorporated_in = 'China'" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE farm_competition (\n\t\"Competition_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Theme\" TEXT, \n\t\"Host_city_ID\" INTEGER, \n\t\"Hosts\" TEXT, \n\tPRIMARY KEY (\"Competition_ID\"), \n\tFOREIGN KEY(\"Host_city_ID\") REFERENCES city (\"City_ID\")\n)\n/*\nColumns in farm_competition and all categories for low cardinality columns :\nCompetition_ID : 1, 2, 5, 4, 6, 3\nYear : 2004, 2013, 2005, 2006, 2003, 2002\nTheme : MTV Cube, Valentine's Day, Codehunters, Carnival M is back!, Aliens, MTV Asia Aid\nHost_city_ID : 1, 2, 5, 4, 3\nHosts : Mandy Moore and Ronan Keating, Alicia Keys, Shaggy and Coco Lee, Leehom Wang and Kelly Rowland, Miley Cyrus Jared Leto and Karen Mok, Vanness Wu and Michelle Branch\n*/\n \nCREATE TABLE airport_aircraft (\n\t\"ID\" INTEGER, \n\t\"Airport_ID\" INTEGER, \n\t\"Aircraft_ID\" INTEGER, \n\tPRIMARY KEY (\"Airport_ID\", \"Aircraft_ID\"), \n\tFOREIGN KEY(\"Aircraft_ID\") REFERENCES aircraft (\"Aircraft_ID\"), \n\tFOREIGN KEY(\"Airport_ID\") REFERENCES airport (\"Airport_ID\")\n)\n/*\nColumns in airport_aircraft and all categories for low cardinality columns :\nID : 1, 2, 4, 3\nAirport_ID : 1, 9, 2, 6\nAircraft_ID : 1, 2, 5, 3\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE buildings (\n\tid INTEGER, \n\tname TEXT, \n\t\"City\" TEXT, \n\t\"Height\" INTEGER, \n\t\"Stories\" INTEGER, \n\t\"Status\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in buildings and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nname : Torre Mitikah, Residencial Vidalta Torre Altaire 2, Reforma 90\nStories : 67, 100, 20\n*/\n/*\nColumns in buildings and all categories for low cardinality columns :\nCity : Monterrey, Mexico City\nHeight : 330, 300, 150, 100, 210, 200, 50, 220, 73\nStatus : on-hold, under construction, proposed\n*/\n \nCREATE TABLE \"Student\" (\n\t\"StuID\" INTEGER, \n\t\"LName\" VARCHAR(12), \n\t\"Fname\" VARCHAR(12), \n\t\"Age\" INTEGER, \n\t\"Sex\" VARCHAR(1), \n\t\"Major\" INTEGER, \n\t\"Advisor\" INTEGER, \n\tcity_code VARCHAR(3), \n\tPRIMARY KEY (\"StuID\")\n)\n/*\nColumns in Student and 3 examples in each column for high cardinality columns :\nStuID : 1003, 1017, 1002\nLName : Lee, Han, Brody\nFname : Tracy, Michael, Shiela\nAdvisor : 7723, 7712, 7134\ncity_code : ATL, HOU, LON\n*/\n/*\nColumns in Student and all categories for low cardinality columns :\nAge : 26, 16, 20, 17, 21, 19, 18, 27, 22\nSex : F, M\nMajor : 520, 100, 50, 600, 540, 550\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Height\" REAL, \n\t\"Weight\" REAL, \n\t\"Date_of_Birth\" TEXT, \n\tPRIMARY KEY (\"People_ID\")\n)\n/*\nColumns in people and all categories for low cardinality columns :\nPeople_ID : 1, 2, 5, 7, 8, 4, 6, 3\nName : Fabrizio Buonocore, Goran Fiorentini, Francesco Postiglione, Alberto Angelini, Leonardo Binchi, Marco Gerini, Roberto Calcaterra, Maurizio Felugo\nHeight : 1.9, 1.86, 1.72, 1.75, 1.95, 1.78, 1.82, 1.83\nWeight : 45.0, 89.0, 67.0, 58.0, 57.0, 75.0, 76.0, 80.0\nDate_of_Birth : 1975-08-27, 1971-08-05, 1972-04-29, 1977-04-28, 1981-03-04, 1972-02-06, 1981-11-21, 1974-09-28\n*/\n \nCREATE TABLE employee (\n\teid NUMERIC(9, 0), \n\tname TEXT(30), \n\tsalary NUMERIC(10, 2), \n\tPRIMARY KEY (eid)\n)\n/*\nColumns in employee and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\nname : Dorthy Lewis, Jennifer Thomas, Eric Cooper\nsalary : 43001.00, 33546.00, 43723.00\n*/\n\n \nCREATE TABLE \"EMPLOYEE\" (\n\t\"EMP_NUM\" INTEGER, \n\t\"EMP_LNAME\" VARCHAR(15), \n\t\"EMP_FNAME\" VARCHAR(12), \n\t\"EMP_INITIAL\" VARCHAR(1), \n\t\"EMP_JOBCODE\" VARCHAR(5), \n\t\"EMP_HIREDATE\" DATETIME, \n\t\"EMP_DOB\" DATETIME, \n\tPRIMARY KEY (\"EMP_NUM\")\n) \nCREATE TABLE \"Tryout\" (\n\t\"pID\" NUMERIC(5, 0), \n\t\"cName\" VARCHAR(20), \n\t\"pPos\" VARCHAR(8), \n\tdecision VARCHAR(3), \n\tPRIMARY KEY (\"pID\", \"cName\"), \n\tFOREIGN KEY(\"pID\") REFERENCES \"Player\" (\"pID\"), \n\tFOREIGN KEY(\"cName\") REFERENCES \"College\" (\"cName\")\n)\n/*\nColumns in Tryout and all categories for low cardinality columns :\npID : 20002, 40004, 50005, 30003, 10001\ncName : FSU, OU, ASU, LSU\npPos : striker, goalie, mid\ndecision : yes, no\n*/\n \nCREATE TABLE results (\n\t\"resultId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\t\"constructorId\" INTEGER, \n\tnumber INTEGER, \n\tgrid INTEGER, \n\tposition TEXT, \n\t\"positionText\" TEXT, \n\t\"positionOrder\" INTEGER, \n\tpoints REAL, \n\tlaps TEXT, \n\ttime TEXT, \n\tmilliseconds TEXT, \n\t\"fastestLap\" TEXT, \n\trank TEXT, \n\t\"fastestLapTime\" TEXT, \n\t\"fastestLapSpeed\" TEXT, \n\t\"statusId\" INTEGER, \n\tPRIMARY KEY (\"resultId\"), \n\tFOREIGN KEY(\"constructorId\") REFERENCES constructors (\"constructorId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/*\nColumns in results and 3 examples in each column for high cardinality columns :\nresultId : 87, 56, 65\ndriverId : 17, 21, 9\nconstructorId : 1, 11, 2\nnumber : 17, 21, 9\ngrid : 17, 21, 9\nposition : , 19, 17\npositionText : 19, 17, 9\npositionOrder : 17, 21, 9\nlaps : 53, 56, 65\ntime : , 58.244, 45.832\nmilliseconds : , 5838976, 5855526\nfastestLap : , 53, 56\nrank : , 19, 17\nfastestLapTime : , 01:26.7, 01:20.7\nfastestLapSpeed : , 151.021, 118.872\nstatusId : 1, 20, 11\n*/\n/*\nColumns in results and all categories for low cardinality columns :\nraceId : 26, 20, 25, 24, 23, 21, 19, 18, 27, 22\npoints : 8.0, 3.0, 10.0, 1.0, 0.0, 6.0, 2.0, 4.0, 5.0\n*/\n \nCREATE TABLE furniture (\n\t\"Furniture_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Num_of_Component\" INTEGER, \n\t\"Market_Rate\" REAL, \n\tPRIMARY KEY (\"Furniture_ID\")\n)\n/*\nColumns in furniture and all categories for low cardinality columns :\nFurniture_ID : 1, 2, 5, 7, 4, 6, 3\nName : Dining set, Chabudai, Billiard table, Hatstand, Bookcase, Four-poster bed, Bench\nNum_of_Component : 5, 4, 6, 14, 3, 12\nMarket_Rate : 1.0, 3.5, 52.5, 0.5, 40.0, 2.0\n*/\n \nCREATE TABLE station (\n\tid INTEGER, \n\tnetwork_name TEXT, \n\tservices TEXT, \n\tlocal_authority TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in station and 3 examples in each column for high cardinality columns :\nid : 1, 11, 2\nnetwork_name : Chalfont & Latimer, Chorleywood, Brentwood\n*/\n/*\nColumns in station and all categories for low cardinality columns :\nservices : Greater Anglia, Metropolitan line and Chiltern Railways, Metropolitan line, c2c, London Overground and London Midland, London Overground\nlocal_authority : Three Rivers, Brentwood, Broxbourne, Thurrock, Watford, Chiltern\n*/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Membership_card\" TEXT, \n\t\"Age\" INTEGER, \n\t\"Time_of_purchase\" INTEGER, \n\t\"Level_of_membership\" INTEGER, \n\t\"Address\" TEXT, \n\tPRIMARY KEY (\"Member_ID\")\n)\n/*\nColumns in member and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Peeler, Russell, Rizzo, Todd, Campbell, Jessie, Breton, Robert, Komisarjevsky, Joshua, Webb, Daniel, Ashby, Lazale, Hayes, Steven, Reynolds, Richard, Cobb, Sedrick\nMembership_card : White, Black\nAge : 67, 45, 33, 50, 34, 42, 29, 51, 35\nTime_of_purchase : 26, 20, 44, 24, 18, 27, 41\nLevel_of_membership : 1, 2, 5, 4, 6, 3, 22\nAddress : Hartford, Bridgeport, Cheshire, Waterbury\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE actor (\n\t\"Actor_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Musical_ID\" INTEGER, \n\t\"Character\" TEXT, \n\t\"Duration\" TEXT, \n\tage INTEGER, \n\tPRIMARY KEY (\"Actor_ID\"), \n\tFOREIGN KEY(\"Musical_ID\") REFERENCES actor (\"Actor_ID\")\n)\n/*\nColumns in actor and all categories for low cardinality columns :\nActor_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Ray Meagher, Lynne McGranger, Ian Smith, Tom Oliver, Kate Ritchie, Ryan Moloney, Alan Fletcher, Stefan Dennis, Jackie Woodburne\nMusical_ID : 1, 2, 4, 6\nCharacter : Harold Bishop, Susan Kennedy, Karl Kennedy, Alf Stewart, Toadfish Rebecchi, Sally Fletcher, Paul Robinson, Lou Carpenter, Irene Roberts\nDuration : 1988—, 1985–1992, 1993, 2004—, 1993—, 1988, 1992—, 1995, 1996—, 1987–1991, 1996–2009, 2011, 1994—, 1988–2008, 2013\nage : 26, 20, 17, 21, 18, 22\n*/\n" }, { "role": "user", "content": "Show all company names with a movie directed in year 1999." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie, culture_company.\nFrom these tables, I'll be using the following columns: culture_company.company_name, movie.movie_id, culture_company.movie_id, movie.year.\nThe SQL query I'll be generating is:\nSELECT T2.company_name FROM movie AS T1 JOIN culture_company AS T2 ON T1.movie_id = T2.movie_id WHERE T1.year = 1999" } ]
[ { "role": "system", "content": "\nYou are an assistant that is an expert in generating sqlite SQL queries.\nHaving the access to database content, generate a correct sqlite SQL query for the given question.\n### Database content ###\n \nCREATE TABLE airports (\n\tapid INTEGER, \n\tname TEXT NOT NULL, \n\tcity TEXT, \n\tcountry TEXT, \n\tx REAL, \n\ty REAL, \n\televation BIGINT, \n\tiata TEXT(3), \n\ticao TEXT(4), \n\tPRIMARY KEY (apid)\n)\n/*\nColumns in airports and 3 examples in each column for high cardinality columns :\napid : 87, 56, 65\nname : Rouyn Noranda Airport, Edmonton International Airport, Val-d'Or Airport\ncity : Medicine Hat, Sarnia, Fort Saint John\nx : -117.4469985961914, -122.054000854, -135.067001343\ny : 45.5175018311, 50.29029846191406, 47.697400654599996\nelevation : 87, 586, 56\niata : NULL, YYE, YXJ\nicao : CYXD, CYBK, CYMO\n*/\n/*\nColumns in airports and all categories for low cardinality columns :\ncountry : Iceland, Papua New Guinea, Greenland, Canada\n*/\n \nCREATE TABLE \"Reservations\" (\n\t\"Code\" INTEGER, \n\t\"Room\" TEXT, \n\t\"CheckIn\" TEXT, \n\t\"CheckOut\" TEXT, \n\t\"Rate\" REAL, \n\t\"LastName\" TEXT, \n\t\"FirstName\" TEXT, \n\t\"Adults\" INTEGER, \n\t\"Kids\" INTEGER, \n\tPRIMARY KEY (\"Code\"), \n\tFOREIGN KEY(\"Room\") REFERENCES \"Rooms\" (\"RoomId\")\n)\n/*\nColumns in Reservations and 3 examples in each column for high cardinality columns :\nCode : 38017, 23850, 20991\nCheckIn : 25-SEP-10, 14-DEC-10, 15-JUN-10\nCheckOut : 19-JAN-10, 09-MAY-10, 06-MAY-10\nRate : 287.5, 115.0, 218.75\nLastName : ESPINO, ECKERT, NORSWORTHY\nFirstName : JEFFEREY, ALLEN, ELVINA\n*/\n/*\nColumns in Reservations and all categories for low cardinality columns :\nRoom : IBD, IBS, RTE, CAS, FNA, HBB, AOB, MWC, TAA, RND\nAdults : 1, 2, 4, 3\nKids : 1, 2, 3, 0\n*/\n \nCREATE TABLE school (\n\t\"School_ID\" INTEGER, \n\t\"Grade\" TEXT, \n\t\"School\" TEXT, \n\t\"Location\" TEXT, \n\t\"Type\" TEXT, \n\tPRIMARY KEY (\"School_ID\")\n)\n/*\nColumns in school and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 7, 4, 6, 3\nGrade : Freshman–Sophomore year, 1st-3rd grade, Kindergarten, Junior–Senior year, College, 5th-12th grade, 4th grade\nSchool : Occidental College, Noelani Elementary School, Harvard Law School, Columbia University, Punahou School, St. Francis Assisi, State Elementary School Menteng 01\nLocation : Cambridge, Massachusetts, Honolulu, Hawaii, Jakarta, Indonesia, Los Angeles, California, New York City\nType : Public, Private Catholic, Private\n*/\n \nCREATE TABLE routes (\n\trid INTEGER, \n\tdst_apid INTEGER, \n\tdst_ap VARCHAR(4), \n\tsrc_apid BIGINT, \n\tsrc_ap VARCHAR(4), \n\talid BIGINT, \n\tairline VARCHAR(4), \n\tcodeshare TEXT, \n\tPRIMARY KEY (rid), \n\tFOREIGN KEY(dst_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(src_apid) REFERENCES airports (apid), \n\tFOREIGN KEY(alid) REFERENCES airlines (alid)\n)\n/*\nColumns in routes and 3 examples in each column for high cardinality columns :\nrid : 87, 56, 65\ndst_apid : 7165, 8076, 1044\ndst_ap : SYB, JKG, IKT\nsrc_apid : 8076, 1044, 2990\nsrc_ap : SYB, JKG, IKT\n*/\n/*\nColumns in routes and all categories for low cardinality columns :\nalid : 146, 8359, 470, 1338, 410, 3652, 897, 1654, 2750\nairline : 2G, 2P, 2, 2J, 2O, 2I, 2B, 2K\ncodeshare : None, Y\n*/\n \nCREATE TABLE takes (\n\t\"ID\" VARCHAR(5), \n\tcourse_id VARCHAR(8), \n\tsec_id VARCHAR(8), \n\tsemester VARCHAR(6), \n\tyear NUMERIC(4, 0), \n\tgrade VARCHAR(2), \n\tPRIMARY KEY (\"ID\", course_id, sec_id, semester, year), \n\tFOREIGN KEY(course_id, sec_id, semester, year) REFERENCES section (course_id, sec_id, semester, year), \n\tFOREIGN KEY(\"ID\") REFERENCES student (\"ID\")\n)\n/*\nColumns in takes and 3 examples in each column for high cardinality columns :\nID : 99189, 44706, 56058\ncourse_id : 843, 400, 349\n*/\n/*\nColumns in takes and all categories for low cardinality columns :\nsec_id : 1, 2, 3\nsemester : Fall, Spring\nyear : 2004, 2009, 2001, 2005, 2008, 2006, 2003, 2002, 2010, 2007\ngrade : B-, B , C , B+, A , A-, C-, C+, A+\n*/\n \nCREATE TABLE \"Web_client_accelerator\" (\n\tid INTEGER, \n\tname TEXT, \n\t\"Operating_system\" TEXT, \n\t\"Client\" TEXT, \n\t\"Connection\" TEXT, \n\tPRIMARY KEY (id)\n)\n/*\nColumns in Web_client_accelerator and 3 examples in each column for high cardinality columns :\nid : 17, 9, 16\nname : Freewire, Toonel, Fasterfox\nOperating_system : Unix (Linux, *BSD, Mac OS X, others), Windows, Windows, Mac and Mobile devices, Windows, Mac, Mobile devices\n*/\n/*\nColumns in Web_client_accelerator and all categories for low cardinality columns :\nClient : End User, ISP, End user, ISP, user/Google server, user/Opera server, user/ISP, ISP, All, user\nConnection : up to 756kbit/s, Broadband, Any, Broadband, Satellite, Wireless, Fiber, DSL, Dial, DSL, ISDN, Satellite, wireless, Dial-up, Broadband, DSL, ISDN, Satellite, Wireless, Dialup, Wireless, Broadband, DSL, Dial-up\n*/\n \nCREATE TABLE school_bus (\n\t\"School_ID\" INTEGER, \n\t\"Driver_ID\" INTEGER, \n\t\"Years_Working\" INTEGER, \n\t\"If_full_time\" BOOLEAN, \n\tPRIMARY KEY (\"School_ID\", \"Driver_ID\"), \n\tFOREIGN KEY(\"Driver_ID\") REFERENCES driver (\"Driver_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/*\nColumns in school_bus and all categories for low cardinality columns :\nSchool_ID : 1, 5, 7, 4, 3\nDriver_ID : 7, 4, 3, 10, 9\nYears_Working : 2, 8, 6, 3, 10\nIf_full_time : True\n*/\n \nCREATE TABLE culture_company (\n\t\"Company_name\" TEXT, \n\t\"Type\" TEXT, \n\t\"Incorporated_in\" TEXT, \n\t\"Group_Equity_Shareholding\" REAL, \n\tbook_club_id TEXT, \n\tmovie_id TEXT, \n\tPRIMARY KEY (\"Company_name\"), \n\tFOREIGN KEY(book_club_id) REFERENCES book_club (book_club_id), \n\tFOREIGN KEY(movie_id) REFERENCES movie (movie_id)\n)\n/*\nColumns in culture_company and all categories for low cardinality columns :\nCompany_name : Cathay Pacific Culture, Culture China Cargo, Culture Hong Kong, Cathay Pacific Culture Services (HK) Limited, Culture China, Dragonair\nType : Joint Venture, Subsidiary, Corporate\nIncorporated_in : Hong Kong, China\nGroup_Equity_Shareholding : 49.0, 60.0, 18.77, 100.0\nbook_club_id : 1, 2, 5, 6, 3\nmovie_id : 2, 5, 7, 4, 6, 3\n*/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_first_name VARCHAR(20), \n\tcustomer_last_name VARCHAR(20), \n\tcustomer_address VARCHAR(255), \n\tcustomer_phone VARCHAR(255), \n\tcustomer_email VARCHAR(255), \n\tother_customer_details VARCHAR(255), \n\tPRIMARY KEY (customer_id)\n)\n/*\nColumns in Customers and 3 examples in each column for high cardinality columns :\ncustomer_id : 1, 13, 11\ncustomer_first_name : Armani, Bryce, Nat\ncustomer_last_name : Swift, Lind, Huels\ncustomer_address : 6478 Moen Isle Suite 910\nSchimmelmouth, VT 96364-4898, 47286 Mraz Park Apt. 424\nJocelynfurt, OH 59023-2787, 094 Julianne Mill\nWebstertown, KY 91980-4004\ncustomer_phone : (415)237-0701x3115, 679-845-8645x94312, 284.749.0453\ncustomer_email : kyra.murazik@example.org, schaden.katrina@example.net, huels.antonina@example.com\n*/\n/*\nColumns in Customers and all categories for low cardinality columns :\nother_customer_details : None\n*/\n \nCREATE TABLE book_club (\n\tbook_club_id INTEGER, \n\t\"Year\" INTEGER, \n\t\"Author_or_Editor\" TEXT, \n\t\"Book_Title\" TEXT, \n\t\"Publisher\" TEXT, \n\t\"Category\" TEXT, \n\t\"Result\" TEXT, \n\tPRIMARY KEY (book_club_id)\n)\n/*\nColumns in book_club and 3 examples in each column for high cardinality columns :\nbook_club_id : 1, 11, 2\nAuthor_or_Editor : Dolores Klaich, Antoinette Azolakov, Sandy Bayer\nBook_Title : Lessons In Murder, Somewhere in the Night, Mundaneӳ World\n*/\n/*\nColumns in book_club and all categories for low cardinality columns :\nYear : 1989, 1990\nPublisher : International Polygonics, William Morrow, St. Martin's Press, Crossing Press, Alyson, Naiad Press, Banned Books, Mysterious Press\nCategory : Lesb. M/SF, Gay SF/F, Gay M/SF\nResult : Nom, Won [B ], Won, Won [A ]\n*/\n \nCREATE TABLE film (\n\t\"Film_ID\" INTEGER, \n\t\"Title\" TEXT, \n\t\"Studio\" TEXT, \n\t\"Director\" TEXT, \n\t\"Gross_in_dollar\" INTEGER, \n\tPRIMARY KEY (\"Film_ID\")\n)\n/*\nColumns in film and 3 examples in each column for high cardinality columns :\nFilm_ID : 1, 13, 11\nTitle : Annie, Rocky III, Tootsie\nDirector : Richard Attenborough, Nicholas Meyer, Ted Kotcheff\nGross_in_dollar : 53977250, 76606280, 125049125\n*/\n/*\nColumns in film and all categories for low cardinality columns :\nStudio : MGM, United Artists, Universal, 20th Century Fox, Columbia, Paramount, Columbia / Rastar, Paramount / Lorimar, Orion / Carolco, Universal / RKO\n*/\n \nCREATE TABLE channel (\n\t\"Channel_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Owner\" TEXT, \n\t\"Share_in_percent\" REAL, \n\t\"Rating_in_percent\" REAL, \n\tPRIMARY KEY (\"Channel_ID\")\n)\n/*\nColumns in channel and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nName : Shandong Satellite TV, CCTV-8, Hunan Satellite TV, CCTV-3, CCTV-14, CCTV-6, CCTV-13, CCTV-1, Anhui Satellite TV, CCTV-4\nOwner : HBS, Shandong Television, CCTV, Anhui Television\nShare_in_percent : 4.9, 2.33, 1.74, 2.91, 4.81, 2.6, 2.86, 3.76, 1.78, 2.73\nRating_in_percent : 0.53, 0.41, 0.32, 0.19, 0.54, 0.3, 0.31, 0.2, 0.29, 0.26\n*/\n \nCREATE TABLE movie (\n\tmovie_id INTEGER, \n\t\"Title\" TEXT, \n\t\"Year\" INTEGER, \n\t\"Director\" TEXT, \n\t\"Budget_million\" REAL, \n\t\"Gross_worldwide\" INTEGER, \n\tPRIMARY KEY (movie_id)\n)\n/*\nColumns in movie and all categories for low cardinality columns :\nmovie_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nTitle : Agent Red, The Whole Nine Yards, Storm Catcher, 3000 Miles to Graceland, The Art of War, The Boondock Saints, Jill Rips, The Big Kahuna, Get Carter, Battlefield Earth\nYear : 2001, 1999, 2000\nDirector : Roger Christian, John Swanbeck, Stephen Kay, Christian Duguay, Jonathan Lynn, Troy Duffy, Anthony Hickox, Demian Lichtenstein, Damian Lee\nBudget_million : 63.6, 47.0, 60.0, 41.3, 44.0, 7.0, 62.0, 6.0, 4.0, 5.0\nGross_worldwide : 106371651, 456774, 40400425, 30471, 40500, 543356, 19412993, 29725663, 3728888, 18720175\n*/\n \nCREATE TABLE stock (\n\t\"Shop_ID\" INTEGER, \n\t\"Device_ID\" INTEGER, \n\t\"Quantity\" INTEGER, \n\tPRIMARY KEY (\"Shop_ID\", \"Device_ID\"), \n\tFOREIGN KEY(\"Device_ID\") REFERENCES device (\"Device_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES shop (\"Shop_ID\")\n)\n/*\nColumns in stock and all categories for low cardinality columns :\nShop_ID : 1, 11, 2, 4, 3, 9\nDevice_ID : 4, 6\nQuantity : 110, 56, 124, 100, 200, 112, 134, 51\n*/\n" }, { "role": "user", "content": "What are all company names that have a corresponding movie directed in the year 1999?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: movie, culture_company.\nFrom these tables, I'll be using the following columns: culture_company.company_name, movie.movie_id, culture_company.movie_id, movie.year.\nThe SQL query I'll be generating is:\nSELECT T2.company_name FROM movie AS T1 JOIN culture_company AS T2 ON T1.movie_id = T2.movie_id WHERE T1.year = 1999" } ]