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MrezaPRZ
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GPT-fine-tuning-spider

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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 department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\n/\n \nCREATE TABLE \"Vehicles\" (\n\tvehicle_id INTEGER, \n\tvehicle_details VARCHAR(255), \n\tPRIMARY KEY (vehicle_id)\n)\n/\nColumns in Vehicles and all categories for low cardinality columns :\nvehicle_id : 1, 2, 3\nvehicle_details : Car, Van, Truck\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 \"Scientists\" (\n\t\"SSN\" INTEGER, \n\t\"Name\" CHAR(30) NOT NULL, \n\tPRIMARY KEY (\"SSN\")\n)\n/\nColumns in Scientists and 3 examples in each column for high cardinality columns :\nSSN : 546523478, 332569843, 845657246\nName : Kumar Swamy, John Doe, David Smith\n/\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 \"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 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 \"Departments\" (\n\tdepartment_id INTEGER, \n\tdept_store_id INTEGER NOT NULL, \n\tdepartment_name VARCHAR(80), \n\tPRIMARY KEY (department_id), \n\tFOREIGN KEY(dept_store_id) REFERENCES \"Department_Stores\" (dept_store_id)\n)\n/\nColumns in Departments and all categories for low cardinality columns :\ndepartment_id : 1, 2, 5, 4, 3\ndept_store_id : 11, 4, 5\ndepartment_name : human resource, managing, marketing, purchasing, advertising\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 repair (\n\t\"repair_ID\" INTEGER, \n\tname TEXT, \n\t\"Launch_Date\" TEXT, \n\t\"Notes\" TEXT, \n\tPRIMARY KEY (\"repair_ID\")\n)\n/\nColumns in repair and all categories for low cardinality columns :\nrepair_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nname : OPS 3042, OPS 3491, OPS 3360, OPS 3754, OPS 3467, Discoverer 3, Discoverer 1, OPS 3236, Discoverer\nLaunch_Date : 10 Jun 2014, 13 Jun 2014, 05 Aug 2014, 28 Feb 2009, 24 Mar 2014, 21 Jan 2009, 18 Nov 2014, 19 Jun 2014, 03 Jun 2009\nNotes : Out-of-focus area on some film., repair failed. Guidance system failed. No orbit., repair Failed. Failed to achieve orbit, First object in polar orbit, repair failed. Failed to achieve orbit, Cameras operated successfully., Cameras operated satisfactorily\n/\n \nCREATE TABLE people (\n\t\"People_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Age\" INTEGER, \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\nDistrict : New York 7, New York 1, New York 8, New York 4, New York 3, New York 9, New York 6, New York 2, New York 5, New York 10\nName : Daniel Sickles, George Briggs, James Humphrey, Luther C. Carter, John B. Haskin, William B. Maclay, John Cochrane, Charles Van Wyck, Thomas J. Barr, Horace F. Clark\nParty : Anti-Lecompton Democrat, Democratic, Independent Democrat, Republican\nAge : 38, 46, 45, 48, 43, 36, 42, 35\n/\n \nCREATE TABLE \"Problem_Category_Codes\" (\n\tproblem_category_code VARCHAR(20), \n\tproblem_category_description VARCHAR(80), \n\tPRIMARY KEY (problem_category_code)\n)\n/\nColumns in Problem_Category_Codes and all categories for low cardinality columns :\nproblem_category_code : Datatabase, Middleware, GUI\nproblem_category_description : User Interface., Infrastructrure and Architecture, Database design or contents.\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 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 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 \"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 \"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 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 \"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 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 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 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 the numbers of the shortest flights?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: flno, distance.\nThe SQL query I'll be generating is:\nSELECT flno FROM Flight ORDER BY distance ASC LIMIT 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"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_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\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 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 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 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 \"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 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 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 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 \"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 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 \"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 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 \"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 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 \"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" }, { "role": "user", "content": "What is the average distance and average price for flights from Los Angeles." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: distance, price, origin, Los Angeles.\nThe SQL query I'll be generating is:\nSELECT avg(distance) , avg(price) FROM Flight WHERE origin = \"Los Angeles\"" } ]
[ { "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 \"match\" (\n\t\"Match_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Score\" TEXT, \n\t\"Result\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (\"Match_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nMatch_ID : 1, 2, 5, 4, 6, 3\nDate : 23 July 1992, 18 February 1992, 19 July 1992, 23 July 2000, 4 April 1993\nVenue : Estadio Rigoberto López , Managua , Nicaragua, Estadio Cuscatlán , San Salvador , El Salvador\nScore : 3-0, 2–1, 1-0, 1–0\nResult : 5-1, 7–1, 5-0, 2–1, 2-0\nCompetition : 1994 FIFA World Cup qualification, Friendly match, 2002 FIFA World Cup qualification\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 \"Documents_Mailed\" (\n\tdocument_id INTEGER NOT NULL, \n\tmailed_to_address_id INTEGER NOT NULL, \n\tmailing_date DATETIME, \n\tPRIMARY KEY (document_id, mailed_to_address_id), \n\tFOREIGN KEY(document_id) REFERENCES \"Documents\" (document_id), \n\tFOREIGN KEY(mailed_to_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Documents_Mailed and 3 examples in each column for high cardinality columns :\nmailing_date : 2007-01-01 22:32:11, 2007-03-20 05:22:01, 1992-11-07 15:03:41\n/\n/\nColumns in Documents_Mailed and all categories for low cardinality columns :\ndocument_id : 13, 20, 2, 7, 24, 23, 4, 12, 14, 10\nmailed_to_address_id : 2, 5, 7, 8, 4, 3, 9, 0\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE pilot (\n\t\"Pilot_Id\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(50) NOT NULL, \n\t\"Age\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Pilot_Id\")\n)\n/\nColumns in pilot and 3 examples in each column for high cardinality columns :\nPilot_Id : 1, 11, 2\nName : Winnifred Boyle, Mr. Cristian Halvorson II, Katheryn Gorczany IV\n/\n/\nColumns in pilot and all categories for low cardinality columns :\nAge : 26, 37, 20, 25, 33, 30, 23, 29, 31\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 employee (\n\t\"Fname\" TEXT, \n\t\"Minit\" TEXT, \n\t\"Lname\" TEXT, \n\t\"Ssn\" INTEGER, \n\t\"Bdate\" TEXT, \n\t\"Address\" TEXT, \n\t\"Sex\" TEXT, \n\t\"Salary\" INTEGER, \n\t\"Super_ssn\" INTEGER, \n\t\"Dno\" INTEGER, \n\tPRIMARY KEY (\"Ssn\")\n)\n/\nColumns in employee and all categories for low cardinality columns :\nFname : Joyce, James, Alicia, Ramesh, Franklin, Ahmad, Jonh, Jennifier\nMinit : E, S, K, J, T, A, V, B\nLname : Borg, Narayan, Smith, English, Zelaya, Jabbar, Wallace, Wong\nSsn : 987987987, 333445555, 453453453, 987654321, 123456789, 999887777, 888665555, 666884444\nBdate : 1969-03-29, 1965-01-09, 1955-12-08, 1968-01-19, 1937-11-10, 1972-07-31, 1962-09-15, 1941-06-20\nAddress : 980 Dallas, Houston, TX, 291 Berry, Bellaire, TX, 975 Fire Oak, Humble, TX, 3321 Castle, Spring, TX, 5631 Rice, Houston, TX, 638 Voss, Houston, TX, 450 Stone, Houston, TX, 731 Fondren, Houston, TX\nSex : F, M\nSalary : 43000, 40000, 38000, 25000, 55000, 30000\nSuper_ssn : 333445555, 888665555, 987654321, None\nDno : 1, 4, 5\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 \"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 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 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 player_coach (\n\t\"Player_ID\" INTEGER, \n\t\"Coach_ID\" INTEGER, \n\t\"Starting_year\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\", \"Coach_ID\"), \n\tFOREIGN KEY(\"Coach_ID\") REFERENCES coach (\"Coach_ID\"), \n\tFOREIGN KEY(\"Player_ID\") REFERENCES player (\"Player_ID\")\n)\n/\nColumns in player_coach and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 4, 6, 14, 3, 10\nCoach_ID : 1, 2, 5, 3\nStarting_year : 2012, 2010, 2011, 2013\n/\n \nCREATE TABLE repair (\n\t\"repair_ID\" INTEGER, \n\tname TEXT, \n\t\"Launch_Date\" TEXT, \n\t\"Notes\" TEXT, \n\tPRIMARY KEY (\"repair_ID\")\n)\n/\nColumns in repair and all categories for low cardinality columns :\nrepair_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nname : OPS 3042, OPS 3491, OPS 3360, OPS 3754, OPS 3467, Discoverer 3, Discoverer 1, OPS 3236, Discoverer\nLaunch_Date : 10 Jun 2014, 13 Jun 2014, 05 Aug 2014, 28 Feb 2009, 24 Mar 2014, 21 Jan 2009, 18 Nov 2014, 19 Jun 2014, 03 Jun 2009\nNotes : Out-of-focus area on some film., repair failed. Guidance system failed. No orbit., repair Failed. Failed to achieve orbit, First object in polar orbit, repair failed. Failed to achieve orbit, Cameras operated successfully., Cameras operated satisfactorily\n/\n \nCREATE TABLE captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\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 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 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 \"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 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" }, { "role": "user", "content": "What is the average distance and price for all flights from LA?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: distance, price, origin, Los Angeles.\nThe SQL query I'll be generating is:\nSELECT avg(distance) , avg(price) FROM Flight WHERE origin = \"Los Angeles\"" } ]
[ { "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 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 \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 \"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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\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 \"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 \"Customer\" (\n\t\"CustomerId\" INTEGER NOT NULL, \n\t\"FirstName\" VARCHAR(40) NOT NULL, \n\t\"LastName\" VARCHAR(20) NOT NULL, \n\t\"Company\" VARCHAR(80) DEFAULT NULL, \n\t\"Address\" VARCHAR(70) DEFAULT NULL, \n\t\"City\" VARCHAR(40) DEFAULT NULL, \n\t\"State\" VARCHAR(40) DEFAULT NULL, \n\t\"Country\" VARCHAR(40) DEFAULT NULL, \n\t\"PostalCode\" VARCHAR(10) DEFAULT NULL, \n\t\"Phone\" VARCHAR(24) DEFAULT NULL, \n\t\"Fax\" VARCHAR(24) DEFAULT NULL, \n\t\"Email\" VARCHAR(60) NOT NULL, \n\t\"SupportRepId\" INTEGER DEFAULT NULL, \n\tPRIMARY KEY (\"CustomerId\"), \n\tFOREIGN KEY(\"SupportRepId\") REFERENCES \"Employee\" (\"EmployeeId\")\n)\n/\nColumns in Customer and 3 examples in each column for high cardinality columns :\nCustomerId : 53, 56, 49\nFirstName : Astrid, Emma, Fynn\nLastName : Sullivan, Schneider, Mercier\nCompany : Apple Inc., Microsoft Corporation, Rogers Canada\nAddress : 696 Osborne Street, 796 Dundas Street West, Grétrystraat 63\nCity : Oslo, Lisbon, Mountain View\nState : AZ, NSW, Dublin\nCountry : Sweden, Australia, India\nPostalCode : 85719, B3S 1C5, 1106\nPhone : +1 (801) 531-7272, +49 030 26550280, +33 05 56 96 96 96\nFax : +1 (212) 221-4679, +55 (12) 3923-5566, +1 (650) 253-0000\nEmail : mphilips12@shaw.ca, luisg@embraer.com.br, marc.dubois@hotmail.com\n/\n/\nColumns in Customer and all categories for low cardinality columns :\nSupportRepId : 4, 5, 3\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 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 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 \"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 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 \"Timed_Locations_of_Things\" (\n\tthing_id INTEGER NOT NULL, \n\t\"Date_and_Time\" DATETIME NOT NULL, \n\t\"Location_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (thing_id, \"Date_and_Time\", \"Location_Code\"), \n\tFOREIGN KEY(thing_id) REFERENCES \"Things\" (thing_id)\n)\n/\nColumns in Timed_Locations_of_Things and 3 examples in each column for high cardinality columns :\nDate_and_Time : 2017-03-19 13:57:49, 2017-08-31 13:54:13, 2016-12-29 00:39:19\nLocation_Code : 2677 Runolfsson, 288 Lang Ferry, 94425 Nellie Kn\n/\n/\nColumns in Timed_Locations_of_Things and all categories for low cardinality columns :\nthing_id : 26, 45, 2, 68, 58, 92, 14, 85, 10\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\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": "Show all origins and the number of flights from each origin." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: origin.\nThe SQL query I'll be generating is:\nSELECT origin , count(*) FROM Flight GROUP BY origin" } ]
[ { "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 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 \"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 repair (\n\t\"repair_ID\" INTEGER, \n\tname TEXT, \n\t\"Launch_Date\" TEXT, \n\t\"Notes\" TEXT, \n\tPRIMARY KEY (\"repair_ID\")\n)\n/\nColumns in repair and all categories for low cardinality columns :\nrepair_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nname : OPS 3042, OPS 3491, OPS 3360, OPS 3754, OPS 3467, Discoverer 3, Discoverer 1, OPS 3236, Discoverer\nLaunch_Date : 10 Jun 2014, 13 Jun 2014, 05 Aug 2014, 28 Feb 2009, 24 Mar 2014, 21 Jan 2009, 18 Nov 2014, 19 Jun 2014, 03 Jun 2009\nNotes : Out-of-focus area on some film., repair failed. Guidance system failed. No orbit., repair Failed. Failed to achieve orbit, First object in polar orbit, repair failed. Failed to achieve orbit, Cameras operated successfully., Cameras operated satisfactorily\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 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 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 \"Asset_Parts\" (\n\tasset_id INTEGER NOT NULL, \n\tpart_id INTEGER NOT NULL, \n\tFOREIGN KEY(asset_id) REFERENCES \"Assets\" (asset_id), \n\tFOREIGN KEY(part_id) REFERENCES \"Parts\" (part_id)\n)\n/\nColumns in Asset_Parts and all categories for low cardinality columns :\nasset_id : 1, 2, 5, 15, 4, 6, 14, 3, 10\npart_id : 1, 2, 3\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"Student_Course_Enrolment\" (\n\tregistration_id INTEGER, \n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_enrolment DATETIME NOT NULL, \n\tdate_of_completion DATETIME NOT NULL, \n\tPRIMARY KEY (registration_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_Enrolment and 3 examples in each column for high cardinality columns :\nregistration_id : 17, 9, 16\nstudent_id : 3, 13, 11\ndate_of_enrolment : 2017-12-16 15:53:06, 2017-10-10 10:05:03, 2017-12-07 02:21:13\ndate_of_completion : 2018-03-01 07:12:39, 2018-03-22 18:04:54, 2018-03-07 09:45:48\n/\n/\nColumns in Student_Course_Enrolment and all categories for low cardinality columns :\ncourse_id : 1, 11, 2, 15, 7, 8, 4, 14, 10, 9\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 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 \"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 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 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 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 \"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 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 player_coach (\n\t\"Player_ID\" INTEGER, \n\t\"Coach_ID\" INTEGER, \n\t\"Starting_year\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\", \"Coach_ID\"), \n\tFOREIGN KEY(\"Coach_ID\") REFERENCES coach (\"Coach_ID\"), \n\tFOREIGN KEY(\"Player_ID\") REFERENCES player (\"Player_ID\")\n)\n/\nColumns in player_coach and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 4, 6, 14, 3, 10\nCoach_ID : 1, 2, 5, 3\nStarting_year : 2012, 2010, 2011, 2013\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 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 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 \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" }, { "role": "user", "content": "For each origin, how many flights came from there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: origin.\nThe SQL query I'll be generating is:\nSELECT origin , count(*) FROM Flight GROUP BY origin" } ]
[ { "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 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 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 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 \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 mountain (\n\tid INTEGER, \n\tname TEXT, \n\t\"Height\" REAL, \n\t\"Prominence\" REAL, \n\t\"Range\" TEXT, \n\t\"Country\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in mountain and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Kaka / Kecha / Chiqe, Aksouâl, Ioll / Yoll\nHeight : 4167.0, 4120.0, 4071.0\nProminence : 1540.0, 3931.0, 610.0\nRange : Toubkal Atlas, Aberdare Range, Semien Mountains\n/\n/\nColumns in mountain and all categories for low cardinality columns :\nCountry : Cameroon, Morocco, Kenya, Rwanda Uganda, Ethiopia\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 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 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 \"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 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 \"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 \"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 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 \"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 \"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 \"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 \"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 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 \"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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n" }, { "role": "user", "content": "Show all destinations and the number of flights to each destination." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: destination.\nThe SQL query I'll be generating is:\nSELECT destination , count(*) FROM Flight GROUP BY destination" } ]
[ { "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 \"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 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 customer (\n\tcustomer_id INTEGER NOT NULL, \n\tstore_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(45) NOT NULL, \n\tlast_name VARCHAR(45) NOT NULL, \n\temail VARCHAR(50) DEFAULT NULL, \n\taddress_id INTEGER NOT NULL, \n\tactive BOOLEAN DEFAULT TRUE NOT NULL, \n\tcreate_date DATETIME NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP, \n\tPRIMARY KEY (customer_id), \n\tFOREIGN KEY(address_id) REFERENCES address (address_id), \n\tFOREIGN KEY(store_id) REFERENCES store (store_id)\n)\n/\nColumns in customer and 3 examples in each column for high cardinality columns :\ncustomer_id : 87, 56, 65\nfirst_name : JUNE, KIM, BERTHA\nlast_name : ALLEN, SANDERS, WOODS\nemail : MEGAN.PALMER@sakilacustomer.org, PHYLLIS.FOSTER@sakilacustomer.org, ELEANOR.HUNT@sakilacustomer.org\naddress_id : 87, 56, 65\n/\n/\nColumns in customer and all categories for low cardinality columns :\nstore_id : 1, 2\nactive : False, True\ncreate_date : 2006-02-14 22:04:36\nlast_update : 2006-02-15 04:57:20\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 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 \"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 \"Shops\" (\n\t\"Shop_ID\" INTEGER NOT NULL, \n\t\"Shop_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Shop_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Shops and all categories for low cardinality columns :\nShop_ID : 8429, 9360, 8449, 8698\nShop_Details : soup, coffee, see food, Flower\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 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 captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\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 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 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 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 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 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 \"Party_Addresses\" (\n\tparty_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_address_from DATETIME NOT NULL, \n\taddress_type_code VARCHAR(15) NOT NULL, \n\tdate_address_to DATETIME, \n\tPRIMARY KEY (party_id, address_id), \n\tFOREIGN KEY(party_id) REFERENCES \"Parties\" (party_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Party_Addresses and 3 examples in each column for high cardinality columns :\ndate_address_from : 2016-11-02 02:06:07, 2016-04-15 03:54:06, 2016-06-09 00:48:07\ndate_address_to : 2018-02-09 08:47:26, 2018-02-27 09:21:41, 2018-03-07 13:28:44\n/\n/\nColumns in Party_Addresses and all categories for low cardinality columns :\nparty_id : 11, 5, 15, 8, 4, 6, 3, 10\naddress_id : 1, 13, 2, 5, 7, 8, 4, 10, 9\naddress_type_code : Billing, Residence, Delivery\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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n" }, { "role": "user", "content": "What are the destinations and number of flights to each one?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: destination.\nThe SQL query I'll be generating is:\nSELECT destination , count(*) FROM Flight GROUP BY destination" } ]
[ { "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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Songs\" (\n\t\"SongId\" INTEGER, \n\t\"Title\" TEXT, \n\tPRIMARY KEY (\"SongId\")\n)\n/\nColumns in Songs and all categories for low cardinality columns :\nSongId : \nTitle : \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 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 \"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 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 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 \"Parties\" (\n\tparty_id INTEGER, \n\tpayment_method_code VARCHAR(15) NOT NULL, \n\tparty_phone VARCHAR(80), \n\tparty_email VARCHAR(80), \n\tPRIMARY KEY (party_id)\n)\n/\nColumns in Parties and 3 examples in each column for high cardinality columns :\nparty_id : 1, 13, 11\nparty_phone : 1-525-947-7867x51521, 05374656172, 1-386-339-9244\nparty_email : hilll.elyssa@example.net, evie97@example.org, brakus.aliya@example.com\n/\n/\nColumns in Parties and all categories for low cardinality columns :\npayment_method_code : Cheque, Direct Debit, Credit Card, Cash\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 party_events (\n\t\"Event_ID\" INTEGER, \n\t\"Event_Name\" TEXT, \n\t\"Party_ID\" INTEGER, \n\t\"Member_in_charge_ID\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Member_in_charge_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in party_events and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 7, 8, 4, 6, 3\nEvent_Name : Election Meeting, Annaual Meeting, Conference, Budget Meeting\nParty_ID : 1, 2, 3\nMember_in_charge_ID : 11, 2, 15, 4, 12, 3, 10\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 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 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 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 \"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 \"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 \"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 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 department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\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" }, { "role": "user", "content": "Which origin has most number of flights?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: origin.\nThe SQL query I'll be generating is:\nSELECT origin FROM Flight GROUP BY origin 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 \"Shops\" (\n\t\"Shop_ID\" INTEGER NOT NULL, \n\t\"Shop_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Shop_ID\"), \n\tFOREIGN KEY(\"Shop_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Shops and all categories for low cardinality columns :\nShop_ID : 8429, 9360, 8449, 8698\nShop_Details : soup, coffee, see food, Flower\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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status_code VARCHAR(15) NOT NULL, \n\tshipping_method_code VARCHAR(15) NOT NULL, \n\torder_placed_datetime DATETIME NOT NULL, \n\torder_delivered_datetime DATETIME, \n\torder_shipping_charges 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_placed_datetime : 2009-01-18 20:06:19, 2008-10-23 06:42:10, 2009-07-05 20:02:55\norder_shipping_charges : 33.58, 77.32, 36.87\n/\n/\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 1, 2, 5, 7, 8, 14, 12, 15, 9\norder_status_code : Paid, Delivered, Cancelled\nshipping_method_code : FedEx, UPS, Unspecified\norder_delivered_datetime : 2018-03-20 12:00:00\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 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 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 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 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 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 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 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 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 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 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 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 \"Product_Categories\" (\n\tproduction_type_code VARCHAR(15), \n\tproduct_type_description VARCHAR(80), \n\tvat_rating DECIMAL(19, 4), \n\tPRIMARY KEY (production_type_code)\n)\n/\nColumns in Product_Categories and all categories for low cardinality columns :\nproduction_type_code : Food, Books, DVDs, Electronics\nproduct_type_description : Food, Books, Dvd products, Electrical devices\nvat_rating : 15.8400, 11.4000, 13.9500, 17.9000\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 place has the most flights coming from there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: origin.\nThe SQL query I'll be generating is:\nSELECT origin FROM Flight GROUP BY origin 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 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 \"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 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 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 news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER NOT NULL, \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 : 79, 87, 16\ncustomer_details : Esteban Senger, Elva Boehm, Mr. Raul Prosacco\n/\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 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 people (\n\t\"People_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Age\" INTEGER, \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\nDistrict : New York 7, New York 1, New York 8, New York 4, New York 3, New York 9, New York 6, New York 2, New York 5, New York 10\nName : Daniel Sickles, George Briggs, James Humphrey, Luther C. Carter, John B. Haskin, William B. Maclay, John Cochrane, Charles Van Wyck, Thomas J. Barr, Horace F. Clark\nParty : Anti-Lecompton Democrat, Democratic, Independent Democrat, Republican\nAge : 38, 46, 45, 48, 43, 36, 42, 35\n/\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 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 \"Customer_Orders\" (\n\torder_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\torder_status_code VARCHAR(15) NOT NULL, \n\tshipping_method_code VARCHAR(15) NOT NULL, \n\torder_placed_datetime DATETIME NOT NULL, \n\torder_delivered_datetime DATETIME, \n\torder_shipping_charges 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_placed_datetime : 2009-01-18 20:06:19, 2008-10-23 06:42:10, 2009-07-05 20:02:55\norder_shipping_charges : 33.58, 77.32, 36.87\n/\n/\nColumns in Customer_Orders and all categories for low cardinality columns :\ncustomer_id : 1, 2, 5, 7, 8, 14, 12, 15, 9\norder_status_code : Paid, Delivered, Cancelled\nshipping_method_code : FedEx, UPS, Unspecified\norder_delivered_datetime : 2018-03-20 12:00:00\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 \"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 \"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 \"Available_Policies\" (\n\t\"Policy_ID\" INTEGER NOT NULL, \n\tpolicy_type_code CHAR(15), \n\t\"Customer_Phone\" VARCHAR(255), \n\tPRIMARY KEY (\"Policy_ID\"), \n\tUNIQUE (\"Policy_ID\")\n)\n/\nColumns in Available_Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 751, 300, 586\nCustomer_Phone : (777)537-7792, 991.642.6485x822, 1-797-927-3585x9321\n/\n/\nColumns in Available_Policies and all categories for low cardinality columns :\npolicy_type_code : Property Insurance, Mortgage Insurance, Life Insurance, Travel Insurance\n/\n" }, { "role": "user", "content": "Which destination has least number of flights?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: destination.\nThe SQL query I'll be generating is:\nSELECT destination FROM Flight GROUP BY destination ORDER BY count(*) 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 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 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 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 \"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 \"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 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 news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\n/\n \nCREATE TABLE \"Participants\" (\n\t\"Participant_ID\" INTEGER NOT NULL, \n\t\"Participant_Type_Code\" CHAR(15) NOT NULL, \n\t\"Participant_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Participant_ID\")\n)\n/\nColumns in Participants and 3 examples in each column for high cardinality columns :\nParticipant_ID : 26, 38, 37\nParticipant_Details : Karlee Batz, Miss Kaci Lebsack, Neil Blick\n/\n/\nColumns in Participants and all categories for low cardinality columns :\nParticipant_Type_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 \"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 \"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 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 \"Photos\" (\n\t\"Photo_ID\" INTEGER NOT NULL, \n\t\"Tourist_Attraction_ID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(255), \n\t\"Description\" VARCHAR(255), \n\t\"Filename\" VARCHAR(255), \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Photo_ID\"), \n\tFOREIGN KEY(\"Tourist_Attraction_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Photos and 3 examples in each column for high cardinality columns :\nPhoto_ID : 428, 303, 332\nTourist_Attraction_ID : 5076, 6523, 5265\nName : fun3, din2, park1\nFilename : 863, 695, 392\n/\n/\nColumns in Photos and all categories for low cardinality columns :\nDescription : None\nOther_Details : None\n/\n \nCREATE TABLE \"Mailshot_Campaigns\" (\n\tmailshot_id INTEGER, \n\tproduct_category VARCHAR(15), \n\tmailshot_name VARCHAR(80), \n\tmailshot_start_date DATETIME, \n\tmailshot_end_date DATETIME, \n\tPRIMARY KEY (mailshot_id)\n)\n/\nColumns in Mailshot_Campaigns and 3 examples in each column for high cardinality columns :\nmailshot_id : 17, 9, 16\nmailshot_start_date : 2017-05-20 20:05:09, 2018-02-04 13:13:36, 2017-09-27 02:35:45\nmailshot_end_date : 2018-03-15 01:06:16, 2018-03-13 14:42:26, 2018-03-01 13:42:09\n/\n/\nColumns in Mailshot_Campaigns and all categories for low cardinality columns :\nproduct_category : food, clothes\nmailshot_name : USPS, US, AL, FED\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 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 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)" }, { "role": "user", "content": "What destination has the fewest number of flights?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight.\nFrom these tables, I'll be using the following columns: destination.\nThe SQL query I'll be generating is:\nSELECT destination FROM Flight GROUP BY destination ORDER BY count(*) 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 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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Assets\" (\n\t\"Asset_ID\" INTEGER NOT NULL, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Asset_ID\")\n)\n/\nColumns in Assets and all categories for low cardinality columns :\nAsset_ID : 1, 2, 3\nOther_Details : Meeting Rooms, Dinning Tables, Transportation Cars\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 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 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 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 phone (\n\t\"Name\" TEXT, \n\t\"Phone_ID\" INTEGER, \n\t\"Memory_in_G\" INTEGER, \n\t\"Carrier\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Phone_ID\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nName : IPhone 6s, IPhone 7, IPhone X, IPhone 6, IPhone 5s\nPhone_ID : 1, 2, 5, 4, 3\nMemory_in_G : 128, 32, 16, 64\nCarrier : Sprint, TMobile\nPrice : 320.0, 1000.0, 480.0, 899.0, 699.0\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 \"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 player (\n\t\"Player_ID\" INTEGER, \n\tname TEXT, \n\t\"Position\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Apps\" REAL, \n\t\"Tries\" REAL, \n\t\"Goals\" TEXT, \n\t\"Points\" REAL, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nname : Michael Platt, Tame Tupou, Terry Newton\nApps : 30.0, 29.0, 24.0\n/\n/\nColumns in player and all categories for low cardinality columns :\nPosition : Scrum Half, Right Centre, Prop, Loose Forward, Hooker, Right Wing, Stand Off, Second Row, Left Wing, Full Back\nClub_ID : 1, 2, 5, 4, 3\nTries : 3.0, 8.0, 1.0, 6.0, 9.0, 2.0, 4.0, 5.0\nGoals : 50/60, 90/106, 0/1, 0\nPoints : 36.0, 8.0, 16.0, 12.0, 24.0, 188.0, 32.0, 110.0, 4.0, 20.0\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 temperature (\n\t\"City_ID\" INTEGER, \n\t\"Jan\" REAL, \n\t\"Feb\" REAL, \n\t\"Mar\" REAL, \n\t\"Apr\" REAL, \n\t\"Jun\" REAL, \n\t\"Jul\" REAL, \n\t\"Aug\" REAL, \n\t\"Sep\" REAL, \n\t\"Oct\" REAL, \n\t\"Nov\" REAL, \n\t\"Dec\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"City_ID\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in temperature and all categories for low cardinality columns :\nCity_ID : 1, 11, 2, 7, 4, 6, 3, 10\nJan : 18.9, 25.6, 18.3, 26.1, 17.8, 26.7, 17.2\nFeb : 18.9, 18.3, 26.1, 27.2, 17.8, 26.6, 17.2\nMar : 19.4, 18.3, 26.1, 26.6, 27.8\nApr : 18.9, 26.1, 20.6, 28.3, 27.8, 20.0\nJun : 22.8, 30.0, 30.6, 22.2, 20.6, 28.3, 27.8, 20.0\nJul : 31.1, 23.3, 28.9, 30.6, 20.6, 21.7, 27.8\nAug : 31.1, 31.7, 23.9, 23.3, 29.4, 20.6, 21.7, 28.3\nSep : 31.1, 21.1, 31.7, 23.3, 29.4, 20.6, 28.3\nOct : 22.8, 30.6, 28.9, 20.6, 28.3, 20.0\nNov : 19.4, 27.2, 28.9, 21.7, 20.0\nDec : 18.3, 26.1, 26.7, 27.8, 20.0\n/\n \nCREATE TABLE entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 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" }, { "role": "user", "content": "What is the aircraft name for the flight with number 99" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Flight.aid, Aircraft.aid, Flight.flno.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T1.flno = 99" } ]
[ { "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 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 \"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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Type_Of_Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResTypeID\" INTEGER, \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\"), \n\tFOREIGN KEY(\"ResTypeID\") REFERENCES \"Restaurant_Type\" (\"ResTypeID\")\n)\n/\nColumns in Type_Of_Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResTypeID : 1, 2\n/\n \nCREATE TABLE \"Products_Booked\" (\n\tbooking_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\treturned_yn VARCHAR(1), \n\treturned_late_yn VARCHAR(1), \n\tbooked_count INTEGER, \n\tbooked_amount FLOAT, \n\tPRIMARY KEY (booking_id, product_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in Products_Booked and 3 examples in each column for high cardinality columns :\nbooked_amount : 398.68, 123.43, 344.38\n/\n/\nColumns in Products_Booked and all categories for low cardinality columns :\nbooking_id : 1, 13, 11, 10, 2, 4, 14, 3, 15\nproduct_id : 1, 2, 5, 4, 3\nreturned_yn : 1\nreturned_late_yn : 1, 0\nbooked_count : 1, 2, 5, 4, 6, 3, 9\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 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 \"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 \"Products\" (\n\tproduct_id INTEGER, \n\tcolor_code VARCHAR(15) NOT NULL, \n\tproduct_category_code VARCHAR(15) NOT NULL, \n\tproduct_name VARCHAR(80), \n\ttypical_buying_price VARCHAR(20), \n\ttypical_selling_price VARCHAR(20), \n\tproduct_description VARCHAR(255), \n\tother_product_details VARCHAR(255), \n\tPRIMARY KEY (product_id), \n\tFOREIGN KEY(color_code) REFERENCES \"Ref_Colors\" (color_code), \n\tFOREIGN KEY(product_category_code) REFERENCES \"Ref_Product_Categories\" (product_category_code)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : peper, cumin, chili\ntypical_buying_price : , 5.578, 503.8431967\ntypical_selling_price : , 149, 10377614.847385\nproduct_description : ut, et, vel\n/\n/\nColumns in Products and all categories for low cardinality columns :\ncolor_code : 1, 2, 5, 7, 4, 9\nproduct_category_code : Spices, Seeds, Herbs\nother_product_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 \"Faculty\" (\n\t\"FacID\" INTEGER, \n\t\"Lname\" VARCHAR(15), \n\t\"Fname\" VARCHAR(15), \n\t\"Rank\" VARCHAR(15), \n\t\"Sex\" VARCHAR(1), \n\t\"Phone\" INTEGER, \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\tPRIMARY KEY (\"FacID\")\n)\n/\nColumns in Faculty and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\nLname : Glaser, Han, James\nFname : Rao, Brenda, James\nPhone : 2105, 3593, 1035\nRoom : 288, 218, 219\n/\n/\nColumns in Faculty and all categories for low cardinality columns :\nRank : AssocProf, AsstProf, Professor, Instructor\nSex : F, M\nBuilding : Krieger, NEB, Barton\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 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 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 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 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 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 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 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" }, { "role": "user", "content": "What is the name of the aircraft that was on flight number 99?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Flight.aid, Aircraft.aid, Flight.flno.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T1.flno = 99" } ]
[ { "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 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 route (\n\ttrain_id INTEGER, \n\tstation_id INTEGER, \n\tPRIMARY KEY (train_id, station_id), \n\tFOREIGN KEY(station_id) REFERENCES station (id), \n\tFOREIGN KEY(train_id) REFERENCES train (id)\n)\n/\nColumns in route and all categories for low cardinality columns :\ntrain_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nstation_id : 1, 2, 5, 7, 8, 4, 6, 3, 9\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 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 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 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 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 races (\n\t\"raceId\" INTEGER, \n\tyear INTEGER, \n\tround INTEGER, \n\t\"circuitId\" INTEGER, \n\tname TEXT, \n\tdate TEXT, \n\ttime TEXT, \n\turl TEXT, \n\tPRIMARY KEY (\"raceId\"), \n\tFOREIGN KEY(\"circuitId\") REFERENCES circuits (\"circuitId\")\n)\n/\nColumns in races and 3 examples in each column for high cardinality columns :\nraceId : 87, 56, 65\nyear : 2004, 2009, 2001\nround : 17, 9, 16\ncircuitId : 19, 17, 21\nname : Turkish Grand Prix, Chinese Grand Prix, Belgian Grand Prix\ndate : 2009-07-12, 2008-05-11, 2005-04-03\ntime : , 16:00:00, 09:00:00\nurl : http://en.wikipedia.org/wiki/2004_Spanish_Grand_Prix, http://en.wikipedia.org/wiki/2000_San_Marino_Grand_Prix, http://en.wikipedia.org/wiki/1999_Austrian_Grand_Prix\n/\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 \"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 church (\n\t\"Church_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Organized_by\" TEXT, \n\t\"Open_Date\" INTEGER, \n\t\"Continuation_of\" TEXT, \n\tPRIMARY KEY (\"Church_ID\")\n)\n/\nColumns in church and all categories for low cardinality columns :\nChurch_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : Pure Church of Christ, True Church of Jesus Christ of Latter Day Saints, Alston Church, Church of Christ, Church of Jesus Christ, the Bride, the Lamb's Wife, Church of Christ (Parrishite), Independent Church\nOrganized_by : Hiram Page, George M. Hinkle, Isaac Russell, Wycam Clark, Ezra Booth, William Chubby, William Law, – Hoton, Warren Parrish\nOpen_Date : 1840, 1839, 1836, 1832, 1837, 1844, 1831, 1830, 1842\nContinuation_of : Church of Jesus Christ of Latter Day Saints, Church of Christ, Church of the Latter Day Saints\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 \"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 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 \"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" }, { "role": "user", "content": "Show all flight numbers with aircraft Airbus A340-300." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Flight.flno, Flight.aid, Aircraft.aid, Aircraft.name, Airbus A340-300.\nThe SQL query I'll be generating is:\nSELECT T1.flno FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T2.name = \"Airbus A340-300\"" } ]
[ { "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 flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE route (\n\ttrain_id INTEGER, \n\tstation_id INTEGER, \n\tPRIMARY KEY (train_id, station_id), \n\tFOREIGN KEY(station_id) REFERENCES station (id), \n\tFOREIGN KEY(train_id) REFERENCES train (id)\n)\n/\nColumns in route and all categories for low cardinality columns :\ntrain_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nstation_id : 1, 2, 5, 7, 8, 4, 6, 3, 9\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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\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 event (\n\t\"ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Stadium_ID\" INTEGER, \n\t\"Year\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Stadium_ID\") REFERENCES stadium (\"ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nID : 1, 2, 5, 4, 6, 3\nName : Pacific, European FINA, FINA, World Master, IPC, World Junior\nStadium_ID : 1, 2, 8, 4, 3, 10\nYear : 2016, 2013, 2012, 2017, 2011, 2014\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 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 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 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 \"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 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 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 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 \"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 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 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 \"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 \"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 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)" }, { "role": "user", "content": "What are the flight numbers for the aircraft Airbus A340-300?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Flight.flno, Flight.aid, Aircraft.aid, Aircraft.name, Airbus A340-300.\nThe SQL query I'll be generating is:\nSELECT T1.flno FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T2.name = \"Airbus A340-300\"" } ]
[ { "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 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 \"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 \"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 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 \"Actual_Order_Products\" (\n\tactual_order_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tFOREIGN KEY(actual_order_id) REFERENCES \"Actual_Orders\" (actual_order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/\nColumns in Actual_Order_Products and all categories for low cardinality columns :\nactual_order_id : 13, 2, 5, 15, 7, 6, 14, 3, 10, 9\nproduct_id : 1, 2, 5, 4, 6, 3\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 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 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 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 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 \"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 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 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 \"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 \"Customers_Policies\" (\n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Policy_ID\" INTEGER NOT NULL, \n\t\"Date_Opened\" DATE, \n\t\"Date_Closed\" DATE, \n\tPRIMARY KEY (\"Customer_ID\", \"Policy_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Customers\" (\"Customer_ID\"), \n\tFOREIGN KEY(\"Policy_ID\") REFERENCES \"Available_Policies\" (\"Policy_ID\")\n)\n/\nColumns in Customers_Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 586, 346, 630\nDate_Opened : 2016-06-24, 2016-11-18, 2016-07-07\nDate_Closed : 2018-03-08, 2018-02-20, 2018-03-19\n/\n/\nColumns in Customers_Policies and all categories for low cardinality columns :\nCustomer_ID : 562, 582, 892, 826, 682, 214, 996, 256, 641\n/\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 \"Invoices\" (\n\tinvoice_number INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_date DATETIME, \n\tPRIMARY KEY (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 2018-03-16 21:57:43, 2018-03-20 00:21:41, 2018-03-05 08:47:33\n/\n/\nColumns in Invoices and all categories for low cardinality columns :\norder_id : 13, 11, 5, 8, 4, 12, 3, 14, 10, 9\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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"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" }, { "role": "user", "content": "Show aircraft names and number of flights for each aircraft." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Flight.aid, Aircraft.aid.\nThe SQL query I'll be generating is:\nSELECT T2.name , count(*) FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid" } ]
[ { "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\" (\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 \"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 \"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 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 \"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 \"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 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 time_slot (\n\ttime_slot_id VARCHAR(4), \n\tday VARCHAR(1), \n\tstart_hr NUMERIC(2), \n\tstart_min NUMERIC(2), \n\tend_hr NUMERIC(2), \n\tend_min NUMERIC(2), \n\tPRIMARY KEY (time_slot_id, day, start_hr, start_min), \n\tCHECK (start_hr >= 0 and start_hr < 24), \n\tCHECK (start_min >= 0 and start_min < 60), \n\tCHECK (end_hr >= 0 and end_hr < 24), \n\tCHECK (end_min >= 0 and end_min < 60)\n)\n/\nColumns in time_slot and all categories for low cardinality columns :\ntime_slot_id : E, F, C, H, A, D, G, B\nday : F, T, R, W, M\nstart_hr : 16.0000000000, 10.0000000000, 14.0000000000, 13.0000000000, 9.0000000000, 8.0000000000, 11.0000000000\nstart_min : 30.0000000000, 0E-10\nend_hr : 16.0000000000, 15.0000000000, 12.0000000000, 13.0000000000, 9.0000000000, 8.0000000000, 11.0000000000\nend_min : 30.0000000000, 45.0000000000, 50.0000000000\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\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 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 \"Participates_in\" (\n\tstuid INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Participates_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nactid : 771, 782, 770\n/\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 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 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 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 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 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 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 people (\n\t\"People_ID\" INTEGER, \n\t\"District\" TEXT, \n\t\"Name\" TEXT, \n\t\"Party\" TEXT, \n\t\"Age\" INTEGER, \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\nDistrict : New York 7, New York 1, New York 8, New York 4, New York 3, New York 9, New York 6, New York 2, New York 5, New York 10\nName : Daniel Sickles, George Briggs, James Humphrey, Luther C. Carter, John B. Haskin, William B. Maclay, John Cochrane, Charles Van Wyck, Thomas J. Barr, Horace F. Clark\nParty : Anti-Lecompton Democrat, Democratic, Independent Democrat, Republican\nAge : 38, 46, 45, 48, 43, 36, 42, 35\n/\n" }, { "role": "user", "content": "What is the name of each aircraft and how many flights does each one complete?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Flight.aid, Aircraft.aid.\nThe SQL query I'll be generating is:\nSELECT T2.name , count(*) FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid" } ]
[ { "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 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 \"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 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 \"Actual_Orders\" (\n\tactual_order_id INTEGER, \n\torder_status_code VARCHAR(10) NOT NULL, \n\tregular_order_id INTEGER NOT NULL, \n\tactual_order_date DATETIME, \n\tPRIMARY KEY (actual_order_id), \n\tFOREIGN KEY(regular_order_id) REFERENCES \"Regular_Orders\" (regular_order_id)\n)\n/\nColumns in Actual_Orders and 3 examples in each column for high cardinality columns :\nactual_order_id : 1, 13, 11\nregular_order_id : 1, 13, 11\nactual_order_date : 2018-03-05 17:31:36, 2018-03-02 08:33:39, 2018-02-26 01:55:52\n/\n/\nColumns in Actual_Orders and all categories for low cardinality columns :\norder_status_code : Cancel, Success\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 \"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 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 \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"Ref_Detention_Type\" (\n\tdetention_type_code VARCHAR(10), \n\tdetention_type_description VARCHAR(80), \n\tPRIMARY KEY (detention_type_code)\n)\n/\nColumns in Ref_Detention_Type and all categories for low cardinality columns :\ndetention_type_code : LUNCH, BREAK , AFTER\ndetention_type_description : After School, During Break time, Lunch-time\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER, \n\tcustomer_type_code VARCHAR(20) NOT NULL, \n\taddress_line_1 VARCHAR(80), \n\taddress_line_2 VARCHAR(80), \n\ttown_city VARCHAR(80), \n\tstate VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and all categories for low cardinality columns :\ncustomer_id : 120, 114, 113, 116, 117, 115, 119, 118\ncustomer_type_code : Defaults on payments, Good Credit Rating\naddress_line_1 : 92189 Gulgowski Ranch Apt. 683, 05355 Marcelle Radial, 039 Jedidiah Estate Suite 537, 72144 Katlynn Flat Suite 512, 518 Mann Park, 425 Roman Tunnel, 1566 Ramona Overpass Apt. 464, 144 Legros Landing\naddress_line_2 : Suite 151, Apt. 551, Suite 035, Suite 959, Apt. 245, Apt. 495, Apt. 828, Suite 054\ntown_city : Funkstad, Tyreekhaven, North Alisaville, Maryamport, Hansenbury, Port Joshuah, West Annamariestad, Sauerberg\nstate : Pennsylvania, Hawaii, Tennessee, Kansas, Colorado, Iowa, Florida\nemail_address : hsteuber@example.org, vbogisich@example.org, rzulauf@example.org, cayla.satterfield@example.net, paige.hyatt@example.com, lavonne.frami@example.com, ubeier@example.org, vida86@example.com\nphone_number : 548.373.3603x59134, 044-468-4549, 06963347450, 997.698.4779x882, +38(3)9011433816, 578.019.7943x328, 1-369-302-7623x576, 470-803-0244\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 \"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 \"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 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 \"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 \"Claims_Processing\" (\n\t\"Claim_Processing_ID\" INTEGER NOT NULL, \n\t\"Claim_ID\" INTEGER NOT NULL, \n\t\"Claim_Outcome_Code\" CHAR(15) NOT NULL, \n\t\"Claim_Stage_ID\" INTEGER NOT NULL, \n\t\"Staff_ID\" INTEGER, \n\tPRIMARY KEY (\"Claim_Processing_ID\"), \n\tFOREIGN KEY(\"Claim_ID\") REFERENCES \"Claim_Headers\" (\"Claim_Header_ID\"), \n\tFOREIGN KEY(\"Staff_ID\") REFERENCES \"Staff\" (\"Staff_ID\")\n)\n/\nColumns in Claims_Processing and 3 examples in each column for high cardinality columns :\nClaim_Processing_ID : 243, 342, 818\n/\n/\nColumns in Claims_Processing and all categories for low cardinality columns :\nClaim_ID : 45, 28, 90, 24, 34, 62, 15, 27, 81\nClaim_Outcome_Code : Settled, In progress, Disputed\nClaim_Stage_ID : 1, 3\nStaff_ID : 771, 427, 510, 673, 986, 687, 822, 589, 718\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 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" }, { "role": "user", "content": "Show names for all aircraft with at least two flights." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Flight.aid, Aircraft.aid.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid 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 regions (\n\t\"REGION_ID\" DECIMAL(5, 0) NOT NULL, \n\t\"REGION_NAME\" VARCHAR(25) DEFAULT NULL, \n\tPRIMARY KEY (\"REGION_ID\")\n)\n/\nColumns in regions and all categories for low cardinality columns :\nREGION_ID : 1, 2, 4, 3\nREGION_NAME : Europe\\r, Middle East and Africa\\r, Asia\\r, Americas\\r\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 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 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 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 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 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 \"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 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 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 \"Player_Attributes\" (\n\tid INTEGER, \n\tplayer_fifa_api_id INTEGER, \n\tplayer_api_id INTEGER, \n\tdate TEXT, \n\toverall_rating INTEGER, \n\tpotential INTEGER, \n\tpreferred_foot TEXT, \n\tattacking_work_rate TEXT, \n\tdefensive_work_rate TEXT, \n\tcrossing INTEGER, \n\tfinishing INTEGER, \n\theading_accuracy INTEGER, \n\tshort_passing INTEGER, \n\tvolleys INTEGER, \n\tdribbling INTEGER, \n\tcurve INTEGER, \n\tfree_kick_accuracy INTEGER, \n\tlong_passing INTEGER, \n\tball_control INTEGER, \n\tacceleration INTEGER, \n\tsprint_speed INTEGER, \n\tagility INTEGER, \n\treactions INTEGER, \n\tbalance INTEGER, \n\tshot_power INTEGER, \n\tjumping INTEGER, \n\tstamina INTEGER, \n\tstrength INTEGER, \n\tlong_shots INTEGER, \n\taggression INTEGER, \n\tinterceptions INTEGER, \n\tpositioning INTEGER, \n\tvision INTEGER, \n\tpenalties INTEGER, \n\tmarking INTEGER, \n\tstanding_tackle INTEGER, \n\tsliding_tackle INTEGER, \n\tgk_diving INTEGER, \n\tgk_handling INTEGER, \n\tgk_kicking INTEGER, \n\tgk_positioning INTEGER, \n\tgk_reflexes INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(player_api_id) REFERENCES \"Player\" (player_api_id), \n\tFOREIGN KEY(player_fifa_api_id) REFERENCES \"Player\" (player_fifa_api_id)\n)\n/\nColumns in Player_Attributes and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\nplayer_fifa_api_id : 186170, 221280, 189615\nplayer_api_id : 30895, 30572, 162549\ndate : 2013-11-01 00:00:00, 2013-09-20 00:00:00, 2007-08-30 00:00:00\noverall_rating : 79, 53, 65\npotential : 79, 87, 56\ncrossing : 79, 56, 78\nfinishing : 79, 53, 56\nheading_accuracy : 79, 56, 65\nshort_passing : 79, 53, 65\nvolleys : 56, 44, 63\ndribbling : 79, 53, 56\ncurve : 79, 56, 65\nfree_kick_accuracy : 53, 65, 63\nlong_passing : 53, 65, 49\nball_control : 79, 65, 78\nacceleration : 79, 53, 78\nsprint_speed : 79, 53, 78\nagility : 79, 78, 49\nreactions : 79, 56, 65\nbalance : 87, 79, 56\nshot_power : 53, 56, 65\njumping : 56, 65, 78\nstamina : 79, 87, 56\nstrength : 87, 56, 78\nlong_shots : 53, 56, 78\naggression : 56, 65, 75\ninterceptions : 56, 65, 44\npositioning : 79, 56, 78\nvision : 79, 53, 65\npenalties : 53, 56, 36\nmarking : 79, 53, 65\nstanding_tackle : 79, 56, 78\nsliding_tackle : 56, 78, 65\ngk_diving : 53, 16, 13\ngk_handling : 41, 13, 20\ngk_kicking : 65, 49, 63\ngk_positioning : 16, 13, 20\ngk_reflexes : 53, 13, 20\n/\n/\nColumns in Player_Attributes and all categories for low cardinality columns :\npreferred_foot : left, right\nattacking_work_rate : high, medium\ndefensive_work_rate : high, medium\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 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" }, { "role": "user", "content": "What are the names for all aircrafts with at least 2 flights?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Flight, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Flight.aid, Aircraft.aid.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid 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 \"Ref_Product_Categories\" (\n\tproduct_category_code VARCHAR(15), \n\tproduct_category_description VARCHAR(80), \n\tunit_of_measure VARCHAR(20), \n\tPRIMARY KEY (product_category_code)\n)\n/\nColumns in Ref_Product_Categories and all categories for low cardinality columns :\nproduct_category_code : Spices, Seeds, Herbs\nproduct_category_description : Spices, Seeds, Herbs\nunit_of_measure : Weight - pound,kilo., Handful \n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 \"driverStandings\" (\n\t\"driverStandingsId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\tpoints REAL, \n\tposition INTEGER, \n\t\"positionText\" TEXT, \n\twins INTEGER, \n\tPRIMARY KEY (\"driverStandingsId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/\nColumns in driverStandings and 3 examples in each column for high cardinality columns :\ndriverStandingsId : 87, 56, 65\ndriverId : 17, 21, 9\npoints : 8.0, 3.0, 29.0\nposition : 17, 21, 9\npositionText : 17, 21, 9\n/\n/\nColumns in driverStandings and all categories for low cardinality columns :\nraceId : 26, 20, 25, 24, 23, 21, 19, 18, 27, 22\nwins : 1, 2, 4, 3, 0\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 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 phone (\n\t\"Company_name\" TEXT, \n\t\"Hardware_Model_name\" TEXT, \n\t\"Accreditation_type\" TEXT, \n\t\"Accreditation_level\" TEXT, \n\t\"Date\" TEXT, \n\tchip_model TEXT, \n\tscreen_mode TEXT, \n\tPRIMARY KEY (\"Hardware_Model_name\"), \n\tFOREIGN KEY(chip_model) REFERENCES chip_model (\"Model_name\"), \n\tFOREIGN KEY(screen_mode) REFERENCES screen_mode (\"Graphics_mode\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nCompany_name : Samsung Electronics Co Ltd, Huawei Technologies Co.Ltd., HTC Corporation, Nokia Corporation, LG Electronics, Sony Mobile Communications\nHardware_Model_name : GT-I9300, U8815 Asura, Lumia 920, Lumia 820, Lumia 620, GT-I9100, Nokia 700, LG-P760, Z520e, XPERIA T, XPERIA J\nAccreditation_type : Provisional, Full\nAccreditation_level : joyn Hot Fixes, joyn\nDate : Approved (valid until 03.05.13), Approved (valid until 06.04.13), Approved (awarded 19.11.12), Approved (awarded 05.12.12), Approved (valid until 14.09.13), Approved (awarded 23.10.12), Approved (awarded 15.11.12)\nchip_model : X50 Advanced, X5, X3i, X51v, X30 low-end, X50 Standard\nscreen_mode : 1, 2, 5, 4, 6, 3\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 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 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 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 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" }, { "role": "user", "content": "How many employees have certificate." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Certificate.\nFrom these tables, I'll be using the following columns: eid.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT eid) FROM Certificate" } ]
[ { "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 \"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 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 \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\tcity 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 : 7089 Mueller Forks, 535 Ariel Brook, 3904 Stroman Passage\ncity : Buckridgehaven, South Eugene, Elviebury\nzip_postcode : 22194, 99903, 14445\nstate_province_county : Louisiana, Kentucky, Ohio\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\n \nCREATE TABLE \"match\" (\n\t\"Match_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Score\" TEXT, \n\t\"Result\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (\"Match_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nMatch_ID : 1, 2, 5, 4, 6, 3\nDate : 23 July 1992, 18 February 1992, 19 July 1992, 23 July 2000, 4 April 1993\nVenue : Estadio Rigoberto López , Managua , Nicaragua, Estadio Cuscatlán , San Salvador , El Salvador\nScore : 3-0, 2–1, 1-0, 1–0\nResult : 5-1, 7–1, 5-0, 2–1, 2-0\nCompetition : 1994 FIFA World Cup qualification, Friendly match, 2002 FIFA World Cup qualification\n/\n \nCREATE TABLE \"Actual_Order_Products\" (\n\tactual_order_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tFOREIGN KEY(actual_order_id) REFERENCES \"Actual_Orders\" (actual_order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/\nColumns in Actual_Order_Products and all categories for low cardinality columns :\nactual_order_id : 13, 2, 5, 15, 7, 6, 14, 3, 10, 9\nproduct_id : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"Trained_In\" (\n\t\"Physician\" INTEGER NOT NULL, \n\t\"Treatment\" INTEGER NOT NULL, \n\t\"CertificationDate\" DATETIME NOT NULL, \n\t\"CertificationExpires\" DATETIME NOT NULL, \n\tPRIMARY KEY (\"Physician\", \"Treatment\"), \n\tCONSTRAINT \"fk_Trained_In_Physician_EmployeeID\" FOREIGN KEY(\"Physician\") REFERENCES \"Physician\" (\"EmployeeID\"), \n\tCONSTRAINT \"fk_Trained_In_Procedures_Code\" FOREIGN KEY(\"Treatment\") REFERENCES \"Procedures\" (\"Code\")\n)\n/\nColumns in Trained_In and all categories for low cardinality columns :\nPhysician : 7, 6, 3\nTreatment : 1, 2, 5, 7, 4, 6, 3\nCertificationDate : 2008-01-01 00:00:00, 2007-01-01 00:00:00\nCertificationExpires : 2007-12-31 00:00:00, 2008-12-31 00:00:00\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 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 \"DEPARTMENT\" (\n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"DEPT_NAME\" VARCHAR(30), \n\t\"SCHOOL_CODE\" VARCHAR(8), \n\t\"EMP_NUM\" INTEGER, \n\t\"DEPT_ADDRESS\" VARCHAR(20), \n\t\"DEPT_EXTENSION\" VARCHAR(4), \n\tPRIMARY KEY (\"DEPT_CODE\"), \n\tFOREIGN KEY(\"EMP_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\")\n)\n/\nColumns in DEPARTMENT and 3 examples in each column for high cardinality columns :\nDEPT_CODE : ART, ECON/FIN, HIST\nDEPT_NAME : History, Computer Info. Systems, Biology\nEMP_NUM : 114, 106, 342\nDEPT_ADDRESS : KLR 126, Box 55, AAK 230, Box 415, KLR 333, Box 56\nDEPT_EXTENSION : 1867, 3126, 4117\n/\n/\nColumns in DEPARTMENT and all categories for low cardinality columns :\nSCHOOL_CODE : BUS, A&SCI\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 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 \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 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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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" }, { "role": "user", "content": "What is the count of distinct employees with certificates?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Certificate.\nFrom these tables, I'll be using the following columns: eid.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT eid) FROM Certificate" } ]
[ { "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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Statements\" (\n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Statement_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Statement_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/\nColumns in Statements and all categories for low cardinality columns :\nStatement_ID : 192, 57\nStatement_Details : Private Project, Open Project\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 \"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 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 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 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 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 \"Courses\" (\n\tcourse_id VARCHAR(100) NOT NULL, \n\tcourse_name VARCHAR(120), \n\tcourse_description VARCHAR(255), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (course_id)\n)\n/\nColumns in Courses and all categories for low cardinality columns :\ncourse_id : 303, 305, 304, 306, 302, 301\ncourse_name : data structure, English, French, statistics, database, Art history\ncourse_description : data structure, English, French, statistics, database, Art history\nother_details : None\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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 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 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 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 \"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 \"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 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 \"Document_Structures\" (\n\tdocument_structure_code VARCHAR(15), \n\tparent_document_structure_code VARCHAR(15), \n\tdocument_structure_description VARCHAR(80), \n\tPRIMARY KEY (document_structure_code)\n)\n/\nColumns in Document_Structures and all categories for low cardinality columns :\ndocument_structure_code : 1, 5, 8, 6, 9\nparent_document_structure_code : 1, 8, 6\ndocument_structure_description : Main section, Image section, Header, Bib, Author section\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" }, { "role": "user", "content": "Show ids for all employees who don't have a certificate." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate.\nFrom these tables, I'll be using the following columns: eid.\nThe SQL query I'll be generating is:\nSELECT eid FROM Employee EXCEPT SELECT eid FROM Certificate" } ]
[ { "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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Participants\" (\n\t\"Participant_ID\" INTEGER NOT NULL, \n\t\"Participant_Type_Code\" CHAR(15) NOT NULL, \n\t\"Participant_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Participant_ID\")\n)\n/\nColumns in Participants and 3 examples in each column for high cardinality columns :\nParticipant_ID : 26, 38, 37\nParticipant_Details : Karlee Batz, Miss Kaci Lebsack, Neil Blick\n/\n/\nColumns in Participants and all categories for low cardinality columns :\nParticipant_Type_Code : Organizer, Participant\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\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 \"Document_Types\" (\n\tdocument_type_code VARCHAR(10), \n\tdocument_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (document_type_code)\n)\n/\nColumns in Document_Types and all categories for low cardinality columns :\ndocument_type_code : APP, REG\ndocument_description : Regular, Initial Application\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 \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 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 \"Authors\" (\n\t\"authID\" INTEGER, \n\tlname TEXT, \n\tfname TEXT, \n\tPRIMARY KEY (\"authID\")\n)\n/\nColumns in Authors and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\nlname : Gibbons, Turon, Ueno\nfname : Daniel W. H., Tim, Ralf\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 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 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 news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\n/\n \nCREATE TABLE project (\n\t\"Pname\" TEXT, \n\t\"Pnumber\" INTEGER, \n\t\"Plocation\" TEXT, \n\t\"Dnum\" INTEGER, \n\tPRIMARY KEY (\"Pnumber\")\n)\n/\nColumns in project and all categories for low cardinality columns :\nPname : Newbenefits, Reorganization, ProductX, Computerization, ProductZ, ProductY\nPnumber : 1, 20, 2, 30, 3, 10\nPlocation : Stafford, Sugarland, Bellaire, Houston\nDnum : 1, 4, 5\n/\n \nCREATE TABLE party_events (\n\t\"Event_ID\" INTEGER, \n\t\"Event_Name\" TEXT, \n\t\"Party_ID\" INTEGER, \n\t\"Member_in_charge_ID\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Member_in_charge_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in party_events and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 7, 8, 4, 6, 3\nEvent_Name : Election Meeting, Annaual Meeting, Conference, Budget Meeting\nParty_ID : 1, 2, 3\nMember_in_charge_ID : 11, 2, 15, 4, 12, 3, 10\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 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 \"Assessment_Notes\" (\n\tnotes_id INTEGER NOT NULL, \n\tstudent_id INTEGER, \n\tteacher_id INTEGER NOT NULL, \n\tdate_of_notes DATETIME, \n\ttext_of_notes VARCHAR(255), \n\tother_details VARCHAR(255), \n\tFOREIGN KEY(teacher_id) REFERENCES \"Teachers\" (teacher_id), \n\tFOREIGN KEY(student_id) REFERENCES \"Students\" (student_id)\n)\n/\nColumns in Assessment_Notes and 3 examples in each column for high cardinality columns :\nnotes_id : 1, 13, 11\ndate_of_notes : 2014-01-31 02:05:02, 2014-04-28 02:07:53, 1978-04-15 04:49:18\n/\n/\nColumns in Assessment_Notes and all categories for low cardinality columns :\nstudent_id : 1, 3, 13, 11, 7, 4, 12, 14, 15\nteacher_id : 1, 15, 7, 6, 14, 3, 10, 9\ntext_of_notes : None\nother_details : None\n/\n" }, { "role": "user", "content": "What are the ids of all employees that don't have certificates?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate.\nFrom these tables, I'll be using the following columns: eid.\nThe SQL query I'll be generating is:\nSELECT eid FROM Employee EXCEPT SELECT eid FROM Certificate" } ]
[ { "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 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 \nCREATE TABLE medicine (\n\tid INTEGER, \n\tname TEXT, \n\t\"Trade_Name\" TEXT, \n\t\"FDA_approved\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in medicine and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Quetiapine, Carpipramine, Asenapine\nTrade_Name : Buronil, Fanapt, Nipolept\n/\n/\nColumns in medicine and all categories for low cardinality columns :\nFDA_approved : Yes, No\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 \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 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 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\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 phone (\n\t\"Name\" TEXT, \n\t\"Phone_ID\" INTEGER, \n\t\"Memory_in_G\" INTEGER, \n\t\"Carrier\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Phone_ID\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nName : IPhone 6s, IPhone 7, IPhone X, IPhone 6, IPhone 5s\nPhone_ID : 1, 2, 5, 4, 3\nMemory_in_G : 128, 32, 16, 64\nCarrier : Sprint, TMobile\nPrice : 320.0, 1000.0, 480.0, 899.0, 699.0\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\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 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" }, { "role": "user", "content": "Show names for all aircrafts of which John Williams has certificates." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Employee.name, John Williams.\nThe SQL query I'll be generating is:\nSELECT T3.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T1.name = \"John Williams\"" } ]
[ { "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 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 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 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 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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"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 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 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 \"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 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" }, { "role": "user", "content": "What are the names of all aircrafts that John Williams have certificates to be able to fly?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Employee.name, John Williams.\nThe SQL query I'll be generating is:\nSELECT T3.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T1.name = \"John Williams\"" } ]
[ { "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 \"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 address (\n\taddress_id INTEGER NOT NULL, \n\taddress VARCHAR(50) NOT NULL, \n\taddress2 VARCHAR(50) DEFAULT NULL, \n\tdistrict VARCHAR(20) NOT NULL, \n\tcity_id INTEGER NOT NULL, \n\tpostal_code VARCHAR(10) DEFAULT NULL, \n\tphone VARCHAR(20) NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (address_id), \n\tFOREIGN KEY(city_id) REFERENCES city (city_id)\n)\n/\nColumns in address and 3 examples in each column for high cardinality columns :\naddress_id : 87, 56, 65\naddress : 900 Santiago de Compostela Parkway, 270 Toulon Boulevard, 1697 Tanauan Lane\ndistrict : , Lipetsk, Kanagawa\ncity_id : 87, 586, 56\npostal_code : , 5892, 23616\nphone : , 760171523969, 380657522649\n/\n/\nColumns in address and all categories for low cardinality columns :\naddress2 : , None\nlast_update : 2006-02-15 04:45:30\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 \"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 \"Circulation_History\" (\n\tdocument_id INTEGER NOT NULL, \n\tdraft_number INTEGER NOT NULL, \n\tcopy_number INTEGER NOT NULL, \n\temployee_id INTEGER NOT NULL, \n\tPRIMARY KEY (document_id, draft_number, copy_number, employee_id), \n\tFOREIGN KEY(document_id, draft_number, copy_number) REFERENCES \"Draft_Copies\" (document_id, draft_number, copy_number), \n\tFOREIGN KEY(employee_id) REFERENCES \"Employees\" (employee_id)\n)\n/\nColumns in Circulation_History and all categories for low cardinality columns :\ndocument_id : 1, 10, 2, 20\ndraft_number : 1, 2, 17, 20\ncopy_number : 10, 15, 4, 5\nemployee_id : 1, 8, 2\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 \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(15), \n\tproduct_name VARCHAR(80), \n\tproduct_price DOUBLE, \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_price : 5927021.8748021, 622.79275984494, 22956668.699482\n/\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_type_code : Hardware, Clothes\nproduct_name : Apple, jcrew, Sony, gucci\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \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 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 \"lapTimes\" (\n\t\"raceId\" INTEGER, \n\t\"driverId\" INTEGER, \n\tlap INTEGER, \n\tposition INTEGER, \n\ttime TEXT, \n\tmilliseconds INTEGER, \n\tPRIMARY KEY (\"raceId\", \"driverId\", lap), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\"), \n\tFOREIGN KEY(\"driverId\") REFERENCES drivers (\"driverId\")\n)\n/\nColumns in lapTimes and all categories for low cardinality columns :\nraceId : \ndriverId : \nlap : \nposition : \ntime : \nmilliseconds : \n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 player_coach (\n\t\"Player_ID\" INTEGER, \n\t\"Coach_ID\" INTEGER, \n\t\"Starting_year\" INTEGER, \n\tPRIMARY KEY (\"Player_ID\", \"Coach_ID\"), \n\tFOREIGN KEY(\"Coach_ID\") REFERENCES coach (\"Coach_ID\"), \n\tFOREIGN KEY(\"Player_ID\") REFERENCES player (\"Player_ID\")\n)\n/\nColumns in player_coach and all categories for low cardinality columns :\nPlayer_ID : 1, 2, 4, 6, 14, 3, 10\nCoach_ID : 1, 2, 5, 3\nStarting_year : 2012, 2010, 2011, 2013\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 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 \"Ref_Characteristic_Types\" (\n\tcharacteristic_type_code VARCHAR(15), \n\tcharacteristic_type_description VARCHAR(80), \n\tPRIMARY KEY (characteristic_type_code)\n)\n/\nColumns in Ref_Characteristic_Types and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_type_description : Grade, Purity\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 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 \"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" }, { "role": "user", "content": "Show names for all employees who have certificate of Boeing 737-800." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.name, Boeing 737-800.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Boeing 737-800\"" } ]
[ { "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 college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"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 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 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 \"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 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 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 \"Premises\" (\n\tpremise_id INTEGER, \n\tpremises_type VARCHAR(15) NOT NULL, \n\tpremise_details VARCHAR(255), \n\tPRIMARY KEY (premise_id)\n)\n/\nColumns in Premises and 3 examples in each column for high cardinality columns :\npremise_id : 1, 13, 11\npremise_details : 5109 Jules Squares Apt. 082, 676 Kelly Spur, 00100 Green Mountains Apt. 653\n/\n/\nColumns in Premises and all categories for low cardinality columns :\npremises_type : Residence, Office, Warehouse\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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 prereq (\n\tcourse_id VARCHAR(8), \n\tprereq_id VARCHAR(8), \n\tPRIMARY KEY (course_id, prereq_id), \n\tFOREIGN KEY(course_id) REFERENCES course (course_id), \n\tFOREIGN KEY(prereq_id) REFERENCES course (course_id)\n)\n/\nColumns in prereq and 3 examples in each column for high cardinality columns :\ncourse_id : 241, 586, 628\nprereq_id : 304, 628, 927\n/\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 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 \"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 are the names of all employees who have a certificate to fly Boeing 737-800?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.name, Boeing 737-800.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Boeing 737-800\"" } ]
[ { "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 \"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 \"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_Shipping_Agents\" (\n\tshipping_agent_code CHAR(15) NOT NULL, \n\tshipping_agent_name VARCHAR(255) NOT NULL, \n\tshipping_agent_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (shipping_agent_code)\n)\n/\nColumns in Ref_Shipping_Agents and all categories for low cardinality columns :\nshipping_agent_code : FE, UP, US, AL, SH\nshipping_agent_name : Airline, Fedex, UPS, USPS, Ship\nshipping_agent_description : t, q, k, w, g\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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\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 \"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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 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 \"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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 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 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 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 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 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 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 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 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" }, { "role": "user", "content": "Show names for all employees who have certificates on both Boeing 737-800 and Airbus A340-300." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.name, Boeing 737-800, Airbus A340-300.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Boeing 737-800\" INTERSECT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Airbus A340-300\"" } ]
[ { "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 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 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 \"Problem_Category_Codes\" (\n\tproblem_category_code VARCHAR(20), \n\tproblem_category_description VARCHAR(80), \n\tPRIMARY KEY (problem_category_code)\n)\n/\nColumns in Problem_Category_Codes and all categories for low cardinality columns :\nproblem_category_code : Datatabase, Middleware, GUI\nproblem_category_description : User Interface., Infrastructrure and Architecture, Database design or contents.\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 \"Products\" (\n\t\"Product_ID\" VARCHAR(100) NOT NULL, \n\t\"Product_Name\" VARCHAR(255), \n\t\"Product_Price\" DECIMAL(20, 4), \n\t\"Product_Description\" VARCHAR(255), \n\t\"Other_Product_Service_Details\" VARCHAR(255), \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 : 250, 300, 233\nProduct_Price : 634660.0000, 1577.0000, 900.0000\n/\n/\nColumns in Products and all categories for low cardinality columns :\nProduct_Name : dinning, photo, film\nProduct_Description : None\nOther_Product_Service_Details : None\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 \"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 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 (\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 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 \"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 film_text (\n\tfilm_id SMALLINT NOT NULL, \n\ttitle VARCHAR(255) NOT NULL, \n\tdescription TEXT, \n\tPRIMARY KEY (film_id)\n)\n/\nColumns in film_text and all categories for low cardinality columns :\nfilm_id : \ntitle : \ndescription : \n/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"College_ID\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"College_ID\") REFERENCES college (\"College_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 : Tom Weiskopf, Tom Watson, Pat Fitzsimons, Homero Blancas, Jack Nicklaus, Billy Casper, J. C. Snead, Arnold Palmer, Lee Trevino, Bobby Nichols\nCountry : United States, Canada\nCollege_ID : 1, 2, 5, 4, 3\n/\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 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 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 \"Premises\" (\n\tpremise_id INTEGER, \n\tpremises_type VARCHAR(15) NOT NULL, \n\tpremise_details VARCHAR(255), \n\tPRIMARY KEY (premise_id)\n)\n/\nColumns in Premises and 3 examples in each column for high cardinality columns :\npremise_id : 1, 13, 11\npremise_details : 5109 Jules Squares Apt. 082, 676 Kelly Spur, 00100 Green Mountains Apt. 653\n/\n/\nColumns in Premises and all categories for low cardinality columns :\npremises_type : Residence, Office, Warehouse\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 \"Third_Party_Companies\" (\n\tcompany_id INTEGER, \n\tcompany_type VARCHAR(5) NOT NULL, \n\tcompany_name VARCHAR(255), \n\tcompany_address VARCHAR(255), \n\tother_company_details VARCHAR(255), \n\tPRIMARY KEY (company_id)\n)\n/\nColumns in Third_Party_Companies and 3 examples in each column for high cardinality columns :\ncompany_id : 1, 13, 11\ncompany_name : Weimann-Swift, Glover-Vandervort, Dicki, Erdman and Kris\ncompany_address : 615 Jacobs Mews, 9576 Jacynthe Point Suite 747, 51515 Conn Corner Suite 696\nother_company_details : Palestinian Territory, Slovenia, Somalia\n/\n/\nColumns in Third_Party_Companies and all categories for low cardinality columns :\ncompany_type : Maintenance Contractor, Supplier\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n" }, { "role": "user", "content": "What are the names of all employees who can fly both the Boeing 737-800 and the Airbus A340-300?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.name, Boeing 737-800, Airbus A340-300.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Boeing 737-800\" INTERSECT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Airbus A340-300\"" } ]
[ { "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 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 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 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 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 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 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 \"Accounts\" (\n\t\"Account_ID\" INTEGER NOT NULL, \n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Account_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Account_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Statements\" (\"Statement_ID\")\n)\n/\nColumns in Accounts and 3 examples in each column for high cardinality columns :\nAccount_ID : 321, 427, 240\nAccount_Details : 12223.93, 6352.31, 930.14\n/\n/\nColumns in Accounts and all categories for low cardinality columns :\nStatement_ID : 192, 57\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 \"Users\" (\n\tuser_id INTEGER, \n\trole_code VARCHAR(15) NOT NULL, \n\tuser_name VARCHAR(40), \n\tuser_login VARCHAR(40), \n\tpassword VARCHAR(40), \n\tPRIMARY KEY (user_id), \n\tFOREIGN KEY(role_code) REFERENCES \"Roles\" (role_code)\n)\n/\nColumns in Users and 3 examples in each column for high cardinality columns :\nuser_id : 1, 13, 11\nuser_name : glenna.simonis, jacklyn.schmitt, larson.vesta\npassword : 20241478f890508ac47870cfba472e1db04a71ca, 90db8f51449e6c39e2a01f0b649d5a92fe76bbbb, 27cca8f94136f0e8971b5ca555a21ff756871b27\n/\n/\nColumns in Users and all categories for low cardinality columns :\nrole_code : PROJ-MGR, DBA\nuser_login : 1, 0\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 \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 \"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 \"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 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 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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"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 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" }, { "role": "user", "content": "Show names for all employees who do not have certificate of Boeing 737-800." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: name, Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.name, Boeing 737-800.\nThe SQL query I'll be generating is:\nSELECT name FROM Employee EXCEPT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Boeing 737-800\"" } ]
[ { "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 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 \"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 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 \"Delivery_Route_Locations\" (\n\tlocation_code VARCHAR(10), \n\troute_id INTEGER NOT NULL, \n\tlocation_address_id INTEGER NOT NULL, \n\tlocation_name VARCHAR(50), \n\tPRIMARY KEY (location_code), \n\tFOREIGN KEY(route_id) REFERENCES \"Delivery_Routes\" (route_id), \n\tFOREIGN KEY(location_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Delivery_Route_Locations and 3 examples in each column for high cardinality columns :\nlocation_code : 27 City Rd, 67 LV Rd, 38 Enisner Av\nlocation_address_id : 13, 2, 5\nlocation_name : Rosenbaum, Kiehn and Kilback, Strosin, Hegmann and Abbott, Pouros, Brakus and Konopelski\n/\n/\nColumns in Delivery_Route_Locations and all categories for low cardinality columns :\nroute_id : 13, 11, 2, 15, 7, 8, 4, 14, 10\n/\n \nCREATE TABLE teaches (\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\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 instructor (\"ID\")\n)\n/\nColumns in teaches and 3 examples in each column for high cardinality columns :\nID : 99052, 6569, 79081\ncourse_id : 561, 304, 927\n/\n/\nColumns in teaches 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\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 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 \"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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 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 course (\n\tcourse_id VARCHAR(8), \n\ttitle VARCHAR(50), \n\tdept_name VARCHAR(20), \n\tcredits NUMERIC(2, 0), \n\tPRIMARY KEY (course_id), \n\tFOREIGN KEY(dept_name) REFERENCES department (dept_name), \n\tCHECK (credits > 0)\n)\n/\nColumns in course and 3 examples in each column for high cardinality columns :\ncourse_id : 241, 586, 377\ntitle : Numerical Methods, Thermal Physics, Stream Processing\ndept_name : Math, Athletics, English\n/\n/\nColumns in course and all categories for low cardinality columns :\ncredits : 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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\tcity 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 : 7089 Mueller Forks, 535 Ariel Brook, 3904 Stroman Passage\ncity : Buckridgehaven, South Eugene, Elviebury\nzip_postcode : 22194, 99903, 14445\nstate_province_county : Louisiana, Kentucky, Ohio\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\n/\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 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 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 membership_register_branch (\n\t\"Member_ID\" INTEGER, \n\t\"Branch_ID\" TEXT, \n\t\"Register_Year\" TEXT, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Branch_ID\") REFERENCES branch (\"Branch_ID\")\n)\n/\nColumns in membership_register_branch and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3\nBranch_ID : 1, 2, 5, 8, 4, 6\nRegister_Year : 2016, 2017\n/\n \nCREATE TABLE \"Vehicles\" (\n\tvehicle_id INTEGER, \n\tvehicle_details VARCHAR(255), \n\tPRIMARY KEY (vehicle_id)\n)\n/\nColumns in Vehicles and all categories for low cardinality columns :\nvehicle_id : 1, 2, 3\nvehicle_details : Car, Van, Truck\n/\n" }, { "role": "user", "content": "What are the names of all employees who are not certified to fly Boeing 737-800s?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: name, Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.name, Boeing 737-800.\nThe SQL query I'll be generating is:\nSELECT name FROM Employee EXCEPT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = \"Boeing 737-800\"" } ]
[ { "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\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 \"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 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 \"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 \"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 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 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 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 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 \"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 employee (\n\t\"Fname\" TEXT, \n\t\"Minit\" TEXT, \n\t\"Lname\" TEXT, \n\t\"Ssn\" INTEGER, \n\t\"Bdate\" TEXT, \n\t\"Address\" TEXT, \n\t\"Sex\" TEXT, \n\t\"Salary\" INTEGER, \n\t\"Super_ssn\" INTEGER, \n\t\"Dno\" INTEGER, \n\tPRIMARY KEY (\"Ssn\")\n)\n/\nColumns in employee and all categories for low cardinality columns :\nFname : Joyce, James, Alicia, Ramesh, Franklin, Ahmad, Jonh, Jennifier\nMinit : E, S, K, J, T, A, V, B\nLname : Borg, Narayan, Smith, English, Zelaya, Jabbar, Wallace, Wong\nSsn : 987987987, 333445555, 453453453, 987654321, 123456789, 999887777, 888665555, 666884444\nBdate : 1969-03-29, 1965-01-09, 1955-12-08, 1968-01-19, 1937-11-10, 1972-07-31, 1962-09-15, 1941-06-20\nAddress : 980 Dallas, Houston, TX, 291 Berry, Bellaire, TX, 975 Fire Oak, Humble, TX, 3321 Castle, Spring, TX, 5631 Rice, Houston, TX, 638 Voss, Houston, TX, 450 Stone, Houston, TX, 731 Fondren, Houston, TX\nSex : F, M\nSalary : 43000, 40000, 38000, 25000, 55000, 30000\nSuper_ssn : 333445555, 888665555, 987654321, None\nDno : 1, 4, 5\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 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 captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\n/\n \nCREATE TABLE \"Customers\" (\n\tcustomer_id INTEGER NOT NULL, \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 : 79, 87, 16\ncustomer_details : Esteban Senger, Elva Boehm, Mr. Raul Prosacco\n/\n\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 \"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 \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 \"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 drivers (\n\t\"driverId\" INTEGER, \n\t\"driverRef\" TEXT, \n\tnumber TEXT, \n\tcode TEXT, \n\tforename TEXT, \n\tsurname TEXT, \n\tdob TEXT, \n\tnationality TEXT, \n\turl TEXT, \n\tPRIMARY KEY (\"driverId\")\n)\n/\nColumns in drivers and 3 examples in each column for high cardinality columns :\ndriverId : 87, 56, 65\ndriverRef : prost, katayama, satoru_nakajima\nnumber : , 5, 44\ncode : WEB, FMO, \nforename : Adrian, Gary, Eliseo\nsurname : Blundell, Boullion, Verstappen\ndob : 06/10/1951, 27/11/1957, 23/09/1981\nnationality : Argentine, Colombian, Czech\nurl : http://en.wikipedia.org/wiki/Ricardo_Rosset, http://en.wikipedia.org/wiki/Alex_Zanardi, http://en.wikipedia.org/wiki/Marc_Surer\n/\n\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n" }, { "role": "user", "content": "Show the name of aircraft which fewest people have its certificate." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Aircraft.aid, Certificate.aid.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid GROUP BY T1.aid 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 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 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 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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\n/\n \nCREATE TABLE \"Ref_Detention_Type\" (\n\tdetention_type_code VARCHAR(10), \n\tdetention_type_description VARCHAR(80), \n\tPRIMARY KEY (detention_type_code)\n)\n/\nColumns in Ref_Detention_Type and all categories for low cardinality columns :\ndetention_type_code : LUNCH, BREAK , AFTER\ndetention_type_description : After School, During Break time, Lunch-time\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 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 \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 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 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 \"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 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 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 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" }, { "role": "user", "content": "What are the names of the aircraft that the least people are certified to fly?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Aircraft.aid, Certificate.aid.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid GROUP BY T1.aid 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 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 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 job_history (\n\t\"EMPLOYEE_ID\" DECIMAL(6, 0) NOT NULL, \n\t\"START_DATE\" DATE NOT NULL, \n\t\"END_DATE\" DATE NOT NULL, \n\t\"JOB_ID\" VARCHAR(10) NOT NULL, \n\t\"DEPARTMENT_ID\" DECIMAL(4, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"EMPLOYEE_ID\", \"START_DATE\"), \n\tFOREIGN KEY(\"EMPLOYEE_ID\") REFERENCES employees (\"EMPLOYEE_ID\"), \n\tFOREIGN KEY(\"DEPARTMENT_ID\") REFERENCES departments (\"DEPARTMENT_ID\"), \n\tFOREIGN KEY(\"JOB_ID\") REFERENCES jobs (\"JOB_ID\")\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 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 \"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 \"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 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 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 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 \"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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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)" }, { "role": "user", "content": "Show the name and distance of the aircrafts with more than 5000 distance and which at least 5 people have its certificate." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Aircraft.aid, Certificate.aid, Aircraft.distance.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid WHERE T2.distance > 5000 GROUP BY T1.aid ORDER BY count(*) >= 5" } ]
[ { "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 party_events (\n\t\"Event_ID\" INTEGER, \n\t\"Event_Name\" TEXT, \n\t\"Party_ID\" INTEGER, \n\t\"Member_in_charge_ID\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Member_in_charge_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in party_events and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 7, 8, 4, 6, 3\nEvent_Name : Election Meeting, Annaual Meeting, Conference, Budget Meeting\nParty_ID : 1, 2, 3\nMember_in_charge_ID : 11, 2, 15, 4, 12, 3, 10\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 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 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 \"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 \"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 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 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 \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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 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 \"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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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" }, { "role": "user", "content": "What is the name and distance of every aircraft that can cover a distance of more than 5000 and which at least 5 people can fly?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Aircraft.name, Aircraft.aid, Certificate.aid, Aircraft.distance.\nThe SQL query I'll be generating is:\nSELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid WHERE T2.distance > 5000 GROUP BY T1.aid ORDER BY count(*) >= 5" } ]
[ { "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 \"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 airport (\n\t\"Airport_ID\" INTEGER, \n\t\"Airport_Name\" TEXT, \n\t\"Total_Passengers\" REAL, \n\t\"%_Change_2007\" TEXT, \n\t\"International_Passengers\" REAL, \n\t\"Domestic_Passengers\" REAL, \n\t\"Transit_Passengers\" REAL, \n\t\"Aircraft_Movements\" REAL, \n\t\"Freight_Metric_Tonnes\" REAL, \n\tPRIMARY KEY (\"Airport_ID\")\n)\n/\nColumns in airport and all categories for low cardinality columns :\nAirport_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAirport_Name : Bristol, London Luton, East Midlands, Birmingham Airport, Glasgow International, London Stansted, London Heathrow, London Gatwick, Edinburgh, Manchester\nTotal_Passengers : 8178891.0, 5620673.0, 34205887.0, 9627589.0, 67054745.0, 6267114.0, 10180734.0, 21219195.0, 22360364.0, 9006702.0\n%_Change_2007 : 2.6%, 4.0%, 6.0%, 1.5%, 0.5%, 5.7%, 2.9%, 4.3%, 3.8%, 7.0%\nInternational_Passengers : 3711140.0, 8105162.0, 3943139.0, 19996947.0, 5057051.0, 4870184.0, 8853224.0, 61344438.0, 30431051.0, 18119230.0\nDomestic_Passengers : 746094.0, 5562516.0, 1171605.0, 2943719.0, 1471538.0, 4192121.0, 3730963.0, 1320678.0, 2343428.0, 5281038.0\nTransit_Passengers : 156246.0, 50889.0, 6832.0, 19989.0, 43873.0, 43631.0, 14524.0, 38458.0, 4395.0, 147791.0\nAircraft_Movements : 478693.0, 117859.0, 204610.0, 193282.0, 125550.0, 76517.0, 112227.0, 100087.0, 93038.0, 263653.0\nFreight_Metric_Tonnes : 3.0, 261507.0, 12418.0, 40518.0, 197738.0, 141781.0, 107702.0, 3546.0, 12192.0, 1397054.0\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 \"Authors\" (\n\t\"authID\" INTEGER, \n\tlname TEXT, \n\tfname TEXT, \n\tPRIMARY KEY (\"authID\")\n)\n/\nColumns in Authors and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\nlname : Gibbons, Turon, Ueno\nfname : Daniel W. H., Tim, Ralf\n/\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 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 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 \"Customers\" (\n\tcustomer_id INTEGER NOT NULL, \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 : 79, 87, 16\ncustomer_details : Esteban Senger, Elva Boehm, Mr. Raul Prosacco\n/\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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\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 department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\n/\n \nCREATE TABLE captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 railway_manage (\n\t\"Railway_ID\" INTEGER, \n\t\"Manager_ID\" INTEGER, \n\t\"From_Year\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\", \"Manager_ID\"), \n\tFOREIGN KEY(\"Manager_ID\") REFERENCES manager (\"Manager_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/\nColumns in railway_manage and all categories for low cardinality columns :\nRailway_ID : 7, 8, 2, 9\nManager_ID : 1, 2, 4, 3\nFrom_Year : 2012, 2010, 2011, 2013\n/\n \nCREATE TABLE \"Invoices\" (\n\tinvoice_number INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_date DATETIME, \n\tPRIMARY KEY (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 2018-03-16 21:57:43, 2018-03-20 00:21:41, 2018-03-05 08:47:33\n/\n/\nColumns in Invoices and all categories for low cardinality columns :\norder_id : 13, 11, 5, 8, 4, 12, 3, 14, 10, 9\n/\n" }, { "role": "user", "content": "what is the salary and name of the employee who has the most number of aircraft certificates?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.salary, Employee.eid, Certificate.eid.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.salary FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid GROUP BY T1.eid 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 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 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 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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Document_Structures\" (\n\tdocument_structure_code VARCHAR(15), \n\tparent_document_structure_code VARCHAR(15), \n\tdocument_structure_description VARCHAR(80), \n\tPRIMARY KEY (document_structure_code)\n)\n/\nColumns in Document_Structures and all categories for low cardinality columns :\ndocument_structure_code : 1, 5, 8, 6, 9\nparent_document_structure_code : 1, 8, 6\ndocument_structure_description : Main section, Image section, Header, Bib, Author section\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 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 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 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 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 \"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 \"Maintenance_Engineers\" (\n\tengineer_id INTEGER, \n\tcompany_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(50), \n\tlast_name VARCHAR(50), \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (engineer_id), \n\tFOREIGN KEY(company_id) REFERENCES \"Third_Party_Companies\" (company_id)\n)\n/\nColumns in Maintenance_Engineers and 3 examples in each column for high cardinality columns :\nengineer_id : 1, 13, 11\ncompany_id : 1, 11, 10\nfirst_name : Lorine, Weston, Josie\nlast_name : Harvey, Hirthe, Goldner\n/\n/\nColumns in Maintenance_Engineers and all categories for low cardinality columns :\nother_details : None, Skilled\n/\n \nCREATE TABLE \"Theme_Parks\" (\n\t\"Theme_Park_ID\" INTEGER NOT NULL, \n\t\"Theme_Park_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Theme_Park_ID\"), \n\tFOREIGN KEY(\"Theme_Park_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Theme_Parks and all categories for low cardinality columns :\nTheme_Park_ID : 6523, 5265, 6476\nTheme_Park_Details : Sea World, Universal Studios, Disney\n/\n \nCREATE TABLE employee (\n\t\"Fname\" TEXT, \n\t\"Minit\" TEXT, \n\t\"Lname\" TEXT, \n\t\"Ssn\" INTEGER, \n\t\"Bdate\" TEXT, \n\t\"Address\" TEXT, \n\t\"Sex\" TEXT, \n\t\"Salary\" INTEGER, \n\t\"Super_ssn\" INTEGER, \n\t\"Dno\" INTEGER, \n\tPRIMARY KEY (\"Ssn\")\n)\n/\nColumns in employee and all categories for low cardinality columns :\nFname : Joyce, James, Alicia, Ramesh, Franklin, Ahmad, Jonh, Jennifier\nMinit : E, S, K, J, T, A, V, B\nLname : Borg, Narayan, Smith, English, Zelaya, Jabbar, Wallace, Wong\nSsn : 987987987, 333445555, 453453453, 987654321, 123456789, 999887777, 888665555, 666884444\nBdate : 1969-03-29, 1965-01-09, 1955-12-08, 1968-01-19, 1937-11-10, 1972-07-31, 1962-09-15, 1941-06-20\nAddress : 980 Dallas, Houston, TX, 291 Berry, Bellaire, TX, 975 Fire Oak, Humble, TX, 3321 Castle, Spring, TX, 5631 Rice, Houston, TX, 638 Voss, Houston, TX, 450 Stone, Houston, TX, 731 Fondren, Houston, TX\nSex : F, M\nSalary : 43000, 40000, 38000, 25000, 55000, 30000\nSuper_ssn : 333445555, 888665555, 987654321, None\nDno : 1, 4, 5\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 captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n" }, { "role": "user", "content": "What is the salaray and name of the employee that is certified to fly the most planes?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.salary, Employee.eid, Certificate.eid.\nThe SQL query I'll be generating is:\nSELECT T1.name , T1.salary FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid GROUP BY T1.eid 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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\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 \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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 \"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 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 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 \"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 project (\n\t\"Pname\" TEXT, \n\t\"Pnumber\" INTEGER, \n\t\"Plocation\" TEXT, \n\t\"Dnum\" INTEGER, \n\tPRIMARY KEY (\"Pnumber\")\n)\n/\nColumns in project and all categories for low cardinality columns :\nPname : Newbenefits, Reorganization, ProductX, Computerization, ProductZ, ProductY\nPnumber : 1, 20, 2, 30, 3, 10\nPlocation : Stafford, Sugarland, Bellaire, Houston\nDnum : 1, 4, 5\n/\n \nCREATE TABLE \"Catalog_Contents\" (\n\tcatalog_entry_id INTEGER, \n\tcatalog_level_number INTEGER NOT NULL, \n\tparent_entry_id INTEGER, \n\tprevious_entry_id INTEGER, \n\tnext_entry_id INTEGER, \n\tcatalog_entry_name VARCHAR(80), \n\tproduct_stock_number VARCHAR(50), \n\tprice_in_dollars DOUBLE, \n\tprice_in_euros DOUBLE, \n\tprice_in_pounds DOUBLE, \n\tcapacity VARCHAR(20), \n\tlength VARCHAR(20), \n\theight VARCHAR(20), \n\twidth VARCHAR(20), \n\tPRIMARY KEY (catalog_entry_id), \n\tFOREIGN KEY(catalog_level_number) REFERENCES \"Catalog_Structure\" (catalog_level_number)\n)\n/\nColumns in Catalog_Contents and 3 examples in each column for high cardinality columns :\ncatalog_entry_id : 1, 13, 11\ncatalog_entry_name : Cream Soda, Diet Pepsi, Ramune\nproduct_stock_number : 15 mr, 42 cp, 26 op\nprice_in_dollars : 475.79, 687.59, 616.22\nprice_in_euros : 385.85, 159.84, 537.66\nprice_in_pounds : 440.52, 405.75, 331.43\n/\n/\nColumns in Catalog_Contents and all categories for low cardinality columns :\ncatalog_level_number : 1, 8, 9\nparent_entry_id : 5, 7, 4, 6, 3\nprevious_entry_id : 5, 7, 8, 4, 6, 3, 9\nnext_entry_id : 1, 7, 8, 6, 3, 9\ncapacity : 1, 5, 7, 8, 4, 6, 9\nlength : 5, 7, 8, 4, 6, 3, 9\nheight : 1, 2, 5, 7, 8, 4, 6, 3, 9\nwidth : 1, 5, 7, 8, 6, 3, 9\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 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 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 is the salary and name of the employee who has the most number of certificates on aircrafts with distance more than 5000?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.distance.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.distance > 5000 GROUP BY T1.eid 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 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 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 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 certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\n\n \nCREATE TABLE \"Appointment\" (\n\t\"AppointmentID\" INTEGER NOT NULL, \n\t\"Patient\" INTEGER NOT NULL, \n\t\"PrepNurse\" INTEGER, \n\t\"Physician\" INTEGER NOT NULL, \n\t\"Start\" DATETIME NOT NULL, \n\t\"End\" DATETIME NOT NULL, \n\t\"ExaminationRoom\" TEXT NOT NULL, \n\tPRIMARY KEY (\"AppointmentID\"), \n\tCONSTRAINT \"fk_Appointment_Patient_SSN\" FOREIGN KEY(\"Patient\") REFERENCES \"Patient\" (\"SSN\"), \n\tCONSTRAINT \"fk_Appointment_Nurse_EmployeeID\" FOREIGN KEY(\"PrepNurse\") REFERENCES \"Nurse\" (\"EmployeeID\"), \n\tCONSTRAINT \"fk_Appointment_Physician_EmployeeID\" FOREIGN KEY(\"Physician\") REFERENCES \"Physician\" (\"EmployeeID\")\n)\n/\nColumns in Appointment and all categories for low cardinality columns :\nAppointmentID : 59871321, 13216584, 46846589, 26548913, 69879231, 76983231, 36549879, 86213939, 93216548\nPatient : 100000001, 100000002, 100000004, 100000003\nPrepNurse : 102, 101, None, 103\nPhysician : 1, 2, 4, 3, 9\nStart : 2008-04-24 10:00:00, 2008-04-25 10:00:00, 2008-04-26 11:00:00, 2008-04-26 10:00:00, 2008-04-26 12:00:00, 2008-04-27 10:00:00\nEnd : 2008-04-25 11:00:00, 2008-04-26 13:00:00, 2008-04-27 11:00:00, 2008-04-21 11:00:00, 2008-04-26 11:00:00, 2008-04-24 11:00:00, 2008-04-26 12:00:00\nExaminationRoom : A, C, B\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 medicine (\n\tid INTEGER, \n\tname TEXT, \n\t\"Trade_Name\" TEXT, \n\t\"FDA_approved\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in medicine and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Quetiapine, Carpipramine, Asenapine\nTrade_Name : Buronil, Fanapt, Nipolept\n/\n/\nColumns in medicine and all categories for low cardinality columns :\nFDA_approved : Yes, No\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 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 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 player (\n\t\"Player_ID\" INTEGER, \n\tname TEXT, \n\t\"Position\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Apps\" REAL, \n\t\"Tries\" REAL, \n\t\"Goals\" TEXT, \n\t\"Points\" REAL, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nname : Michael Platt, Tame Tupou, Terry Newton\nApps : 30.0, 29.0, 24.0\n/\n/\nColumns in player and all categories for low cardinality columns :\nPosition : Scrum Half, Right Centre, Prop, Loose Forward, Hooker, Right Wing, Stand Off, Second Row, Left Wing, Full Back\nClub_ID : 1, 2, 5, 4, 3\nTries : 3.0, 8.0, 1.0, 6.0, 9.0, 2.0, 4.0, 5.0\nGoals : 50/60, 90/106, 0/1, 0\nPoints : 36.0, 8.0, 16.0, 12.0, 24.0, 188.0, 32.0, 110.0, 4.0, 20.0\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 \"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 \"Candidates\" (\n\tcandidate_id INTEGER NOT NULL, \n\tcandidate_details VARCHAR(255), \n\tPRIMARY KEY (candidate_id), \n\tFOREIGN KEY(candidate_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Candidates and all categories for low cardinality columns :\ncandidate_id : 151, 141, 131, 171, 111, 161, 181, 121\ncandidate_details : Cindy, Robin, Jane, Leo, Alex, Jack, Robert, Tao\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 medicine_enzyme_interaction (\n\tenzyme_id INTEGER, \n\tmedicine_id INTEGER, \n\tinteraction_type TEXT, \n\tPRIMARY KEY (enzyme_id, medicine_id), \n\tFOREIGN KEY(medicine_id) REFERENCES medicine (id), \n\tFOREIGN KEY(enzyme_id) REFERENCES enzyme (id)\n)\n/\nColumns in medicine_enzyme_interaction and 3 examples in each column for high cardinality columns :\nmedicine_id : 1, 13, 20\n/\n/\nColumns in medicine_enzyme_interaction and all categories for low cardinality columns :\nenzyme_id : 1, 2, 5, 4, 6, 3\ninteraction_type : inhibitor, activitor\n/\n \nCREATE TABLE farm (\n\t\"Farm_ID\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"Total_Horses\" REAL, \n\t\"Working_Horses\" REAL, \n\t\"Total_Cattle\" REAL, \n\t\"Oxen\" REAL, \n\t\"Bulls\" REAL, \n\t\"Cows\" REAL, \n\t\"Pigs\" REAL, \n\t\"Sheep_and_Goats\" REAL, \n\tPRIMARY KEY (\"Farm_ID\")\n)\n/\nColumns in farm and all categories for low cardinality columns :\nFarm_ID : 1, 2, 5, 7, 8, 4, 6, 3\nYear : 1932, 1928, 1930, 1931, 1927, 1934, 1929, 1933\nTotal_Horses : 3658.9, 5056.5, 2546.9, 5607.5, 4781.3, 5308.2, 5486.9, 2604.8\nWorking_Horses : 3721.6, 3711.2, 3900.1, 3711.6, 4090.5, 4198.8, 2197.3, 3593.7\nTotal_Cattle : 6274.1, 4446.3, 6189.5, 8374.5, 5277.5, 7611.0, 5006.7, 8604.8\nOxen : 805.5, 895.3, 156.5, 593.7, 116.9, 113.8, 254.8, 105.2\nBulls : 49.6, 71.6, 40.0, 26.9, 32.8, 31.6, 37.6, 46.7\nCows : 3852.1, 2739.5, 2518.0, 2407.2, 3377.0, 3987.0, 3873.0, 3471.6\nPigs : 3171.8, 4236.7, 4161.2, 2089.2, 4412.4, 3373.3, 6962.9, 2623.7\nSheep_and_Goats : 7956.3, 7030.8, 2197.1, 2004.7, 3364.8, 4533.4, 2109.5, 8112.2\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" }, { "role": "user", "content": "What is the salaray and name of the employee with the most certificates to fly planes more than 5000?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Employee, Certificate, Aircraft.\nFrom these tables, I'll be using the following columns: Employee.name, Employee.eid, Certificate.eid, Aircraft.aid, Certificate.aid, Aircraft.distance.\nThe SQL query I'll be generating is:\nSELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.distance > 5000 GROUP BY T1.eid 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 \"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 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 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 \"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 \"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 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 \"Product\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Product and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : life, messager, wechat\nproduct_details : d, m, q\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 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 \"Engineer_Visits\" (\n\tengineer_visit_id INTEGER, \n\tcontact_staff_id INTEGER, \n\tengineer_id INTEGER NOT NULL, \n\tfault_log_entry_id INTEGER NOT NULL, \n\tfault_status VARCHAR(10) NOT NULL, \n\tvisit_start_datetime DATETIME, \n\tvisit_end_datetime DATETIME, \n\tother_visit_details VARCHAR(255), \n\tPRIMARY KEY (engineer_visit_id), \n\tFOREIGN KEY(contact_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(engineer_id) REFERENCES \"Maintenance_Engineers\" (engineer_id), \n\tFOREIGN KEY(fault_log_entry_id) REFERENCES \"Fault_Log\" (fault_log_entry_id)\n)\n/\nColumns in Engineer_Visits and 3 examples in each column for high cardinality columns :\nengineer_visit_id : 1, 13, 11\nvisit_start_datetime : 2015-07-05 21:37:55, 1997-06-23 17:45:21, 1996-11-07 05:31:35\nvisit_end_datetime : 2012-11-27 06:26:01, 1970-03-25 14:44:29, 2000-01-27 09:33:10\n/\n/\nColumns in Engineer_Visits and all categories for low cardinality columns :\ncontact_staff_id : 2, 7, 8, 4, 6, 12, 14, 9\nengineer_id : 1, 11, 15, 8, 4, 6, 12, 10\nfault_log_entry_id : 3, 13, 11, 2, 8, 4, 14, 12, 10\nfault_status : Fixed, Reported, Return, Waiting\nother_visit_details : None\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 \"Benefits_Overpayments\" (\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 Benefits_Overpayments and all categories for low cardinality columns :\ncouncil_tax_id : 7, 8, 6, 3\ncmi_cross_ref_id : 83, 65, 41, 48\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 \"Document_Structures\" (\n\tdocument_structure_code VARCHAR(15), \n\tparent_document_structure_code VARCHAR(15), \n\tdocument_structure_description VARCHAR(80), \n\tPRIMARY KEY (document_structure_code)\n)\n/\nColumns in Document_Structures and all categories for low cardinality columns :\ndocument_structure_code : 1, 5, 8, 6, 9\nparent_document_structure_code : 1, 8, 6\ndocument_structure_description : Main section, Image section, Header, Bib, Author section\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 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 \"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 \"Benefits_Overpayments\" (\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 Benefits_Overpayments and all categories for low cardinality columns :\ncouncil_tax_id : 7, 8, 6, 3\ncmi_cross_ref_id : 83, 65, 41, 48\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 \"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 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" }, { "role": "user", "content": "How many allergies are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergy.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT allergy) FROM Allergy_type" } ]
[ { "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 \"Medication\" (\n\t\"Code\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Brand\" VARCHAR(30) NOT NULL, \n\t\"Description\" VARCHAR(30) NOT NULL, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Medication and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 3\nName : Melioraurin, Procrastin-X, Awakin, Crescavitin, Thesisin\nBrand : Snafu Pharmaceuticals, Baz Industries, Bar Laboratories, Foo Labs, X\nDescription : N/A\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 \"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 \"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 phone (\n\t\"Company_name\" TEXT, \n\t\"Hardware_Model_name\" TEXT, \n\t\"Accreditation_type\" TEXT, \n\t\"Accreditation_level\" TEXT, \n\t\"Date\" TEXT, \n\tchip_model TEXT, \n\tscreen_mode TEXT, \n\tPRIMARY KEY (\"Hardware_Model_name\"), \n\tFOREIGN KEY(chip_model) REFERENCES chip_model (\"Model_name\"), \n\tFOREIGN KEY(screen_mode) REFERENCES screen_mode (\"Graphics_mode\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nCompany_name : Samsung Electronics Co Ltd, Huawei Technologies Co.Ltd., HTC Corporation, Nokia Corporation, LG Electronics, Sony Mobile Communications\nHardware_Model_name : GT-I9300, U8815 Asura, Lumia 920, Lumia 820, Lumia 620, GT-I9100, Nokia 700, LG-P760, Z520e, XPERIA T, XPERIA J\nAccreditation_type : Provisional, Full\nAccreditation_level : joyn Hot Fixes, joyn\nDate : Approved (valid until 03.05.13), Approved (valid until 06.04.13), Approved (awarded 19.11.12), Approved (awarded 05.12.12), Approved (valid until 14.09.13), Approved (awarded 23.10.12), Approved (awarded 15.11.12)\nchip_model : X50 Advanced, X5, X3i, X51v, X30 low-end, X50 Standard\nscreen_mode : 1, 2, 5, 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 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 \"Player_Attributes\" (\n\tid INTEGER, \n\tplayer_fifa_api_id INTEGER, \n\tplayer_api_id INTEGER, \n\tdate TEXT, \n\toverall_rating INTEGER, \n\tpotential INTEGER, \n\tpreferred_foot TEXT, \n\tattacking_work_rate TEXT, \n\tdefensive_work_rate TEXT, \n\tcrossing INTEGER, \n\tfinishing INTEGER, \n\theading_accuracy INTEGER, \n\tshort_passing INTEGER, \n\tvolleys INTEGER, \n\tdribbling INTEGER, \n\tcurve INTEGER, \n\tfree_kick_accuracy INTEGER, \n\tlong_passing INTEGER, \n\tball_control INTEGER, \n\tacceleration INTEGER, \n\tsprint_speed INTEGER, \n\tagility INTEGER, \n\treactions INTEGER, \n\tbalance INTEGER, \n\tshot_power INTEGER, \n\tjumping INTEGER, \n\tstamina INTEGER, \n\tstrength INTEGER, \n\tlong_shots INTEGER, \n\taggression INTEGER, \n\tinterceptions INTEGER, \n\tpositioning INTEGER, \n\tvision INTEGER, \n\tpenalties INTEGER, \n\tmarking INTEGER, \n\tstanding_tackle INTEGER, \n\tsliding_tackle INTEGER, \n\tgk_diving INTEGER, \n\tgk_handling INTEGER, \n\tgk_kicking INTEGER, \n\tgk_positioning INTEGER, \n\tgk_reflexes INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(player_api_id) REFERENCES \"Player\" (player_api_id), \n\tFOREIGN KEY(player_fifa_api_id) REFERENCES \"Player\" (player_fifa_api_id)\n)\n/\nColumns in Player_Attributes and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\nplayer_fifa_api_id : 186170, 221280, 189615\nplayer_api_id : 30895, 30572, 162549\ndate : 2013-11-01 00:00:00, 2013-09-20 00:00:00, 2007-08-30 00:00:00\noverall_rating : 79, 53, 65\npotential : 79, 87, 56\ncrossing : 79, 56, 78\nfinishing : 79, 53, 56\nheading_accuracy : 79, 56, 65\nshort_passing : 79, 53, 65\nvolleys : 56, 44, 63\ndribbling : 79, 53, 56\ncurve : 79, 56, 65\nfree_kick_accuracy : 53, 65, 63\nlong_passing : 53, 65, 49\nball_control : 79, 65, 78\nacceleration : 79, 53, 78\nsprint_speed : 79, 53, 78\nagility : 79, 78, 49\nreactions : 79, 56, 65\nbalance : 87, 79, 56\nshot_power : 53, 56, 65\njumping : 56, 65, 78\nstamina : 79, 87, 56\nstrength : 87, 56, 78\nlong_shots : 53, 56, 78\naggression : 56, 65, 75\ninterceptions : 56, 65, 44\npositioning : 79, 56, 78\nvision : 79, 53, 65\npenalties : 53, 56, 36\nmarking : 79, 53, 65\nstanding_tackle : 79, 56, 78\nsliding_tackle : 56, 78, 65\ngk_diving : 53, 16, 13\ngk_handling : 41, 13, 20\ngk_kicking : 65, 49, 63\ngk_positioning : 16, 13, 20\ngk_reflexes : 53, 13, 20\n/\n/\nColumns in Player_Attributes and all categories for low cardinality columns :\npreferred_foot : left, right\nattacking_work_rate : high, medium\ndefensive_work_rate : high, medium\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 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 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 \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 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 \"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" }, { "role": "user", "content": "How many allergy entries are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergy.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT allergy) FROM Allergy_type" } ]
[ { "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 \"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 \"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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 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 \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1 VARCHAR(120), \n\tline_2 VARCHAR(120), \n\tline_3 VARCHAR(120), \n\tcity VARCHAR(80), \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 : 17, 9, 16\nline_1 : 056 Murphy Stravenue Apt. 600, 39834 Anne Mission Apt. 956, 18327 Jaime Terrace Suite 343\ncity : North Jayceton, Elinoreport, Hegmannborough\nzip_postcode : 937, 002, 607\nstate_province_county : Hawaii, Tennessee, NewYork\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\nline_2 : None\nline_3 : None\ncountry : USA\nother_address_details : None\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 \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 \"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 \"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 \"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 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 \"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 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 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 \"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 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 \"Organizations\" (\n\torganization_id INTEGER NOT NULL, \n\tparent_organization_id INTEGER, \n\torganization_details VARCHAR(255), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 7, 8, 10\nparent_organization_id : 7, 8\norganization_details : Denesik and Sons Party, Reinger, Hudson and Nolan Group, Robel-Schulist Group\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 \"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 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" }, { "role": "user", "content": "How many different allergy types exist?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT allergytype) FROM Allergy_type" } ]
[ { "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 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 \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(15), \n\tproduct_name VARCHAR(80), \n\tproduct_price DOUBLE, \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_price : 5927021.8748021, 622.79275984494, 22956668.699482\n/\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_type_code : Hardware, Clothes\nproduct_name : Apple, jcrew, Sony, gucci\n/\n \nCREATE TABLE \"Images\" (\n\timage_id INTEGER, \n\timage_alt_text VARCHAR(80), \n\timage_name VARCHAR(40), \n\timage_url VARCHAR(255), \n\tPRIMARY KEY (image_id)\n)\n/\nColumns in Images and 3 examples in each column for high cardinality columns :\nimage_id : 1, 13, 11\nimage_alt_text : Chaya, Ashtyn, Marianna\nimage_name : chapter3, data1, data2\nimage_url : http://www.bernierconnelly.com/1.jpg, http://www.hermann.com/1.jpg, http://connellykertzmann.org/1.jpg\n/\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 \"Features\" (\n\t\"Feature_ID\" INTEGER NOT NULL, \n\t\"Feature_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Feature_ID\")\n)\n/\nColumns in Features and all categories for low cardinality columns :\nFeature_ID : 955, 543, 681, 528, 523\nFeature_Details : park, shopping, cafe, parking, garden\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 \"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 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 \"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 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 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 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 genres (\n\tid INTEGER, \n\tname VARCHAR(120), \n\tPRIMARY KEY (id)\n)\n/\nColumns in genres and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Bossa Nova, Comedy, Opera\n/\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 \"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 \"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 NOT NULL, \n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\torder_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 :\norder_item_id : 1, 13, 11\norder_id : 13, 11, 5\n/\n/\nColumns in Order_Items and all categories for low cardinality columns :\nproduct_id : 13, 11, 2, 5, 4, 6, 12, 3, 15, 9\norder_quantity : 2, 5, 7, 8, 4, 3, 9, male\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 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 \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\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" }, { "role": "user", "content": "How many distinct allergies are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT allergytype) FROM Allergy_type" } ]
[ { "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 \"Statements\" (\n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Statement_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Statement_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/\nColumns in Statements and all categories for low cardinality columns :\nStatement_ID : 192, 57\nStatement_Details : Private Project, Open Project\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 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\" (\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 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 \"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 \"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 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 \"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 \"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 \"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 \"Available_Policies\" (\n\t\"Policy_ID\" INTEGER NOT NULL, \n\tpolicy_type_code CHAR(15), \n\t\"Customer_Phone\" VARCHAR(255), \n\tPRIMARY KEY (\"Policy_ID\"), \n\tUNIQUE (\"Policy_ID\")\n)\n/\nColumns in Available_Policies and 3 examples in each column for high cardinality columns :\nPolicy_ID : 751, 300, 586\nCustomer_Phone : (777)537-7792, 991.642.6485x822, 1-797-927-3585x9321\n/\n/\nColumns in Available_Policies and all categories for low cardinality columns :\npolicy_type_code : Property Insurance, Mortgage Insurance, Life Insurance, Travel Insurance\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 \"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 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 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 \"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 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 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 \"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" }, { "role": "user", "content": "Show all allergy types." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT DISTINCT allergytype FROM Allergy_type" } ]
[ { "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 \"Parts\" (\n\tpart_id INTEGER, \n\tpart_name VARCHAR(255), \n\tchargeable_yn VARCHAR(1), \n\tchargeable_amount VARCHAR(20), \n\tother_part_details VARCHAR(255), \n\tPRIMARY KEY (part_id)\n)\n/\nColumns in Parts and all categories for low cardinality columns :\npart_id : 1, 2, 3\npart_name : top, middle, package\nchargeable_yn : 1, 0\nchargeable_amount : 4, 9\nother_part_details : None\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 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 \"Suppliers\" (\n\tsupplier_id INTEGER, \n\tsupplier_name VARCHAR(80), \n\tsupplier_phone VARCHAR(80), \n\tPRIMARY KEY (supplier_id)\n)\n/\nColumns in Suppliers and all categories for low cardinality columns :\nsupplier_id : 1, 2, 4, 3\nsupplier_name : Tesco, Lidl, AB Store, Audi\nsupplier_phone : 287-071-1153x254, (692)009-5928, 1-432-960-2402x1734, 1-483-283-4742\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 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 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 \"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 \"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 \"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 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 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 \"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 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 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 \"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 \"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 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 \"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" }, { "role": "user", "content": "What are the different allergy types?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT DISTINCT allergytype FROM Allergy_type" } ]
[ { "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 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 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 \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 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 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 \"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 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 party_events (\n\t\"Event_ID\" INTEGER, \n\t\"Event_Name\" TEXT, \n\t\"Party_ID\" INTEGER, \n\t\"Member_in_charge_ID\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Member_in_charge_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in party_events and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 7, 8, 4, 6, 3\nEvent_Name : Election Meeting, Annaual Meeting, Conference, Budget Meeting\nParty_ID : 1, 2, 3\nMember_in_charge_ID : 11, 2, 15, 4, 12, 3, 10\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 \"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 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 \"CMI_Cross_References\" (\n\tcmi_cross_ref_id INTEGER NOT NULL, \n\tmaster_customer_id INTEGER NOT NULL, \n\tsource_system_code CHAR(15) NOT NULL, \n\tPRIMARY KEY (cmi_cross_ref_id), \n\tFOREIGN KEY(master_customer_id) REFERENCES \"Customer_Master_Index\" (master_customer_id)\n)\n/\nColumns in CMI_Cross_References and 3 examples in each column for high cardinality columns :\ncmi_cross_ref_id : 65, 75, 102\n/\n/\nColumns in CMI_Cross_References and all categories for low cardinality columns :\nmaster_customer_id : 1, 2, 5, 4, 3, 9\nsource_system_code : Rent, Electoral, Business, Parking, Tax, Benefits\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 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 \"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 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 \"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 \"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 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 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 railway_manage (\n\t\"Railway_ID\" INTEGER, \n\t\"Manager_ID\" INTEGER, \n\t\"From_Year\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\", \"Manager_ID\"), \n\tFOREIGN KEY(\"Manager_ID\") REFERENCES manager (\"Manager_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/\nColumns in railway_manage and all categories for low cardinality columns :\nRailway_ID : 7, 8, 2, 9\nManager_ID : 1, 2, 4, 3\nFrom_Year : 2012, 2010, 2011, 2013\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" }, { "role": "user", "content": "Show all allergies and their types." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergy, allergytype.\nThe SQL query I'll be generating is:\nSELECT allergy , allergytype FROM Allergy_type" } ]
[ { "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_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 \"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 college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\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 \"Product\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Product and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : life, messager, wechat\nproduct_details : d, m, q\n/\n\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 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 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 flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE \"Ref_Service_Types\" (\n\t\"Service_Type_Code\" CHAR(15) NOT NULL, \n\t\"Parent_Service_Type_Code\" CHAR(15), \n\t\"Service_Type_Description\" VARCHAR(255), \n\tPRIMARY KEY (\"Service_Type_Code\"), \n\tUNIQUE (\"Service_Type_Code\")\n)\n/\nColumns in Ref_Service_Types and all categories for low cardinality columns :\nService_Type_Code : 1, 2, 4, 3\nParent_Service_Type_Code : 1\nService_Type_Description : provide photo service, provide dinning service, provide adv promoting service, provide filming service\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 \"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 \"Organization_Contact_Individuals\" (\n\tindividual_id INTEGER NOT NULL, \n\torganization_id INTEGER NOT NULL, \n\tdate_contact_from DATETIME NOT NULL, \n\tdate_contact_to DATETIME, \n\tPRIMARY KEY (individual_id, organization_id), \n\tFOREIGN KEY(individual_id) REFERENCES \"Individuals\" (individual_id), \n\tFOREIGN KEY(organization_id) REFERENCES \"Organizations\" (organization_id)\n)\n/\nColumns in Organization_Contact_Individuals and 3 examples in each column for high cardinality columns :\ndate_contact_from : 2016-07-26 09:08:15, 2016-04-21 03:55:35, 2017-01-06 09:38:54\ndate_contact_to : 2018-03-24 16:54:36, 2018-03-07 16:40:29, 2018-03-06 21:22:49\n/\n/\nColumns in Organization_Contact_Individuals and all categories for low cardinality columns :\nindividual_id : 13, 11, 5, 7, 8, 6, 14, 10, 9\norganization_id : 1, 2, 5, 4, 3\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 \"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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 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 \"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" }, { "role": "user", "content": "What are the allergies and their types?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergy, allergytype.\nThe SQL query I'll be generating is:\nSELECT allergy , allergytype FROM Allergy_type" } ]
[ { "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 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 temperature (\n\t\"City_ID\" INTEGER, \n\t\"Jan\" REAL, \n\t\"Feb\" REAL, \n\t\"Mar\" REAL, \n\t\"Apr\" REAL, \n\t\"Jun\" REAL, \n\t\"Jul\" REAL, \n\t\"Aug\" REAL, \n\t\"Sep\" REAL, \n\t\"Oct\" REAL, \n\t\"Nov\" REAL, \n\t\"Dec\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"City_ID\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in temperature and all categories for low cardinality columns :\nCity_ID : 1, 11, 2, 7, 4, 6, 3, 10\nJan : 18.9, 25.6, 18.3, 26.1, 17.8, 26.7, 17.2\nFeb : 18.9, 18.3, 26.1, 27.2, 17.8, 26.6, 17.2\nMar : 19.4, 18.3, 26.1, 26.6, 27.8\nApr : 18.9, 26.1, 20.6, 28.3, 27.8, 20.0\nJun : 22.8, 30.0, 30.6, 22.2, 20.6, 28.3, 27.8, 20.0\nJul : 31.1, 23.3, 28.9, 30.6, 20.6, 21.7, 27.8\nAug : 31.1, 31.7, 23.9, 23.3, 29.4, 20.6, 21.7, 28.3\nSep : 31.1, 21.1, 31.7, 23.3, 29.4, 20.6, 28.3\nOct : 22.8, 30.6, 28.9, 20.6, 28.3, 20.0\nNov : 19.4, 27.2, 28.9, 21.7, 20.0\nDec : 18.3, 26.1, 26.7, 27.8, 20.0\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 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 \"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 \"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 \"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 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 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_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 \"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 \"Product\" (\n\tproduct_id INTEGER, \n\tproduct_name VARCHAR(80), \n\tproduct_details VARCHAR(255), \n\tPRIMARY KEY (product_id)\n)\n/\nColumns in Product and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : life, messager, wechat\nproduct_details : d, m, q\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 \"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 \"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 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 \"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 \"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 \"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" }, { "role": "user", "content": "Show all allergies with type food." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergy, allergytype, food.\nThe SQL query I'll be generating is:\nSELECT DISTINCT allergy FROM Allergy_type WHERE allergytype = \"food\"" } ]
[ { "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 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 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 school_details (\n\t\"School_ID\" INTEGER, \n\t\"Nickname\" TEXT, \n\t\"Colors\" TEXT, \n\t\"League\" TEXT, \n\t\"Class\" TEXT, \n\t\"Division\" TEXT, \n\tPRIMARY KEY (\"School_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in school_details and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nNickname : Auks, Raiders, Silver Eagles, Seahawks, Buccaneers, Tigers\nColors : Dark Green and White, Blue and Yellow, Maroon and White, Blue and Gold, Garnet and White, Silver and Maroon\nLeague : DSHA\nClass : Flight B, Flight A, Fight A\nDivision : Division 1, Division 2, Division 3\n/\n \nCREATE TABLE news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\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 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 \"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 \"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 \"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 \"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 \"Lessons\" (\n\tlesson_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tlesson_status_code VARCHAR(15) NOT NULL, \n\tstaff_id INTEGER, \n\tvehicle_id INTEGER NOT NULL, \n\tlesson_date DATETIME, \n\tlesson_time VARCHAR(10), \n\tprice DOUBLE, \n\tPRIMARY KEY (lesson_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(vehicle_id) REFERENCES \"Vehicles\" (vehicle_id)\n)\n/\nColumns in Lessons and 3 examples in each column for high cardinality columns :\nlesson_id : 1, 13, 11\nlesson_date : 2018-03-03 15:10:16, 2018-03-07 16:12:36, 2018-03-08 16:05:05\nprice : 306.0, 492.0, 446.0\n/\n/\nColumns in Lessons and all categories for low cardinality columns :\ncustomer_id : 13, 11, 2, 5, 8, 6, 3, 10, 9\nlesson_status_code : Completed, Cancelled\nstaff_id : 1, 11, 5, 8, 4, 14, 3, 12, 15\nvehicle_id : 1, 2, 3\nlesson_time : 2, 5, 4, 6, 3, 9\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 \"Course\" (\n\t\"CID\" VARCHAR(7), \n\t\"CName\" VARCHAR(40), \n\t\"Credits\" INTEGER, \n\t\"Instructor\" INTEGER, \n\t\"Days\" VARCHAR(5), \n\t\"Hours\" VARCHAR(11), \n\t\"DNO\" INTEGER, \n\tPRIMARY KEY (\"CID\"), \n\tFOREIGN KEY(\"Instructor\") REFERENCES \"Faculty\" (\"FacID\"), \n\tFOREIGN KEY(\"DNO\") REFERENCES \"Department\" (\"DNO\")\n)\n/\nColumns in Course and 3 examples in each column for high cardinality columns :\nCID : 600.433, 550.413, 050.381\nCName : UNIX SYSTEMS PROGRAMMING, BUSINESS LAW II, HIGH PERFORMANCE GRAPHICS AND MODELING\nInstructor : 6112, 7134, 8918\nDays : Tu, TTh, M\nHours : 4-5:15, 9, 1-4\n/\n/\nColumns in Course and all categories for low cardinality columns :\nCredits : 1, 2, 4, 3\nDNO : 50, 520, 550, 600\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 \"Scientists\" (\n\t\"SSN\" INTEGER, \n\t\"Name\" CHAR(30) NOT NULL, \n\tPRIMARY KEY (\"SSN\")\n)\n/\nColumns in Scientists and 3 examples in each column for high cardinality columns :\nSSN : 546523478, 332569843, 845657246\nName : Kumar Swamy, John Doe, David Smith\n/\n\n \nCREATE TABLE pilot (\n\t\"Pilot_Id\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(50) NOT NULL, \n\t\"Age\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Pilot_Id\")\n)\n/\nColumns in pilot and 3 examples in each column for high cardinality columns :\nPilot_Id : 1, 11, 2\nName : Winnifred Boyle, Mr. Cristian Halvorson II, Katheryn Gorczany IV\n/\n/\nColumns in pilot and all categories for low cardinality columns :\nAge : 26, 37, 20, 25, 33, 30, 23, 29, 31\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 \"Organizations\" (\n\torganization_id INTEGER, \n\tdate_formed DATETIME, \n\torganization_name VARCHAR(255), \n\tuk_vat_number VARCHAR(20), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 1, 2, 5, 4, 3\ndate_formed : 2016-08-24 23:52:48, 2016-07-28 01:45:10, 2016-10-09 07:22:53, 2017-04-06 23:59:16, 2016-10-01 12:42:01\norganization_name : Liberal Democrats, Green Party, Labour Party, Conservative, Plaid Cymru\nuk_vat_number : 2157, 1211, 7459, 7237, 4271\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 \"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 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" }, { "role": "user", "content": "What are all the different food allergies?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergy, allergytype, food.\nThe SQL query I'll be generating is:\nSELECT DISTINCT allergy FROM Allergy_type WHERE allergytype = \"food\"" } ]
[ { "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 \"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 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 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 \"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 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 \"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 \"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 \"People_Addresses\" (\n\tperson_address_id INTEGER NOT NULL, \n\tperson_id INTEGER NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tdate_from DATETIME, \n\tdate_to DATETIME, \n\tPRIMARY KEY (person_address_id), \n\tFOREIGN KEY(person_id) REFERENCES \"People\" (person_id), \n\tFOREIGN KEY(address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in People_Addresses and all categories for low cardinality columns :\nperson_address_id : 269, 276, 281, 257, 363, 396, 122, 340\nperson_id : 151, 141, 131, 171, 111, 161, 181, 121\naddress_id : 45, 9, 5, 88, 55, 92, 82, 99\ndate_from : 2013-12-26 16:57:01, 2008-07-31 02:17:25, 2012-09-26 13:21:00, 2008-05-26 20:43:41, 2014-05-10 00:32:31, 2010-11-26 05:21:12, 2017-05-01 17:32:26, 2015-05-24 16:14:12\ndate_to : 2018-03-21 09:46:30, 2018-03-08 06:16:47, 2018-02-23 22:44:18, 2018-03-11 20:26:41, 2018-03-09 02:11:12, 2018-03-09 08:45:06, 2018-03-03 16:06:17, 2018-03-12 21:10:02\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 \"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 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 \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 \"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 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 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 \"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 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" }, { "role": "user", "content": "What is the type of allergy Cat?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype, allergy, Cat.\nThe SQL query I'll be generating is:\nSELECT allergytype FROM Allergy_type WHERE allergy = \"Cat\"" } ]
[ { "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 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 \"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 playlist_tracks (\n\tplaylist_id INTEGER NOT NULL, \n\ttrack_id INTEGER NOT NULL, \n\tCONSTRAINT \"PK_PlaylistTrack\" PRIMARY KEY (playlist_id, track_id), \n\tFOREIGN KEY(playlist_id) REFERENCES playlists (id), \n\tFOREIGN KEY(track_id) REFERENCES tracks (id)\n)\n/\nColumns in playlist_tracks and 3 examples in each column for high cardinality columns :\ntrack_id : 1138, 537, 937\n/\n/\nColumns in playlist_tracks and all categories for low cardinality columns :\nplaylist_id : 1\n/\n \nCREATE TABLE \"Fault_Log\" (\n\tfault_log_entry_id INTEGER, \n\tasset_id INTEGER NOT NULL, \n\trecorded_by_staff_id INTEGER NOT NULL, \n\tfault_log_entry_datetime DATETIME, \n\tfault_description VARCHAR(255), \n\tother_fault_details VARCHAR(255), \n\tPRIMARY KEY (fault_log_entry_id), \n\tFOREIGN KEY(recorded_by_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(asset_id) REFERENCES \"Assets\" (asset_id)\n)\n/\nColumns in Fault_Log and 3 examples in each column for high cardinality columns :\nfault_log_entry_id : 1, 13, 11\nfault_log_entry_datetime : 2018-03-01 08:52:58, 2018-02-28 02:07:36, 2018-03-13 09:43:05\n/\n/\nColumns in Fault_Log and all categories for low cardinality columns :\nasset_id : 2, 5, 7, 8, 6, 12, 3, 15, 9\nrecorded_by_staff_id : 13, 11, 5, 8, 4, 14, 12, 10, 9\nfault_description : failed parts, system error\nother_fault_details : None\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 \"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 \"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 captain (\n\t\"Captain_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Ship_ID\" INTEGER, \n\tage TEXT, \n\t\"Class\" TEXT, \n\t\"Rank\" TEXT, \n\tPRIMARY KEY (\"Captain_ID\"), \n\tFOREIGN KEY(\"Ship_ID\") REFERENCES \"Ship\" (\"Ship_ID\")\n)\n/\nColumns in captain and all categories for low cardinality columns :\nCaptain_ID : 1, 2, 5, 7, 4, 6, 3\nName : Lieutenant Hugh Bolitho, Captain Gilbert Pears, Commander Richard Bolitho, Captain Sir Henry Langford, Captain Beves Conway, Captain Henry Dumaresq, Lieutenant Montagu Verling\nShip_ID : 1, 2, 5, 4, 3\nage : 38, 45, 40, 60, 43, 54\nClass : Sloop-of-war, Armed schooner, Third-rate ship of the line, Frigate, Cutter\nRank : Midshipman, Lieutenant, Commander, junior captain\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 \"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 \"Student_Course_Enrolment\" (\n\tregistration_id INTEGER, \n\tstudent_id INTEGER NOT NULL, \n\tcourse_id INTEGER NOT NULL, \n\tdate_of_enrolment DATETIME NOT NULL, \n\tdate_of_completion DATETIME NOT NULL, \n\tPRIMARY KEY (registration_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_Enrolment and 3 examples in each column for high cardinality columns :\nregistration_id : 17, 9, 16\nstudent_id : 3, 13, 11\ndate_of_enrolment : 2017-12-16 15:53:06, 2017-10-10 10:05:03, 2017-12-07 02:21:13\ndate_of_completion : 2018-03-01 07:12:39, 2018-03-22 18:04:54, 2018-03-07 09:45:48\n/\n/\nColumns in Student_Course_Enrolment and all categories for low cardinality columns :\ncourse_id : 1, 11, 2, 15, 7, 8, 4, 14, 10, 9\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 \"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 \"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 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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 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 \"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" }, { "role": "user", "content": "What is allergy type of a cat allergy?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype, allergy, Cat.\nThe SQL query I'll be generating is:\nSELECT allergytype FROM Allergy_type WHERE allergy = \"Cat\"" } ]
[ { "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 \"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 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 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 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 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 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 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 \"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 \"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 \"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 \"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 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 \"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 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 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 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 \"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 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 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 \"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 \"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 \"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" }, { "role": "user", "content": "How many allergies have type animal?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype, animal.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Allergy_type WHERE allergytype = \"animal\"" } ]
[ { "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 \"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 \"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 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 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 \"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 \"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 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 \"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 \"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 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 \"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 \"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 airport (\n\t\"Airport_ID\" INTEGER, \n\t\"Airport_Name\" TEXT, \n\t\"Total_Passengers\" REAL, \n\t\"%_Change_2007\" TEXT, \n\t\"International_Passengers\" REAL, \n\t\"Domestic_Passengers\" REAL, \n\t\"Transit_Passengers\" REAL, \n\t\"Aircraft_Movements\" REAL, \n\t\"Freight_Metric_Tonnes\" REAL, \n\tPRIMARY KEY (\"Airport_ID\")\n)\n/\nColumns in airport and all categories for low cardinality columns :\nAirport_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAirport_Name : Bristol, London Luton, East Midlands, Birmingham Airport, Glasgow International, London Stansted, London Heathrow, London Gatwick, Edinburgh, Manchester\nTotal_Passengers : 8178891.0, 5620673.0, 34205887.0, 9627589.0, 67054745.0, 6267114.0, 10180734.0, 21219195.0, 22360364.0, 9006702.0\n%_Change_2007 : 2.6%, 4.0%, 6.0%, 1.5%, 0.5%, 5.7%, 2.9%, 4.3%, 3.8%, 7.0%\nInternational_Passengers : 3711140.0, 8105162.0, 3943139.0, 19996947.0, 5057051.0, 4870184.0, 8853224.0, 61344438.0, 30431051.0, 18119230.0\nDomestic_Passengers : 746094.0, 5562516.0, 1171605.0, 2943719.0, 1471538.0, 4192121.0, 3730963.0, 1320678.0, 2343428.0, 5281038.0\nTransit_Passengers : 156246.0, 50889.0, 6832.0, 19989.0, 43873.0, 43631.0, 14524.0, 38458.0, 4395.0, 147791.0\nAircraft_Movements : 478693.0, 117859.0, 204610.0, 193282.0, 125550.0, 76517.0, 112227.0, 100087.0, 93038.0, 263653.0\nFreight_Metric_Tonnes : 3.0, 261507.0, 12418.0, 40518.0, 197738.0, 141781.0, 107702.0, 3546.0, 12192.0, 1397054.0\n/\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 \"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" }, { "role": "user", "content": "How many animal type allergies exist?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype, animal.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Allergy_type WHERE allergytype = \"animal\"" } ]
[ { "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 \"Band\" (\n\t\"Id\" INTEGER, \n\t\"Firstname\" TEXT, \n\t\"Lastname\" TEXT, \n\tPRIMARY KEY (\"Id\")\n)\n/\nColumns in Band and all categories for low cardinality columns :\nId : \nFirstname : \nLastname : \n/\n \nCREATE TABLE country (\n\tcountry_id INTEGER NOT NULL, \n\tcountry VARCHAR(50) NOT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (country_id)\n)\n/\nColumns in country and 3 examples in each column for high cardinality columns :\ncountry_id : 87, 56, 65\ncountry : Belarus, Afghanistan, Runion\n/\n/\nColumns in country and all categories for low cardinality columns :\nlast_update : 2006-02-15 04:44:00\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 \"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 \"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 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 \"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 \"Problems\" (\n\tproblem_id INTEGER, \n\tproduct_id INTEGER NOT NULL, \n\tclosure_authorised_by_staff_id INTEGER NOT NULL, \n\treported_by_staff_id INTEGER NOT NULL, \n\tdate_problem_reported DATETIME NOT NULL, \n\tdate_problem_closed DATETIME, \n\tproblem_description VARCHAR(255), \n\tother_problem_details VARCHAR(255), \n\tPRIMARY KEY (problem_id), \n\tFOREIGN KEY(reported_by_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Product\" (product_id), \n\tFOREIGN KEY(closure_authorised_by_staff_id) REFERENCES \"Staff\" (staff_id)\n)\n/\nColumns in Problems and 3 examples in each column for high cardinality columns :\nproblem_id : 1, 13, 11\nclosure_authorised_by_staff_id : 1, 13, 2\ndate_problem_reported : 1995-05-14 08:32:56, 1988-11-07 16:09:31, 1986-11-13 07:30:55\ndate_problem_closed : 1974-09-20 13:42:19, 1997-10-18 20:09:57, 2004-06-20 01:08:25\nproblem_description : d, i, s\n/\n/\nColumns in Problems and all categories for low cardinality columns :\nproduct_id : 1, 13, 2, 5, 7, 8, 4, 6, 15\nreported_by_staff_id : 1, 13, 11, 2, 5, 7, 4, 14, 10\nother_problem_details : f, m, i, s, k, l, p, v, c\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 status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 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 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 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 \"match\" (\n\t\"Match_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Score\" TEXT, \n\t\"Result\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (\"Match_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nMatch_ID : 1, 2, 5, 4, 6, 3\nDate : 23 July 1992, 18 February 1992, 19 July 1992, 23 July 2000, 4 April 1993\nVenue : Estadio Rigoberto López , Managua , Nicaragua, Estadio Cuscatlán , San Salvador , El Salvador\nScore : 3-0, 2–1, 1-0, 1–0\nResult : 5-1, 7–1, 5-0, 2–1, 2-0\nCompetition : 1994 FIFA World Cup qualification, Friendly match, 2002 FIFA World Cup qualification\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 (\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 \"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 \"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 \"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 \"Fault_Log\" (\n\tfault_log_entry_id INTEGER, \n\tasset_id INTEGER NOT NULL, \n\trecorded_by_staff_id INTEGER NOT NULL, \n\tfault_log_entry_datetime DATETIME, \n\tfault_description VARCHAR(255), \n\tother_fault_details VARCHAR(255), \n\tPRIMARY KEY (fault_log_entry_id), \n\tFOREIGN KEY(recorded_by_staff_id) REFERENCES \"Staff\" (staff_id), \n\tFOREIGN KEY(asset_id) REFERENCES \"Assets\" (asset_id)\n)\n/\nColumns in Fault_Log and 3 examples in each column for high cardinality columns :\nfault_log_entry_id : 1, 13, 11\nfault_log_entry_datetime : 2018-03-01 08:52:58, 2018-02-28 02:07:36, 2018-03-13 09:43:05\n/\n/\nColumns in Fault_Log and all categories for low cardinality columns :\nasset_id : 2, 5, 7, 8, 6, 12, 3, 15, 9\nrecorded_by_staff_id : 13, 11, 5, 8, 4, 14, 12, 10, 9\nfault_description : failed parts, system error\nother_fault_details : None\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" }, { "role": "user", "content": "Show all allergy types and the number of allergies in each type." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT allergytype , count(*) FROM Allergy_type GROUP BY allergytype" } ]
[ { "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 \"Problem_Category_Codes\" (\n\tproblem_category_code VARCHAR(20), \n\tproblem_category_description VARCHAR(80), \n\tPRIMARY KEY (problem_category_code)\n)\n/\nColumns in Problem_Category_Codes and all categories for low cardinality columns :\nproblem_category_code : Datatabase, Middleware, GUI\nproblem_category_description : User Interface., Infrastructrure and Architecture, Database design or contents.\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 \"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 \"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 \"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 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 \"Invoices\" (\n\tinvoice_number INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_date DATETIME, \n\tPRIMARY KEY (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 2018-03-16 21:57:43, 2018-03-20 00:21:41, 2018-03-05 08:47:33\n/\n/\nColumns in Invoices and all categories for low cardinality columns :\norder_id : 13, 11, 5, 8, 4, 12, 3, 14, 10, 9\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 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 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 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 \"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 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 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 \"Physician\" (\n\t\"EmployeeID\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Position\" VARCHAR(30) NOT NULL, \n\t\"SSN\" INTEGER NOT NULL, \n\tCONSTRAINT pk_physician PRIMARY KEY (\"EmployeeID\")\n)\n/\nColumns in Physician and all categories for low cardinality columns :\nEmployeeID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nName : John Dorian, Bob Kelso, Todd Quinlan, Elliot Reid, John Wen, Keith Dudemeister, Molly Clock, Percival Cox, Christopher Turk\nPosition : Senior Attending Physician, Head Chief of Medicine, Staff Internist, Attending Physician, Surgical Attending Physician, Attending Psychiatrist, MD Resident\nSSN : 888888888, 999999999, 111111111, 444444444, 777777777, 222222222, 333333333, 555555555, 666666666\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 drivers (\n\t\"driverId\" INTEGER, \n\t\"driverRef\" TEXT, \n\tnumber TEXT, \n\tcode TEXT, \n\tforename TEXT, \n\tsurname TEXT, \n\tdob TEXT, \n\tnationality TEXT, \n\turl TEXT, \n\tPRIMARY KEY (\"driverId\")\n)\n/\nColumns in drivers and 3 examples in each column for high cardinality columns :\ndriverId : 87, 56, 65\ndriverRef : prost, katayama, satoru_nakajima\nnumber : , 5, 44\ncode : WEB, FMO, \nforename : Adrian, Gary, Eliseo\nsurname : Blundell, Boullion, Verstappen\ndob : 06/10/1951, 27/11/1957, 23/09/1981\nnationality : Argentine, Colombian, Czech\nurl : http://en.wikipedia.org/wiki/Ricardo_Rosset, http://en.wikipedia.org/wiki/Alex_Zanardi, http://en.wikipedia.org/wiki/Marc_Surer\n/\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 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 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": "What are the allergy types and how many allergies correspond to each one?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT allergytype , count(*) FROM Allergy_type GROUP BY allergytype" } ]
[ { "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 \"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 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 \"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 \"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 \"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 \"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 \"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 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 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 \"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 \"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 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 \"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 \"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 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 \"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 \"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 \"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 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 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 \"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" }, { "role": "user", "content": "Which allergy type has most number of allergies?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT allergytype FROM Allergy_type GROUP BY allergytype 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 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_Hotel_Star_Ratings\" (\n\tstar_rating_code CHAR(15) NOT NULL, \n\tstar_rating_description VARCHAR(80), \n\tPRIMARY KEY (star_rating_code), \n\tUNIQUE (star_rating_code)\n)\n/\nColumns in Ref_Hotel_Star_Ratings and all categories for low cardinality columns :\nstar_rating_code : 1, 2, 5, 4, 3\nstar_rating_description : star\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 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 \"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 membership_register_branch (\n\t\"Member_ID\" INTEGER, \n\t\"Branch_ID\" TEXT, \n\t\"Register_Year\" TEXT, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Branch_ID\") REFERENCES branch (\"Branch_ID\")\n)\n/\nColumns in membership_register_branch and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3\nBranch_ID : 1, 2, 5, 8, 4, 6\nRegister_Year : 2016, 2017\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 \"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 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 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 \"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 \"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 \"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 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 \"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 \"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 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 \"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 party_events (\n\t\"Event_ID\" INTEGER, \n\t\"Event_Name\" TEXT, \n\t\"Party_ID\" INTEGER, \n\t\"Member_in_charge_ID\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Member_in_charge_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in party_events and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 7, 8, 4, 6, 3\nEvent_Name : Election Meeting, Annaual Meeting, Conference, Budget Meeting\nParty_ID : 1, 2, 3\nMember_in_charge_ID : 11, 2, 15, 4, 12, 3, 10\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": "Which allergy type is most common?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT allergytype FROM Allergy_type GROUP BY allergytype 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 \"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 \"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 \"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 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 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 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 \"Party_Services\" (\n\tbooking_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tservice_id INTEGER NOT NULL, \n\tservice_datetime DATETIME NOT NULL, \n\tbooking_made_date DATETIME, \n\tFOREIGN KEY(customer_id) REFERENCES \"Parties\" (party_id), \n\tFOREIGN KEY(service_id) REFERENCES \"Services\" (service_id)\n)\n/\nColumns in Party_Services and 3 examples in each column for high cardinality columns :\nbooking_id : 1, 13, 11\ncustomer_id : 13, 2, 5\nservice_datetime : 2018-02-28 16:29:04, 2018-03-01 18:31:32, 2018-03-09 07:27:30\nbooking_made_date : 2018-03-25 15:09:54, 2018-03-24 07:55:33, 2018-03-24 12:21:20\n/\n/\nColumns in Party_Services and all categories for low cardinality columns :\nservice_id : 1, 13, 11, 5, 7, 6, 12, 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 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 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 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 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 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 \"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 \"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 \"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 \"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 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 \"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" }, { "role": "user", "content": "Which allergy type has least number of allergies?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT allergytype FROM Allergy_type GROUP BY allergytype ORDER BY count(*) ASC 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 \"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 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 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 college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\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 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 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 \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 \"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 artwork (\n\t\"Artwork_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\")\n)\n/\nColumns in artwork and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nType : Presenter Talent Show, Program Talent Show, Presenter Music/Variety Show, Program Music/Variety Show\nName : Why, I Know, Martin, Indonesian Idol, Loving you, Daniel Mananta, Back Home, Cats, Boys\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 \"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 \"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_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 \"Participates_in\" (\n\tstuid INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Participates_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nactid : 771, 782, 770\n/\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 \"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 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 \"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 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 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 \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" }, { "role": "user", "content": "Which allergy type is the least common?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Allergy_type.\nFrom these tables, I'll be using the following columns: allergytype.\nThe SQL query I'll be generating is:\nSELECT allergytype FROM Allergy_type GROUP BY allergytype ORDER BY count(*) ASC 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 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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\n/\n \nCREATE TABLE \"Vehicles\" (\n\tvehicle_id INTEGER, \n\tvehicle_details VARCHAR(255), \n\tPRIMARY KEY (vehicle_id)\n)\n/\nColumns in Vehicles and all categories for low cardinality columns :\nvehicle_id : 1, 2, 3\nvehicle_details : Car, Van, Truck\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 \"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 \"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 \"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 news_report (\n\t\"journalist_ID\" INTEGER, \n\t\"Event_ID\" INTEGER, \n\t\"Work_Type\" TEXT, \n\tPRIMARY KEY (\"journalist_ID\", \"Event_ID\"), \n\tFOREIGN KEY(\"Event_ID\") REFERENCES event (\"Event_ID\"), \n\tFOREIGN KEY(\"journalist_ID\") REFERENCES journalist (\"journalist_ID\")\n)\n/\nColumns in news_report and all categories for low cardinality columns :\njournalist_ID : 1, 11, 7, 8, 4, 6\nEvent_ID : 1, 2, 5, 4, 3\nWork_Type : Screening, Host, Music\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 \"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 \"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 \"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 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 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 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 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 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 \"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 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 department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\n/\n" }, { "role": "user", "content": "How many students are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: .\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Student" } ]
[ { "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 \"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 \"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 \"Scientists\" (\n\t\"SSN\" INTEGER, \n\t\"Name\" CHAR(30) NOT NULL, \n\tPRIMARY KEY (\"SSN\")\n)\n/\nColumns in Scientists and 3 examples in each column for high cardinality columns :\nSSN : 546523478, 332569843, 845657246\nName : Kumar Swamy, John Doe, David Smith\n/\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 phone (\n\t\"Name\" TEXT, \n\t\"Phone_ID\" INTEGER, \n\t\"Memory_in_G\" INTEGER, \n\t\"Carrier\" TEXT, \n\t\"Price\" REAL, \n\tPRIMARY KEY (\"Phone_ID\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nName : IPhone 6s, IPhone 7, IPhone X, IPhone 6, IPhone 5s\nPhone_ID : 1, 2, 5, 4, 3\nMemory_in_G : 128, 32, 16, 64\nCarrier : Sprint, TMobile\nPrice : 320.0, 1000.0, 480.0, 899.0, 699.0\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 department (\n\t\"Dname\" TEXT, \n\t\"Dnumber\" INTEGER, \n\t\"Mgr_ssn\" INTEGER, \n\t\"Mgr_start_date\" TEXT, \n\tPRIMARY KEY (\"Dnumber\")\n)\n/\nColumns in department and all categories for low cardinality columns :\nDname : Headquarters, Administration, Research\nDnumber : 1, 4, 5\nMgr_ssn : 987654321, 333445555, 888665555\nMgr_start_date : 1988-05-22, 1995-01-01, 1981-06-19\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 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 \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 \"Organization_Contact_Individuals\" (\n\tindividual_id INTEGER NOT NULL, \n\torganization_id INTEGER NOT NULL, \n\tdate_contact_from DATETIME NOT NULL, \n\tdate_contact_to DATETIME, \n\tPRIMARY KEY (individual_id, organization_id), \n\tFOREIGN KEY(individual_id) REFERENCES \"Individuals\" (individual_id), \n\tFOREIGN KEY(organization_id) REFERENCES \"Organizations\" (organization_id)\n)\n/\nColumns in Organization_Contact_Individuals and 3 examples in each column for high cardinality columns :\ndate_contact_from : 2016-07-26 09:08:15, 2016-04-21 03:55:35, 2017-01-06 09:38:54\ndate_contact_to : 2018-03-24 16:54:36, 2018-03-07 16:40:29, 2018-03-06 21:22:49\n/\n/\nColumns in Organization_Contact_Individuals and all categories for low cardinality columns :\nindividual_id : 13, 11, 5, 7, 8, 6, 14, 10, 9\norganization_id : 1, 2, 5, 4, 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 \"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 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 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 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 \"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 school_details (\n\t\"School_ID\" INTEGER, \n\t\"Nickname\" TEXT, \n\t\"Colors\" TEXT, \n\t\"League\" TEXT, \n\t\"Class\" TEXT, \n\t\"Division\" TEXT, \n\tPRIMARY KEY (\"School_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in school_details and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nNickname : Auks, Raiders, Silver Eagles, Seahawks, Buccaneers, Tigers\nColors : Dark Green and White, Blue and Yellow, Maroon and White, Blue and Gold, Garnet and White, Silver and Maroon\nLeague : DSHA\nClass : Flight B, Flight A, Fight A\nDivision : Division 1, Division 2, Division 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 \"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" }, { "role": "user", "content": "What is the total number of students?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: .\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Student" } ]
[ { "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 \"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 \"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 \"Trucks\" (\n\ttruck_id INTEGER, \n\ttruck_licence_number VARCHAR(20), \n\ttruck_details VARCHAR(255), \n\tPRIMARY KEY (truck_id)\n)\n/\nColumns in Trucks and 3 examples in each column for high cardinality columns :\ntruck_id : 1, 13, 11\ntruck_licence_number : 25232, 63359, 24474\ntruck_details : Kaya, Ricky, Deon\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 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 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 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 \"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 college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\n/\n \nCREATE TABLE \"DEPARTMENT\" (\n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"DEPT_NAME\" VARCHAR(30), \n\t\"SCHOOL_CODE\" VARCHAR(8), \n\t\"EMP_NUM\" INTEGER, \n\t\"DEPT_ADDRESS\" VARCHAR(20), \n\t\"DEPT_EXTENSION\" VARCHAR(4), \n\tPRIMARY KEY (\"DEPT_CODE\"), \n\tFOREIGN KEY(\"EMP_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\")\n)\n/\nColumns in DEPARTMENT and 3 examples in each column for high cardinality columns :\nDEPT_CODE : ART, ECON/FIN, HIST\nDEPT_NAME : History, Computer Info. Systems, Biology\nEMP_NUM : 114, 106, 342\nDEPT_ADDRESS : KLR 126, Box 55, AAK 230, Box 415, KLR 333, Box 56\nDEPT_EXTENSION : 1867, 3126, 4117\n/\n/\nColumns in DEPARTMENT and all categories for low cardinality columns :\nSCHOOL_CODE : BUS, A&SCI\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 \"InvoiceLine\" (\n\t\"InvoiceLineId\" INTEGER NOT NULL, \n\t\"InvoiceId\" INTEGER NOT NULL, \n\t\"TrackId\" INTEGER NOT NULL, \n\t\"UnitPrice\" DECIMAL(10, 2) NOT NULL, \n\t\"Quantity\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"InvoiceLineId\"), \n\tFOREIGN KEY(\"TrackId\") REFERENCES \"Track\" (\"TrackId\"), \n\tFOREIGN KEY(\"InvoiceId\") REFERENCES \"Invoice\" (\"InvoiceId\")\n)\n/\nColumns in InvoiceLine and 3 examples in each column for high cardinality columns :\nInvoiceLineId : 87, 56, 65\nInvoiceId : 36, 17, 21\nTrackId : 1188, 756, 988\n/\n/\nColumns in InvoiceLine and all categories for low cardinality columns :\nUnitPrice : 0.99\nQuantity : 1\n/\n \nCREATE TABLE \"Order_Items\" (\n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\torder_quantity VARCHAR(15), \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 all categories for low cardinality columns :\norder_id : 13, 11, 2, 5, 7, 8, 14, 10\nproduct_id : 1, 2, 3\norder_quantity : 1, 2, 5, 7, 8, 6, 9\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 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 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 csu_fees (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"CampusFee\" INTEGER, \n\tPRIMARY KEY (\"Campus\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in csu_fees and 3 examples in each column for high cardinality columns :\nCampus : 17, 21, 9\nCampusFee : 1916, 2009, 2204\n/\n/\nColumns in csu_fees and all categories for low cardinality columns :\nYear : 2003, 1996\n/\n \nCREATE TABLE purchase (\n\t\"Member_ID\" INTEGER, \n\t\"Branch_ID\" TEXT, \n\t\"Year\" TEXT, \n\t\"Total_pounds\" REAL, \n\tPRIMARY KEY (\"Member_ID\", \"Branch_ID\", \"Year\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Branch_ID\") REFERENCES branch (\"Branch_ID\")\n)\n/\nColumns in purchase and all categories for low cardinality columns :\nMember_ID : 1, 2, 4, 6, 3\nBranch_ID : 1, 2, 5, 6, 3\nYear : 2018, 2017\nTotal_pounds : 232.09, 2013.32, 20.99, 430.29, 402.1, 988.09, 321.13, 343.76\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\"ID\" VARCHAR(5), \n\tname VARCHAR(20) NOT NULL, \n\tdept_name VARCHAR(20), \n\ttot_cred NUMERIC(3, 0), \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(dept_name) REFERENCES department (dept_name), \n\tCHECK (tot_cred >= 0)\n)\n/\nColumns in student and 3 examples in each column for high cardinality columns :\nID : 93061, 97679, 35175\nname : Tran-, Norman, Moei\ndept_name : Math, Athletics, English\ntot_cred : 87, 56, 65\n/\n\n \nCREATE TABLE event (\n\t\"ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Stadium_ID\" INTEGER, \n\t\"Year\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Stadium_ID\") REFERENCES stadium (\"ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nID : 1, 2, 5, 4, 6, 3\nName : Pacific, European FINA, FINA, World Master, IPC, World Junior\nStadium_ID : 1, 2, 8, 4, 3, 10\nYear : 2016, 2013, 2012, 2017, 2011, 2014\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" }, { "role": "user", "content": "Show first name and last name for all students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Fname, Lname.\nThe SQL query I'll be generating is:\nSELECT Fname , Lname FROM Student" } ]
[ { "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 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 \"Ref_Product_Categories\" (\n\tproduct_category_code VARCHAR(15), \n\tproduct_category_description VARCHAR(80), \n\tunit_of_measure VARCHAR(20), \n\tPRIMARY KEY (product_category_code)\n)\n/\nColumns in Ref_Product_Categories and all categories for low cardinality columns :\nproduct_category_code : Spices, Seeds, Herbs\nproduct_category_description : Spices, Seeds, Herbs\nunit_of_measure : Weight - pound,kilo., Handful \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 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 \"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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 \"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 \"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 \"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 \"Party_Services\" (\n\tbooking_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tservice_id INTEGER NOT NULL, \n\tservice_datetime DATETIME NOT NULL, \n\tbooking_made_date DATETIME, \n\tFOREIGN KEY(customer_id) REFERENCES \"Parties\" (party_id), \n\tFOREIGN KEY(service_id) REFERENCES \"Services\" (service_id)\n)\n/\nColumns in Party_Services and 3 examples in each column for high cardinality columns :\nbooking_id : 1, 13, 11\ncustomer_id : 13, 2, 5\nservice_datetime : 2018-02-28 16:29:04, 2018-03-01 18:31:32, 2018-03-09 07:27:30\nbooking_made_date : 2018-03-25 15:09:54, 2018-03-24 07:55:33, 2018-03-24 12:21:20\n/\n/\nColumns in Party_Services and all categories for low cardinality columns :\nservice_id : 1, 13, 11, 5, 7, 6, 12, 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 \"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 \"Staff\" (\n\tstaff_id INTEGER, \n\tstaff_name VARCHAR(255), \n\tgender VARCHAR(1), \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_name : Edmond, Audreanne, Oren\n/\n/\nColumns in Staff and all categories for low cardinality columns :\ngender : 1, 0\nother_staff_details : Woker, None, Manager\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 \"Party_Services\" (\n\tbooking_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tservice_id INTEGER NOT NULL, \n\tservice_datetime DATETIME NOT NULL, \n\tbooking_made_date DATETIME, \n\tFOREIGN KEY(customer_id) REFERENCES \"Parties\" (party_id), \n\tFOREIGN KEY(service_id) REFERENCES \"Services\" (service_id)\n)\n/\nColumns in Party_Services and 3 examples in each column for high cardinality columns :\nbooking_id : 1, 13, 11\ncustomer_id : 13, 2, 5\nservice_datetime : 2018-02-28 16:29:04, 2018-03-01 18:31:32, 2018-03-09 07:27:30\nbooking_made_date : 2018-03-25 15:09:54, 2018-03-24 07:55:33, 2018-03-24 12:21:20\n/\n/\nColumns in Party_Services and all categories for low cardinality columns :\nservice_id : 1, 13, 11, 5, 7, 6, 12, 3\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 \"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" }, { "role": "user", "content": "What are the full names of all students" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Fname, Lname.\nThe SQL query I'll be generating is:\nSELECT Fname , Lname FROM Student" } ]
[ { "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 \"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 \"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 \"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 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 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 \"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 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 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 \"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 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 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 party_events (\n\t\"Event_ID\" INTEGER, \n\t\"Event_Name\" TEXT, \n\t\"Party_ID\" INTEGER, \n\t\"Member_in_charge_ID\" INTEGER, \n\tPRIMARY KEY (\"Event_ID\"), \n\tFOREIGN KEY(\"Member_in_charge_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Party_ID\") REFERENCES party (\"Party_ID\")\n)\n/\nColumns in party_events and all categories for low cardinality columns :\nEvent_ID : 1, 2, 5, 7, 8, 4, 6, 3\nEvent_Name : Election Meeting, Annaual Meeting, Conference, Budget Meeting\nParty_ID : 1, 2, 3\nMember_in_charge_ID : 11, 2, 15, 4, 12, 3, 10\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 \"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 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 \"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 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 aircraft (\n\t\"Aircraft_ID\" INTEGER NOT NULL, \n\t\"Aircraft\" VARCHAR(50) NOT NULL, \n\t\"Description\" VARCHAR(50) NOT NULL, \n\t\"Max_Gross_Weight\" VARCHAR(50) NOT NULL, \n\t\"Total_disk_area\" VARCHAR(50) NOT NULL, \n\t\"Max_disk_Loading\" VARCHAR(50) NOT NULL, \n\tPRIMARY KEY (\"Aircraft_ID\")\n)\n/\nColumns in aircraft and all categories for low cardinality columns :\nAircraft_ID : 1, 2, 5, 4, 3\nAircraft : Bell 206B3 JetRanger, Mil Mi-26, CH-53E Super Stallion, Robinson R-22, CH-47D Chinook\nDescription : Light utility helicopter, Heavy-lift helicopter, Turboshaft utility helicopter, Tandem rotor helicopter\nMax_Gross_Weight : 50,000 lb (22,680 kg), 123,500 lb (56,000 kg), 73,500 lb (33,300 kg), 3,200 lb (1,451 kg), 1,370 lb (635 kg)\nTotal_disk_area : 872 ft² (81.1 m²), 5,655 ft² (526 m²), 8,495 ft² (789 m²), 497 ft² (46.2 m²), 4,900 ft² (460 m²)\nMax_disk_Loading : 15 lb/ft² (72 kg/m²), 2.6 lb/ft² (14 kg/m²), 14.5 lb/ft² (71 kg/m²), 8.8 lb/ft² (43 kg/m²), 3.7 lb/ft² (18 kg/m²)\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 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 \"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" }, { "role": "user", "content": "How many different advisors are listed?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: advisor.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT advisor) FROM Student" } ]
[ { "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 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 \"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 artists (\n\tid INTEGER, \n\tname VARCHAR(120), \n\tPRIMARY KEY (id)\n)\n/\nColumns in artists and 3 examples in each column for high cardinality columns :\nid : 87, 56, 65\nname : Smashing Pumpkins, Santana Feat. Eric Clapton, Godsmack\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 \"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 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 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 \"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 \"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 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 \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 \"Document_Sections_Images\" (\n\tsection_id INTEGER NOT NULL, \n\timage_id INTEGER NOT NULL, \n\tPRIMARY KEY (section_id, image_id), \n\tFOREIGN KEY(image_id) REFERENCES \"Images\" (image_id), \n\tFOREIGN KEY(section_id) REFERENCES \"Document_Sections\" (section_id)\n)\n/\nColumns in Document_Sections_Images and 3 examples in each column for high cardinality columns :\nsection_id : 89, 38, 86\nimage_id : 13, 2, 5\n/\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 \"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 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 \"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_Characteristic_Types\" (\n\tcharacteristic_type_code VARCHAR(15), \n\tcharacteristic_type_description VARCHAR(80), \n\tPRIMARY KEY (characteristic_type_code)\n)\n/\nColumns in Ref_Characteristic_Types and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_type_description : Grade, Purity\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 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 \"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" }, { "role": "user", "content": "How many advisors are there?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: advisor.\nThe SQL query I'll be generating is:\nSELECT count(DISTINCT advisor) FROM Student" } ]
[ { "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 \"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 medicine (\n\tid INTEGER, \n\tname TEXT, \n\t\"Trade_Name\" TEXT, \n\t\"FDA_approved\" TEXT, \n\tPRIMARY KEY (id)\n)\n/\nColumns in medicine and 3 examples in each column for high cardinality columns :\nid : 17, 21, 9\nname : Quetiapine, Carpipramine, Asenapine\nTrade_Name : Buronil, Fanapt, Nipolept\n/\n/\nColumns in medicine and all categories for low cardinality columns :\nFDA_approved : Yes, No\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 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 \"Residents\" (\n\tresident_id INTEGER NOT NULL, \n\tproperty_id INTEGER NOT NULL, \n\tdate_moved_in DATETIME NOT NULL, \n\tdate_moved_out DATETIME NOT NULL, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (resident_id, property_id, date_moved_in), \n\tFOREIGN KEY(property_id) REFERENCES \"Properties\" (property_id)\n)\n/\nColumns in Residents and 3 examples in each column for high cardinality columns :\nresident_id : 87, 38, 37\nproperty_id : 954, 120, 108\ndate_moved_out : 2018-01-28 13:19:54, 2017-11-14 06:28:48, 2018-02-22 06:24:15\nother_details : Anderson Batz, Jacques Glover II, Jess Wyman\n/\n/\nColumns in Residents and all categories for low cardinality columns :\ndate_moved_in : 2016-09-27 12:00:00, 2017-06-17 15:43:33, 2015-03-27 12:00:00\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 \"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 \"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 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 \"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 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 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 temperature (\n\t\"City_ID\" INTEGER, \n\t\"Jan\" REAL, \n\t\"Feb\" REAL, \n\t\"Mar\" REAL, \n\t\"Apr\" REAL, \n\t\"Jun\" REAL, \n\t\"Jul\" REAL, \n\t\"Aug\" REAL, \n\t\"Sep\" REAL, \n\t\"Oct\" REAL, \n\t\"Nov\" REAL, \n\t\"Dec\" REAL, \n\tPRIMARY KEY (\"City_ID\"), \n\tFOREIGN KEY(\"City_ID\") REFERENCES city (\"City_ID\")\n)\n/\nColumns in temperature and all categories for low cardinality columns :\nCity_ID : 1, 11, 2, 7, 4, 6, 3, 10\nJan : 18.9, 25.6, 18.3, 26.1, 17.8, 26.7, 17.2\nFeb : 18.9, 18.3, 26.1, 27.2, 17.8, 26.6, 17.2\nMar : 19.4, 18.3, 26.1, 26.6, 27.8\nApr : 18.9, 26.1, 20.6, 28.3, 27.8, 20.0\nJun : 22.8, 30.0, 30.6, 22.2, 20.6, 28.3, 27.8, 20.0\nJul : 31.1, 23.3, 28.9, 30.6, 20.6, 21.7, 27.8\nAug : 31.1, 31.7, 23.9, 23.3, 29.4, 20.6, 21.7, 28.3\nSep : 31.1, 21.1, 31.7, 23.3, 29.4, 20.6, 28.3\nOct : 22.8, 30.6, 28.9, 20.6, 28.3, 20.0\nNov : 19.4, 27.2, 28.9, 21.7, 20.0\nDec : 18.3, 26.1, 26.7, 27.8, 20.0\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 \"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 \"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 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" }, { "role": "user", "content": "Show all majors." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Major.\nThe SQL query I'll be generating is:\nSELECT DISTINCT Major FROM Student" } ]
[ { "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 aircraft (\n\t\"Aircraft_ID\" INTEGER NOT NULL, \n\t\"Aircraft\" VARCHAR(50) NOT NULL, \n\t\"Description\" VARCHAR(50) NOT NULL, \n\t\"Max_Gross_Weight\" VARCHAR(50) NOT NULL, \n\t\"Total_disk_area\" VARCHAR(50) NOT NULL, \n\t\"Max_disk_Loading\" VARCHAR(50) NOT NULL, \n\tPRIMARY KEY (\"Aircraft_ID\")\n)\n/\nColumns in aircraft and all categories for low cardinality columns :\nAircraft_ID : 1, 2, 5, 4, 3\nAircraft : Bell 206B3 JetRanger, Mil Mi-26, CH-53E Super Stallion, Robinson R-22, CH-47D Chinook\nDescription : Light utility helicopter, Heavy-lift helicopter, Turboshaft utility helicopter, Tandem rotor helicopter\nMax_Gross_Weight : 50,000 lb (22,680 kg), 123,500 lb (56,000 kg), 73,500 lb (33,300 kg), 3,200 lb (1,451 kg), 1,370 lb (635 kg)\nTotal_disk_area : 872 ft² (81.1 m²), 5,655 ft² (526 m²), 8,495 ft² (789 m²), 497 ft² (46.2 m²), 4,900 ft² (460 m²)\nMax_disk_Loading : 15 lb/ft² (72 kg/m²), 2.6 lb/ft² (14 kg/m²), 14.5 lb/ft² (71 kg/m²), 8.8 lb/ft² (43 kg/m²), 3.7 lb/ft² (18 kg/m²)\n/\n \nCREATE TABLE \"Delivery_Routes\" (\n\troute_id INTEGER, \n\troute_name VARCHAR(50), \n\tother_route_details VARCHAR(255), \n\tPRIMARY KEY (route_id)\n)\n/\nColumns in Delivery_Routes and 3 examples in each column for high cardinality columns :\nroute_id : 1, 13, 11\nroute_name : Huel, Armstrong and Senger, Brekke, Powlowski and Fritsch, Heidenreich Group\nother_route_details : 534 Lubowitz Terrace\nLake Tomfort, LA 52697-4998, 941 Ritchie Plains Suite 833\nNorth Jerry, LA 32804-7405, 36578 Kirsten Terrace\nKrajcikside, NH 29063\n/\n\n \nCREATE TABLE \"Products_Booked\" (\n\tbooking_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\treturned_yn VARCHAR(1), \n\treturned_late_yn VARCHAR(1), \n\tbooked_count INTEGER, \n\tbooked_amount FLOAT, \n\tPRIMARY KEY (booking_id, product_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in Products_Booked and 3 examples in each column for high cardinality columns :\nbooked_amount : 398.68, 123.43, 344.38\n/\n/\nColumns in Products_Booked and all categories for low cardinality columns :\nbooking_id : 1, 13, 11, 10, 2, 4, 14, 3, 15\nproduct_id : 1, 2, 5, 4, 3\nreturned_yn : 1\nreturned_late_yn : 1, 0\nbooked_count : 1, 2, 5, 4, 6, 3, 9\n/\n \nCREATE TABLE staff (\n\tstaff_id INTEGER NOT NULL, \n\tfirst_name VARCHAR(45) NOT NULL, \n\tlast_name VARCHAR(45) NOT NULL, \n\taddress_id INTEGER NOT NULL, \n\tpicture BLOB DEFAULT NULL, \n\temail VARCHAR(50) DEFAULT NULL, \n\tstore_id INTEGER NOT NULL, \n\tactive BOOLEAN DEFAULT TRUE NOT NULL, \n\tusername VARCHAR(16) NOT NULL, \n\tpassword VARCHAR(40) DEFAULT NULL, \n\tlast_update TIMESTAMP DEFAULT CURRENT_TIMESTAMP NOT NULL, \n\tPRIMARY KEY (staff_id), \n\tFOREIGN KEY(address_id) REFERENCES address (address_id)\n)\n/\nColumns in staff and all categories for low cardinality columns :\nstaff_id : \nfirst_name : \nlast_name : \naddress_id : \npicture : \nemail : \nstore_id : \nactive : \nusername : \npassword : \nlast_update : \n/\n \nCREATE TABLE \"Bookings\" (\n\t\"Booking_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Workshop_Group_ID\" VARCHAR(100) NOT NULL, \n\t\"Status_Code\" CHAR(15) NOT NULL, \n\t\"Store_ID\" INTEGER NOT NULL, \n\t\"Order_Date\" DATETIME NOT NULL, \n\t\"Planned_Delivery_Date\" DATETIME NOT NULL, \n\t\"Actual_Delivery_Date\" DATETIME NOT NULL, \n\t\"Other_Order_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Booking_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Clients\" (\"Client_ID\"), \n\tFOREIGN KEY(\"Workshop_Group_ID\") REFERENCES \"Drama_Workshop_Groups\" (\"Workshop_Group_ID\"), \n\tUNIQUE (\"Booking_ID\")\n)\n/\nColumns in Bookings and 3 examples in each column for high cardinality columns :\nBooking_ID : 1, 13, 11\nCustomer_ID : 938, 605, 591\nOrder_Date : 1971-05-11 06:53:01, 1975-11-23 06:28:47, 1975-12-30 14:12:32\nPlanned_Delivery_Date : 2014-06-05 10:19:46, 2013-03-10 18:47:05, 1993-04-17 23:53:01\nActual_Delivery_Date : 1983-02-07 20:27:10, 1971-01-13 13:24:52, 1983-10-09 10:48:48\n/\n/\nColumns in Bookings and all categories for low cardinality columns :\nWorkshop_Group_ID : 954, 838, 405, 735, 140, 708, 176, 685, 136\nStatus_Code : stop, good\nStore_ID : 1, 2, 5, 7, 8, 4, 6, 9\nOther_Order_Details : None\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 \"Ref_Characteristic_Types\" (\n\tcharacteristic_type_code VARCHAR(15), \n\tcharacteristic_type_description VARCHAR(80), \n\tPRIMARY KEY (characteristic_type_code)\n)\n/\nColumns in Ref_Characteristic_Types and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_type_description : Grade, Purity\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 \"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 \"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 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 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 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 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 \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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 membership_register_branch (\n\t\"Member_ID\" INTEGER, \n\t\"Branch_ID\" TEXT, \n\t\"Register_Year\" TEXT, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\"), \n\tFOREIGN KEY(\"Branch_ID\") REFERENCES branch (\"Branch_ID\")\n)\n/\nColumns in membership_register_branch and all categories for low cardinality columns :\nMember_ID : 1, 2, 5, 7, 8, 4, 6, 3\nBranch_ID : 1, 2, 5, 8, 4, 6\nRegister_Year : 2016, 2017\n/\n" }, { "role": "user", "content": "What are the different majors?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Major.\nThe SQL query I'll be generating is:\nSELECT DISTINCT Major FROM Student" } ]
[ { "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 \"Order_Deliveries\" (\n\tlocation_code VARCHAR(10) NOT NULL, \n\tactual_order_id INTEGER NOT NULL, \n\tdelivery_status_code VARCHAR(10) NOT NULL, \n\tdriver_employee_id INTEGER NOT NULL, \n\ttruck_id INTEGER NOT NULL, \n\tdelivery_date DATETIME, \n\tFOREIGN KEY(driver_employee_id) REFERENCES \"Employees\" (employee_id), \n\tFOREIGN KEY(location_code) REFERENCES \"Delivery_Route_Locations\" (location_code), \n\tFOREIGN KEY(actual_order_id) REFERENCES \"Actual_Orders\" (actual_order_id), \n\tFOREIGN KEY(truck_id) REFERENCES \"Trucks\" (truck_id)\n)\n/\nColumns in Order_Deliveries and 3 examples in each column for high cardinality columns :\nactual_order_id : 1, 11, 2\ndelivery_date : 2018-03-08 17:17:12, 2018-02-26 13:22:53, 2018-03-17 09:09:06\n/\n/\nColumns in Order_Deliveries and all categories for low cardinality columns :\nlocation_code : 27 City Rd, 73 Nancy Av, 58 Roof Av, 34 Benz St\ndelivery_status_code : Ready, On Road, Delivered\ndriver_employee_id : 1, 3, 13, 11, 2, 8, 4, 6, 12, 14\ntruck_id : 1, 11, 2, 5, 4, 6, 10, 9\n/\n \nCREATE TABLE \"Residents\" (\n\tresident_id INTEGER NOT NULL, \n\tproperty_id INTEGER NOT NULL, \n\tdate_moved_in DATETIME NOT NULL, \n\tdate_moved_out DATETIME NOT NULL, \n\tother_details VARCHAR(255), \n\tPRIMARY KEY (resident_id, property_id, date_moved_in), \n\tFOREIGN KEY(property_id) REFERENCES \"Properties\" (property_id)\n)\n/\nColumns in Residents and 3 examples in each column for high cardinality columns :\nresident_id : 87, 38, 37\nproperty_id : 954, 120, 108\ndate_moved_out : 2018-01-28 13:19:54, 2017-11-14 06:28:48, 2018-02-22 06:24:15\nother_details : Anderson Batz, Jacques Glover II, Jess Wyman\n/\n/\nColumns in Residents and all categories for low cardinality columns :\ndate_moved_in : 2016-09-27 12:00:00, 2017-06-17 15:43:33, 2015-03-27 12:00:00\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 status (\n\tstation_id INTEGER, \n\tbikes_available INTEGER, \n\tdocks_available INTEGER, \n\ttime TEXT, \n\tFOREIGN KEY(station_id) REFERENCES station (id)\n)\n/\nColumns in status and 3 examples in each column for high cardinality columns :\ntime : 2015-06-02 13:25:02, 2015-06-02 14:06:02, 2015-06-02 14:41:02\n/\n/\nColumns in status and all categories for low cardinality columns :\nstation_id : 4, 3\nbikes_available : 7, 6, 12\ndocks_available : 4, 5, 3\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 \"Parking_Fines\" (\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 Parking_Fines and all categories for low cardinality columns :\ncouncil_tax_id : 10, 9\ncmi_cross_ref_id : 4, 81\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 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 \"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 \"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 \"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 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 \"Product_Categories\" (\n\tproduction_type_code VARCHAR(15), \n\tproduct_type_description VARCHAR(80), \n\tvat_rating DECIMAL(19, 4), \n\tPRIMARY KEY (production_type_code)\n)\n/\nColumns in Product_Categories and all categories for low cardinality columns :\nproduction_type_code : Food, Books, DVDs, Electronics\nproduct_type_description : Food, Books, Dvd products, Electrical devices\nvat_rating : 15.8400, 11.4000, 13.9500, 17.9000\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 enrollments (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"TotalEnrollment_AY\" INTEGER, \n\t\"FTE_AY\" INTEGER, \n\tPRIMARY KEY (\"Campus\", \"Year\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in enrollments and 3 examples in each column for high cardinality columns :\nYear : 1979, 2004, 1937\nTotalEnrollment_AY : 495, 5734, 9547\nFTE_AY : 3877, 14324, 12876\n/\n/\nColumns in enrollments and all categories for low cardinality columns :\nCampus : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE route (\n\ttrain_id INTEGER, \n\tstation_id INTEGER, \n\tPRIMARY KEY (train_id, station_id), \n\tFOREIGN KEY(station_id) REFERENCES station (id), \n\tFOREIGN KEY(train_id) REFERENCES train (id)\n)\n/\nColumns in route and all categories for low cardinality columns :\ntrain_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nstation_id : 1, 2, 5, 7, 8, 4, 6, 3, 9\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 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 \"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 \"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 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 all cities where students live." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code.\nThe SQL query I'll be generating is:\nSELECT DISTINCT city_code FROM Student" } ]
[ { "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 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 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 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 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\" (\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 \"Parking_Fines\" (\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 Parking_Fines and all categories for low cardinality columns :\ncouncil_tax_id : 10, 9\ncmi_cross_ref_id : 4, 81\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 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 \"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 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 \nCREATE TABLE \"Services\" (\n\tservice_id INTEGER, \n\tservice_type_code VARCHAR(15) NOT NULL, \n\tservice_name VARCHAR(80), \n\tservice_descriptio VARCHAR(255), \n\tPRIMARY KEY (service_id)\n)\n/\nColumns in Services and 3 examples in each column for high cardinality columns :\nservice_id : 1, 13, 11\n/\n/\nColumns in Services and all categories for low cardinality columns :\nservice_type_code : Welfare, Health, Education\nservice_name : Welfare, Health, Education\nservice_descriptio : Welfare, Health, Education\n/\n \nCREATE TABLE member (\n\t\"Member_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Country\" TEXT, \n\t\"College_ID\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\"), \n\tFOREIGN KEY(\"College_ID\") REFERENCES college (\"College_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 : Tom Weiskopf, Tom Watson, Pat Fitzsimons, Homero Blancas, Jack Nicklaus, Billy Casper, J. C. Snead, Arnold Palmer, Lee Trevino, Bobby Nichols\nCountry : United States, Canada\nCollege_ID : 1, 2, 5, 4, 3\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 \"Payments\" (\n\tpayment_id INTEGER, \n\tbooking_id INTEGER, \n\tcustomer_id INTEGER NOT NULL, \n\tpayment_type_code VARCHAR(15) NOT NULL, \n\tamount_paid_in_full_yn VARCHAR(1), \n\tpayment_date DATETIME, \n\tamount_due DECIMAL(19, 4), \n\tamount_paid DECIMAL(19, 4), \n\tPRIMARY KEY (payment_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in Payments and 3 examples in each column for high cardinality columns :\npayment_id : 1, 13, 11\npayment_date : 2018-03-22 15:00:23, 2018-03-03 13:39:44, 2018-03-12 23:00:55\namount_due : 407.5100, 686.8500, 678.2900\namount_paid : 681.2100, 704.4100, 666.4500\n/\n/\nColumns in Payments and all categories for low cardinality columns :\nbooking_id : 1, 13, 5, 8, 4, 6, 14, 3, 15, 9\ncustomer_id : 1, 11, 10, 5, 7, 8, 12, 14, 15, 9\npayment_type_code : Cash, Direct Debit, Credit Card, Check\namount_paid_in_full_yn : 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 \"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 \"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 \"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 \"Type_Of_Restaurant\" (\n\t\"ResID\" INTEGER, \n\t\"ResTypeID\" INTEGER, \n\tFOREIGN KEY(\"ResID\") REFERENCES \"Restaurant\" (\"ResID\"), \n\tFOREIGN KEY(\"ResTypeID\") REFERENCES \"Restaurant_Type\" (\"ResTypeID\")\n)\n/\nColumns in Type_Of_Restaurant and all categories for low cardinality columns :\nResID : 1, 2\nResTypeID : 1, 2\n/\n \nCREATE TABLE school_details (\n\t\"School_ID\" INTEGER, \n\t\"Nickname\" TEXT, \n\t\"Colors\" TEXT, \n\t\"League\" TEXT, \n\t\"Class\" TEXT, \n\t\"Division\" TEXT, \n\tPRIMARY KEY (\"School_ID\"), \n\tFOREIGN KEY(\"School_ID\") REFERENCES school (\"School_ID\")\n)\n/\nColumns in school_details and all categories for low cardinality columns :\nSchool_ID : 1, 2, 5, 4, 6, 3\nNickname : Auks, Raiders, Silver Eagles, Seahawks, Buccaneers, Tigers\nColors : Dark Green and White, Blue and Yellow, Maroon and White, Blue and Gold, Garnet and White, Silver and Maroon\nLeague : DSHA\nClass : Flight B, Flight A, Fight A\nDivision : Division 1, Division 2, Division 3\n/\n" }, { "role": "user", "content": "What cities do students live in?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code.\nThe SQL query I'll be generating is:\nSELECT DISTINCT city_code FROM Student" } ]
[ { "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 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 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 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 \"Museums\" (\n\t\"Museum_ID\" INTEGER NOT NULL, \n\t\"Museum_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Museum_ID\"), \n\tFOREIGN KEY(\"Museum_ID\") REFERENCES \"Tourist_Attractions\" (\"Tourist_Attraction_ID\")\n)\n/\nColumns in Museums and all categories for low cardinality columns :\nMuseum_ID : 2113, 2701, 5076\nMuseum_Details : MoMA, The Metropolitan Museum of Art, Yale Center for British Art\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 \"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 \"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 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 flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\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 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 \"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 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 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 \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 \"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 \"Artist\" (\n\t\"ArtistId\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(120) DEFAULT NULL, \n\tPRIMARY KEY (\"ArtistId\")\n)\n/\nColumns in Artist and 3 examples in each column for high cardinality columns :\nArtistId : 87, 56, 65\nName : Smashing Pumpkins, Santana Feat. Eric Clapton, Godsmack\n/\n\n" }, { "role": "user", "content": "Show first name, last name, age for all female students. Their sex is F." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Fname, Lname, Age, Sex.\nThe SQL query I'll be generating is:\nSELECT Fname , Lname , Age FROM Student WHERE Sex = 'F'" } ]
[ { "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 \"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 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 \"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 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 \"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 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 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 \"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 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 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 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 \"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 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 \"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 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 \"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 \"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" }, { "role": "user", "content": "What are the full names and ages for all female students whose sex is F?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Fname, Lname, Age, Sex.\nThe SQL query I'll be generating is:\nSELECT Fname , Lname , Age FROM Student WHERE Sex = 'F'" } ]
[ { "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 (\n\t\"repair_ID\" INTEGER, \n\tname TEXT, \n\t\"Launch_Date\" TEXT, \n\t\"Notes\" TEXT, \n\tPRIMARY KEY (\"repair_ID\")\n)\n/\nColumns in repair and all categories for low cardinality columns :\nrepair_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nname : OPS 3042, OPS 3491, OPS 3360, OPS 3754, OPS 3467, Discoverer 3, Discoverer 1, OPS 3236, Discoverer\nLaunch_Date : 10 Jun 2014, 13 Jun 2014, 05 Aug 2014, 28 Feb 2009, 24 Mar 2014, 21 Jan 2009, 18 Nov 2014, 19 Jun 2014, 03 Jun 2009\nNotes : Out-of-focus area on some film., repair failed. Guidance system failed. No orbit., repair Failed. Failed to achieve orbit, First object in polar orbit, repair failed. Failed to achieve orbit, Cameras operated successfully., Cameras operated satisfactorily\n/\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 \"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 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 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 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 \"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 \"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 \"constructorStandings\" (\n\t\"constructorStandingsId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"constructorId\" INTEGER, \n\tpoints REAL, \n\tposition INTEGER, \n\t\"positionText\" TEXT, \n\twins INTEGER, \n\tPRIMARY KEY (\"constructorStandingsId\"), \n\tFOREIGN KEY(\"constructorId\") REFERENCES constructors (\"constructorId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\")\n)\n/\nColumns in constructorStandings and 3 examples in each column for high cardinality columns :\nconstructorStandingsId : 87, 56, 65\nraceId : 21, 72, 71\nconstructorId : 1, 11, 2\npoints : 96.0, 8.0, 47.0\nposition : 1, 11, 2\npositionText : 1, 11, 2\n/\n/\nColumns in constructorStandings and all categories for low cardinality columns :\nwins : 1, 2, 5, 7, 8, 4, 6, 3, 0\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 \"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 \"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 \"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 pilot (\n\t\"Pilot_Id\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(50) NOT NULL, \n\t\"Age\" INTEGER NOT NULL, \n\tPRIMARY KEY (\"Pilot_Id\")\n)\n/\nColumns in pilot and 3 examples in each column for high cardinality columns :\nPilot_Id : 1, 11, 2\nName : Winnifred Boyle, Mr. Cristian Halvorson II, Katheryn Gorczany IV\n/\n/\nColumns in pilot and all categories for low cardinality columns :\nAge : 26, 37, 20, 25, 33, 30, 23, 29, 31\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" }, { "role": "user", "content": "Show student ids for all male students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: StuID, Sex.\nThe SQL query I'll be generating is:\nSELECT StuID FROM Student WHERE Sex = 'M'" } ]
[ { "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 airport (\n\t\"Airport_ID\" INTEGER, \n\t\"Airport_Name\" TEXT, \n\t\"Total_Passengers\" REAL, \n\t\"%_Change_2007\" TEXT, \n\t\"International_Passengers\" REAL, \n\t\"Domestic_Passengers\" REAL, \n\t\"Transit_Passengers\" REAL, \n\t\"Aircraft_Movements\" REAL, \n\t\"Freight_Metric_Tonnes\" REAL, \n\tPRIMARY KEY (\"Airport_ID\")\n)\n/\nColumns in airport and all categories for low cardinality columns :\nAirport_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAirport_Name : Bristol, London Luton, East Midlands, Birmingham Airport, Glasgow International, London Stansted, London Heathrow, London Gatwick, Edinburgh, Manchester\nTotal_Passengers : 8178891.0, 5620673.0, 34205887.0, 9627589.0, 67054745.0, 6267114.0, 10180734.0, 21219195.0, 22360364.0, 9006702.0\n%_Change_2007 : 2.6%, 4.0%, 6.0%, 1.5%, 0.5%, 5.7%, 2.9%, 4.3%, 3.8%, 7.0%\nInternational_Passengers : 3711140.0, 8105162.0, 3943139.0, 19996947.0, 5057051.0, 4870184.0, 8853224.0, 61344438.0, 30431051.0, 18119230.0\nDomestic_Passengers : 746094.0, 5562516.0, 1171605.0, 2943719.0, 1471538.0, 4192121.0, 3730963.0, 1320678.0, 2343428.0, 5281038.0\nTransit_Passengers : 156246.0, 50889.0, 6832.0, 19989.0, 43873.0, 43631.0, 14524.0, 38458.0, 4395.0, 147791.0\nAircraft_Movements : 478693.0, 117859.0, 204610.0, 193282.0, 125550.0, 76517.0, 112227.0, 100087.0, 93038.0, 263653.0\nFreight_Metric_Tonnes : 3.0, 261507.0, 12418.0, 40518.0, 197738.0, 141781.0, 107702.0, 3546.0, 12192.0, 1397054.0\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 \"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 \"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 flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE member_attendance (\n\t\"Member_ID\" INTEGER, \n\t\"Performance_ID\" INTEGER, \n\t\"Num_of_Pieces\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Performance_ID\"), \n\tFOREIGN KEY(\"Performance_ID\") REFERENCES performance (\"Performance_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in member_attendance and all categories for low cardinality columns :\nMember_ID : 1, 11, 2, 5, 7, 4, 3\nPerformance_ID : 1, 2, 4, 6, 3\nNum_of_Pieces : 1, 2, 4, 3\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 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 \"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 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 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 \"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 \"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 \"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 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 \"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 route (\n\ttrain_id INTEGER, \n\tstation_id INTEGER, \n\tPRIMARY KEY (train_id, station_id), \n\tFOREIGN KEY(station_id) REFERENCES station (id), \n\tFOREIGN KEY(train_id) REFERENCES train (id)\n)\n/\nColumns in route and all categories for low cardinality columns :\ntrain_id : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nstation_id : 1, 2, 5, 7, 8, 4, 6, 3, 9\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 \"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" }, { "role": "user", "content": "What are the student ids for all male students?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: StuID, Sex.\nThe SQL query I'll be generating is:\nSELECT StuID FROM Student WHERE Sex = 'M'" } ]
[ { "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\" 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 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 \"DEPARTMENT\" (\n\t\"DEPT_CODE\" VARCHAR(10), \n\t\"DEPT_NAME\" VARCHAR(30), \n\t\"SCHOOL_CODE\" VARCHAR(8), \n\t\"EMP_NUM\" INTEGER, \n\t\"DEPT_ADDRESS\" VARCHAR(20), \n\t\"DEPT_EXTENSION\" VARCHAR(4), \n\tPRIMARY KEY (\"DEPT_CODE\"), \n\tFOREIGN KEY(\"EMP_NUM\") REFERENCES \"EMPLOYEE\" (\"EMP_NUM\")\n)\n/\nColumns in DEPARTMENT and 3 examples in each column for high cardinality columns :\nDEPT_CODE : ART, ECON/FIN, HIST\nDEPT_NAME : History, Computer Info. Systems, Biology\nEMP_NUM : 114, 106, 342\nDEPT_ADDRESS : KLR 126, Box 55, AAK 230, Box 415, KLR 333, Box 56\nDEPT_EXTENSION : 1867, 3126, 4117\n/\n/\nColumns in DEPARTMENT and all categories for low cardinality columns :\nSCHOOL_CODE : BUS, A&SCI\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 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 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 \"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 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 \"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 \"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 \"Suppliers\" (\n\tsupplier_id INTEGER, \n\tsupplier_name VARCHAR(80), \n\tsupplier_phone VARCHAR(80), \n\tPRIMARY KEY (supplier_id)\n)\n/\nColumns in Suppliers and all categories for low cardinality columns :\nsupplier_id : 1, 2, 4, 3\nsupplier_name : Tesco, Lidl, AB Store, Audi\nsupplier_phone : 287-071-1153x254, (692)009-5928, 1-432-960-2402x1734, 1-483-283-4742\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 \"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 \"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 \"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 \"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 \"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 \"Products_Booked\" (\n\tbooking_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\treturned_yn VARCHAR(1), \n\treturned_late_yn VARCHAR(1), \n\tbooked_count INTEGER, \n\tbooked_amount FLOAT, \n\tPRIMARY KEY (booking_id, product_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in Products_Booked and 3 examples in each column for high cardinality columns :\nbooked_amount : 398.68, 123.43, 344.38\n/\n/\nColumns in Products_Booked and all categories for low cardinality columns :\nbooking_id : 1, 13, 11, 10, 2, 4, 14, 3, 15\nproduct_id : 1, 2, 5, 4, 3\nreturned_yn : 1\nreturned_late_yn : 1, 0\nbooked_count : 1, 2, 5, 4, 6, 3, 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\"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" }, { "role": "user", "content": "How many students are age 18?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Student WHERE age = 18" } ]
[ { "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 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 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 \"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 \"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 \"Premises\" (\n\tpremise_id INTEGER, \n\tpremises_type VARCHAR(15) NOT NULL, \n\tpremise_details VARCHAR(255), \n\tPRIMARY KEY (premise_id)\n)\n/\nColumns in Premises and 3 examples in each column for high cardinality columns :\npremise_id : 1, 13, 11\npremise_details : 5109 Jules Squares Apt. 082, 676 Kelly Spur, 00100 Green Mountains Apt. 653\n/\n/\nColumns in Premises and all categories for low cardinality columns :\npremises_type : Residence, Office, Warehouse\n/\n \nCREATE TABLE college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\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 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 \"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 \"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 \"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 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 job_history (\n\t\"EMPLOYEE_ID\" DECIMAL(6, 0) NOT NULL, \n\t\"START_DATE\" DATE NOT NULL, \n\t\"END_DATE\" DATE NOT NULL, \n\t\"JOB_ID\" VARCHAR(10) NOT NULL, \n\t\"DEPARTMENT_ID\" DECIMAL(4, 0) DEFAULT NULL, \n\tPRIMARY KEY (\"EMPLOYEE_ID\", \"START_DATE\"), \n\tFOREIGN KEY(\"EMPLOYEE_ID\") REFERENCES employees (\"EMPLOYEE_ID\"), \n\tFOREIGN KEY(\"DEPARTMENT_ID\") REFERENCES departments (\"DEPARTMENT_ID\"), \n\tFOREIGN KEY(\"JOB_ID\") REFERENCES jobs (\"JOB_ID\")\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 \"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 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 \"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" }, { "role": "user", "content": "How many students are 18 years old?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Student WHERE age = 18" } ]
[ { "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 \"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 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\"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 \"Band\" (\n\t\"Id\" INTEGER, \n\t\"Firstname\" TEXT, \n\t\"Lastname\" TEXT, \n\tPRIMARY KEY (\"Id\")\n)\n/\nColumns in Band and all categories for low cardinality columns :\nId : \nFirstname : \nLastname : \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 \"Songs\" (\n\t\"SongId\" INTEGER, \n\t\"Title\" TEXT, \n\tPRIMARY KEY (\"SongId\")\n)\n/\nColumns in Songs and all categories for low cardinality columns :\nSongId : \nTitle : \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 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 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 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 \"Timed_Status_of_Things\" (\n\tthing_id INTEGER NOT NULL, \n\t\"Date_and_Date\" DATETIME NOT NULL, \n\t\"Status_of_Thing_Code\" CHAR(15) NOT NULL, \n\tPRIMARY KEY (thing_id, \"Date_and_Date\", \"Status_of_Thing_Code\"), \n\tFOREIGN KEY(thing_id) REFERENCES \"Things\" (thing_id)\n)\n/\nColumns in Timed_Status_of_Things and 3 examples in each column for high cardinality columns :\nthing_id : 26, 80, 2\nDate_and_Date : 2017-06-19 02:59:21, 2017-08-05 02:10:02, 2016-10-08 08:02:57\n/\n/\nColumns in Timed_Status_of_Things and all categories for low cardinality columns :\nStatus_of_Thing_Code : Open, Close, In Progress\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 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 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 \"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 \"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" }, { "role": "user", "content": "Show all student ids who are older than 20." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: StuID, age.\nThe SQL query I'll be generating is:\nSELECT StuID FROM Student WHERE age > 20" } ]
[ { "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 \"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 \"Delivery_Routes\" (\n\troute_id INTEGER, \n\troute_name VARCHAR(50), \n\tother_route_details VARCHAR(255), \n\tPRIMARY KEY (route_id)\n)\n/\nColumns in Delivery_Routes and 3 examples in each column for high cardinality columns :\nroute_id : 1, 13, 11\nroute_name : Huel, Armstrong and Senger, Brekke, Powlowski and Fritsch, Heidenreich Group\nother_route_details : 534 Lubowitz Terrace\nLake Tomfort, LA 52697-4998, 941 Ritchie Plains Suite 833\nNorth Jerry, LA 32804-7405, 36578 Kirsten Terrace\nKrajcikside, NH 29063\n/\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 \"Bookings\" (\n\t\"Booking_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Workshop_Group_ID\" VARCHAR(100) NOT NULL, \n\t\"Status_Code\" CHAR(15) NOT NULL, \n\t\"Store_ID\" INTEGER NOT NULL, \n\t\"Order_Date\" DATETIME NOT NULL, \n\t\"Planned_Delivery_Date\" DATETIME NOT NULL, \n\t\"Actual_Delivery_Date\" DATETIME NOT NULL, \n\t\"Other_Order_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Booking_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Clients\" (\"Client_ID\"), \n\tFOREIGN KEY(\"Workshop_Group_ID\") REFERENCES \"Drama_Workshop_Groups\" (\"Workshop_Group_ID\"), \n\tUNIQUE (\"Booking_ID\")\n)\n/\nColumns in Bookings and 3 examples in each column for high cardinality columns :\nBooking_ID : 1, 13, 11\nCustomer_ID : 938, 605, 591\nOrder_Date : 1971-05-11 06:53:01, 1975-11-23 06:28:47, 1975-12-30 14:12:32\nPlanned_Delivery_Date : 2014-06-05 10:19:46, 2013-03-10 18:47:05, 1993-04-17 23:53:01\nActual_Delivery_Date : 1983-02-07 20:27:10, 1971-01-13 13:24:52, 1983-10-09 10:48:48\n/\n/\nColumns in Bookings and all categories for low cardinality columns :\nWorkshop_Group_ID : 954, 838, 405, 735, 140, 708, 176, 685, 136\nStatus_Code : stop, good\nStore_ID : 1, 2, 5, 7, 8, 4, 6, 9\nOther_Order_Details : None\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 \"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 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 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 \"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 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 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 \"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 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 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 \"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 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 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 \"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 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 csu_fees (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"CampusFee\" INTEGER, \n\tPRIMARY KEY (\"Campus\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in csu_fees and 3 examples in each column for high cardinality columns :\nCampus : 17, 21, 9\nCampusFee : 1916, 2009, 2204\n/\n/\nColumns in csu_fees and all categories for low cardinality columns :\nYear : 2003, 1996\n/\n" }, { "role": "user", "content": "What are the student ids for students over 20 years old?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: StuID, age.\nThe SQL query I'll be generating is:\nSELECT StuID FROM Student WHERE age > 20" } ]
[ { "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 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 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 player (\n\t\"Player_ID\" INTEGER, \n\tname TEXT, \n\t\"Position\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Apps\" REAL, \n\t\"Tries\" REAL, \n\t\"Goals\" TEXT, \n\t\"Points\" REAL, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nname : Michael Platt, Tame Tupou, Terry Newton\nApps : 30.0, 29.0, 24.0\n/\n/\nColumns in player and all categories for low cardinality columns :\nPosition : Scrum Half, Right Centre, Prop, Loose Forward, Hooker, Right Wing, Stand Off, Second Row, Left Wing, Full Back\nClub_ID : 1, 2, 5, 4, 3\nTries : 3.0, 8.0, 1.0, 6.0, 9.0, 2.0, 4.0, 5.0\nGoals : 50/60, 90/106, 0/1, 0\nPoints : 36.0, 8.0, 16.0, 12.0, 24.0, 188.0, 32.0, 110.0, 4.0, 20.0\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 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 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 \"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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 \"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 \"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 \"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 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 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 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 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 \"Students\" (\n\tstudent_id INTEGER NOT NULL, \n\tstudent_details VARCHAR(255), \n\tPRIMARY KEY (student_id), \n\tFOREIGN KEY(student_id) REFERENCES \"People\" (person_id)\n)\n/\nColumns in Students and all categories for low cardinality columns :\nstudent_id : 151, 141, 131, 171, 111, 161, 181, 121\nstudent_details : Barry, Marry, Martin, Sarah, Joe, John, Nikhil, Nancy\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": "Which city does the student whose last name is \"Kim\" live in?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code, LName, Kim.\nThe SQL query I'll be generating is:\nSELECT city_code FROM Student WHERE LName = \"Kim\"" } ]
[ { "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 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 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 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 \"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 \"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 \"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 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 \"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 \"Benefits_Overpayments\" (\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 Benefits_Overpayments and all categories for low cardinality columns :\ncouncil_tax_id : 7, 8, 6, 3\ncmi_cross_ref_id : 83, 65, 41, 48\n/\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 enrollments (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"TotalEnrollment_AY\" INTEGER, \n\t\"FTE_AY\" INTEGER, \n\tPRIMARY KEY (\"Campus\", \"Year\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in enrollments and 3 examples in each column for high cardinality columns :\nYear : 1979, 2004, 1937\nTotalEnrollment_AY : 495, 5734, 9547\nFTE_AY : 3877, 14324, 12876\n/\n/\nColumns in enrollments and all categories for low cardinality columns :\nCampus : 1, 2, 5, 4, 3\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 \"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 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 \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 broadcast (\n\t\"Channel_ID\" INTEGER, \n\t\"Program_ID\" INTEGER, \n\t\"Time_of_day\" TEXT, \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 and all categories for low cardinality columns :\nChannel_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nProgram_ID : 1, 2, 4, 3\nTime_of_day : Morning, Night, Noon\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 \"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": "Give the city that the student whose family name is Kim lives in." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code, LName, Kim.\nThe SQL query I'll be generating is:\nSELECT city_code FROM Student WHERE LName = \"Kim\"" } ]
[ { "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 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 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 \"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 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 \"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 \"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 \"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 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 \"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 \"Ref_Document_Status\" (\n\tdocument_status_code CHAR(15) NOT NULL, \n\tdocument_status_description VARCHAR(255) NOT NULL, \n\tPRIMARY KEY (document_status_code)\n)\n/\nColumns in Ref_Document_Status and all categories for low cardinality columns :\ndocument_status_code : done, overdue, working\ndocument_status_description : mailed late, mailed, currently working on\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 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 \"Employee\" (\n\t\"EmployeeId\" INTEGER NOT NULL, \n\t\"LastName\" VARCHAR(20) NOT NULL, \n\t\"FirstName\" VARCHAR(20) NOT NULL, \n\t\"Title\" VARCHAR(30) DEFAULT NULL, \n\t\"ReportsTo\" INTEGER DEFAULT NULL, \n\t\"BirthDate\" DATETIME DEFAULT NULL, \n\t\"HireDate\" DATETIME DEFAULT NULL, \n\t\"Address\" VARCHAR(70) DEFAULT NULL, \n\t\"City\" VARCHAR(40) DEFAULT NULL, \n\t\"State\" VARCHAR(40) DEFAULT NULL, \n\t\"Country\" VARCHAR(40) DEFAULT NULL, \n\t\"PostalCode\" VARCHAR(10) DEFAULT NULL, \n\t\"Phone\" VARCHAR(24) DEFAULT NULL, \n\t\"Fax\" VARCHAR(24) DEFAULT NULL, \n\t\"Email\" VARCHAR(60) DEFAULT NULL, \n\tPRIMARY KEY (\"EmployeeId\"), \n\tFOREIGN KEY(\"ReportsTo\") REFERENCES \"Employee\" (\"EmployeeId\")\n)\n/\nColumns in Employee and all categories for low cardinality columns :\nEmployeeId : 1, 2, 5, 7, 8, 4, 6, 3\nLastName : Callahan, Mitchell, Adams, Park, Edwards, Peacock, Johnson, King\nFirstName : Jane, Michael, Steve, Laura, Margaret, Andrew, Robert, Nancy\nTitle : IT Staff, Sales Manager, IT Manager, Sales Support Agent, General Manager\nReportsTo : 1, None, 2, 6\nBirthDate : 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\nHireDate : 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\nPostalCode : 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 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 \"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" }, { "role": "user", "content": "Who is the advisor of student with ID 1004?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Advisor, StuID.\nThe SQL query I'll be generating is:\nSELECT Advisor FROM Student WHERE StuID = 1004" } ]
[ { "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 \"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 \"constructorResults\" (\n\t\"constructorResultsId\" INTEGER, \n\t\"raceId\" INTEGER, \n\t\"constructorId\" INTEGER, \n\tpoints REAL, \n\tstatus TEXT, \n\tPRIMARY KEY (\"constructorResultsId\"), \n\tFOREIGN KEY(\"constructorId\") REFERENCES constructors (\"constructorId\"), \n\tFOREIGN KEY(\"raceId\") REFERENCES races (\"raceId\")\n)\n/\nColumns in constructorResults and 3 examples in each column for high cardinality columns :\nconstructorResultsId : 87, 56, 65\nraceId : 36, 21, 35\nconstructorId : 1, 11, 2\npoints : 8.0, 3.0, 16.0\n/\n/\nColumns in constructorResults and all categories for low cardinality columns :\nstatus : NULL, D\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 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 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 \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 \"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 \"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 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 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 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 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 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 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 \"Products\" (\n\t\"Product_ID\" VARCHAR(100) NOT NULL, \n\t\"Product_Name\" VARCHAR(255), \n\t\"Product_Price\" DECIMAL(20, 4), \n\t\"Product_Description\" VARCHAR(255), \n\t\"Other_Product_Service_Details\" VARCHAR(255), \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 : 250, 300, 233\nProduct_Price : 634660.0000, 1577.0000, 900.0000\n/\n/\nColumns in Products and all categories for low cardinality columns :\nProduct_Name : dinning, photo, film\nProduct_Description : None\nOther_Product_Service_Details : None\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 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 \"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 \"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" }, { "role": "user", "content": "Who advises student 1004?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: Advisor, StuID.\nThe SQL query I'll be generating is:\nSELECT Advisor FROM Student WHERE StuID = 1004" } ]
[ { "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 \"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 \"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 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 \"Statements\" (\n\t\"Statement_ID\" INTEGER NOT NULL, \n\t\"Statement_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Statement_ID\"), \n\tFOREIGN KEY(\"Statement_ID\") REFERENCES \"Documents\" (\"Document_ID\")\n)\n/\nColumns in Statements and all categories for low cardinality columns :\nStatement_ID : 192, 57\nStatement_Details : Private Project, Open Project\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 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 \"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 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 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 \"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 \"Actual_Orders\" (\n\tactual_order_id INTEGER, \n\torder_status_code VARCHAR(10) NOT NULL, \n\tregular_order_id INTEGER NOT NULL, \n\tactual_order_date DATETIME, \n\tPRIMARY KEY (actual_order_id), \n\tFOREIGN KEY(regular_order_id) REFERENCES \"Regular_Orders\" (regular_order_id)\n)\n/\nColumns in Actual_Orders and 3 examples in each column for high cardinality columns :\nactual_order_id : 1, 13, 11\nregular_order_id : 1, 13, 11\nactual_order_date : 2018-03-05 17:31:36, 2018-03-02 08:33:39, 2018-02-26 01:55:52\n/\n/\nColumns in Actual_Orders and all categories for low cardinality columns :\norder_status_code : Cancel, Success\n/\n \nCREATE TABLE \"match\" (\n\t\"Match_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Score\" TEXT, \n\t\"Result\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (\"Match_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nMatch_ID : 1, 2, 5, 4, 6, 3\nDate : 23 July 1992, 18 February 1992, 19 July 1992, 23 July 2000, 4 April 1993\nVenue : Estadio Rigoberto López , Managua , Nicaragua, Estadio Cuscatlán , San Salvador , El Salvador\nScore : 3-0, 2–1, 1-0, 1–0\nResult : 5-1, 7–1, 5-0, 2–1, 2-0\nCompetition : 1994 FIFA World Cup qualification, Friendly match, 2002 FIFA World Cup qualification\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 \"Services\" (\n\t\"Service_ID\" INTEGER NOT NULL, \n\t\"Service_name\" VARCHAR(40), \n\tPRIMARY KEY (\"Service_ID\")\n)\n/\nColumns in Services and all categories for low cardinality columns :\nService_ID : 1, 9, 4, 6\nService_name : Upgrade a policy, New policy application, Close a policy, Change a policy\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 \"Departments\" (\n\tdepartment_id INTEGER, \n\tdept_store_id INTEGER NOT NULL, \n\tdepartment_name VARCHAR(80), \n\tPRIMARY KEY (department_id), \n\tFOREIGN KEY(dept_store_id) REFERENCES \"Department_Stores\" (dept_store_id)\n)\n/\nColumns in Departments and all categories for low cardinality columns :\ndepartment_id : 1, 2, 5, 4, 3\ndept_store_id : 11, 4, 5\ndepartment_name : human resource, managing, marketing, purchasing, advertising\n/\n \nCREATE TABLE \"Authors\" (\n\t\"authID\" INTEGER, \n\tlname TEXT, \n\tfname TEXT, \n\tPRIMARY KEY (\"authID\")\n)\n/\nColumns in Authors and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\nlname : Gibbons, Turon, Ueno\nfname : Daniel W. H., Tim, Ralf\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 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 \"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 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 \"View_Unit_Status\" (\n\tapt_id INTEGER, \n\tapt_booking_id INTEGER, \n\tstatus_date DATETIME NOT NULL, \n\tavailable_yn NUMERIC, \n\tPRIMARY KEY (status_date), \n\tFOREIGN KEY(apt_id) REFERENCES \"Apartments\" (apt_id), \n\tFOREIGN KEY(apt_booking_id) REFERENCES \"Apartment_Bookings\" (apt_booking_id)\n)\n/\nColumns in View_Unit_Status and 3 examples in each column for high cardinality columns :\napt_id : 1, 13, 11\napt_booking_id : 924, 497, 575\nstatus_date : 2011-02-12 09:04:07, 2003-07-25 10:13:48, 2000-02-04 07:50:09\n/\n/\nColumns in View_Unit_Status and all categories for low cardinality columns :\navailable_yn : 0E-10, 1.0000000000\n/\n" }, { "role": "user", "content": "How many students live in HKG or CHI?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code, HKG, CHI.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Student WHERE city_code = \"HKG\" OR city_code = \"CHI\"" } ]
[ { "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\" (\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 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 \"Ref_Detention_Type\" (\n\tdetention_type_code VARCHAR(10), \n\tdetention_type_description VARCHAR(80), \n\tPRIMARY KEY (detention_type_code)\n)\n/\nColumns in Ref_Detention_Type and all categories for low cardinality columns :\ndetention_type_code : LUNCH, BREAK , AFTER\ndetention_type_description : After School, During Break time, Lunch-time\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 \"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 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 \"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 \"Addresses\" (\n\taddress_id INTEGER, \n\tline_1_number_building VARCHAR(80), \n\tcity 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 : 7089 Mueller Forks, 535 Ariel Brook, 3904 Stroman Passage\ncity : Buckridgehaven, South Eugene, Elviebury\nzip_postcode : 22194, 99903, 14445\nstate_province_county : Louisiana, Kentucky, Ohio\n/\n/\nColumns in Addresses and all categories for low cardinality columns :\ncountry : USA\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 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 \"Ref_Characteristic_Types\" (\n\tcharacteristic_type_code VARCHAR(15), \n\tcharacteristic_type_description VARCHAR(80), \n\tPRIMARY KEY (characteristic_type_code)\n)\n/\nColumns in Ref_Characteristic_Types and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_type_description : Grade, Purity\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 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 \"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 \"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 \"match\" (\n\t\"Match_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Score\" TEXT, \n\t\"Result\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (\"Match_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nMatch_ID : 1, 2, 5, 4, 6, 3\nDate : 23 July 1992, 18 February 1992, 19 July 1992, 23 July 2000, 4 April 1993\nVenue : Estadio Rigoberto López , Managua , Nicaragua, Estadio Cuscatlán , San Salvador , El Salvador\nScore : 3-0, 2–1, 1-0, 1–0\nResult : 5-1, 7–1, 5-0, 2–1, 2-0\nCompetition : 1994 FIFA World Cup qualification, Friendly match, 2002 FIFA World Cup qualification\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 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" }, { "role": "user", "content": "Give the number of students living in either HKG or CHI." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code, HKG, CHI.\nThe SQL query I'll be generating is:\nSELECT count(*) FROM Student WHERE city_code = \"HKG\" OR city_code = \"CHI\"" } ]
[ { "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\" (\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 \"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 \"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 \"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 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 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 \"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 railway_manage (\n\t\"Railway_ID\" INTEGER, \n\t\"Manager_ID\" INTEGER, \n\t\"From_Year\" TEXT, \n\tPRIMARY KEY (\"Railway_ID\", \"Manager_ID\"), \n\tFOREIGN KEY(\"Manager_ID\") REFERENCES manager (\"Manager_ID\"), \n\tFOREIGN KEY(\"Railway_ID\") REFERENCES railway (\"Railway_ID\")\n)\n/\nColumns in railway_manage and all categories for low cardinality columns :\nRailway_ID : 7, 8, 2, 9\nManager_ID : 1, 2, 4, 3\nFrom_Year : 2012, 2010, 2011, 2013\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 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 \"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 \"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 \"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 \"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 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 \"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 \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 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" }, { "role": "user", "content": "Show the minimum, average, and maximum age of all students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age.\nThe SQL query I'll be generating is:\nSELECT min(age) , avg(age) , max(age) FROM Student" } ]
[ { "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 \"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 \"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 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 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 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 \"Ref_Characteristic_Types\" (\n\tcharacteristic_type_code VARCHAR(15), \n\tcharacteristic_type_description VARCHAR(80), \n\tPRIMARY KEY (characteristic_type_code)\n)\n/\nColumns in Ref_Characteristic_Types and all categories for low cardinality columns :\ncharacteristic_type_code : Grade, Purity\ncharacteristic_type_description : Grade, Purity\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 \"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 \"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 \"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 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 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 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 employee (\n\t\"Fname\" TEXT, \n\t\"Minit\" TEXT, \n\t\"Lname\" TEXT, \n\t\"Ssn\" INTEGER, \n\t\"Bdate\" TEXT, \n\t\"Address\" TEXT, \n\t\"Sex\" TEXT, \n\t\"Salary\" INTEGER, \n\t\"Super_ssn\" INTEGER, \n\t\"Dno\" INTEGER, \n\tPRIMARY KEY (\"Ssn\")\n)\n/\nColumns in employee and all categories for low cardinality columns :\nFname : Joyce, James, Alicia, Ramesh, Franklin, Ahmad, Jonh, Jennifier\nMinit : E, S, K, J, T, A, V, B\nLname : Borg, Narayan, Smith, English, Zelaya, Jabbar, Wallace, Wong\nSsn : 987987987, 333445555, 453453453, 987654321, 123456789, 999887777, 888665555, 666884444\nBdate : 1969-03-29, 1965-01-09, 1955-12-08, 1968-01-19, 1937-11-10, 1972-07-31, 1962-09-15, 1941-06-20\nAddress : 980 Dallas, Houston, TX, 291 Berry, Bellaire, TX, 975 Fire Oak, Humble, TX, 3321 Castle, Spring, TX, 5631 Rice, Houston, TX, 638 Voss, Houston, TX, 450 Stone, Houston, TX, 731 Fondren, Houston, TX\nSex : F, M\nSalary : 43000, 40000, 38000, 25000, 55000, 30000\nSuper_ssn : 333445555, 888665555, 987654321, None\nDno : 1, 4, 5\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 \"Locations\" (\n\t\"Location_ID\" INTEGER NOT NULL, \n\t\"Other_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Location_ID\")\n)\n/\nColumns in Locations and 3 examples in each column for high cardinality columns :\nLocation_ID : 1, 13, 11\nOther_Details : Rowe PLC, Rowe-Stoltenberg, Fritsch LLC\n/\n\n \nCREATE TABLE phone (\n\t\"Company_name\" TEXT, \n\t\"Hardware_Model_name\" TEXT, \n\t\"Accreditation_type\" TEXT, \n\t\"Accreditation_level\" TEXT, \n\t\"Date\" TEXT, \n\tchip_model TEXT, \n\tscreen_mode TEXT, \n\tPRIMARY KEY (\"Hardware_Model_name\"), \n\tFOREIGN KEY(chip_model) REFERENCES chip_model (\"Model_name\"), \n\tFOREIGN KEY(screen_mode) REFERENCES screen_mode (\"Graphics_mode\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nCompany_name : Samsung Electronics Co Ltd, Huawei Technologies Co.Ltd., HTC Corporation, Nokia Corporation, LG Electronics, Sony Mobile Communications\nHardware_Model_name : GT-I9300, U8815 Asura, Lumia 920, Lumia 820, Lumia 620, GT-I9100, Nokia 700, LG-P760, Z520e, XPERIA T, XPERIA J\nAccreditation_type : Provisional, Full\nAccreditation_level : joyn Hot Fixes, joyn\nDate : Approved (valid until 03.05.13), Approved (valid until 06.04.13), Approved (awarded 19.11.12), Approved (awarded 05.12.12), Approved (valid until 14.09.13), Approved (awarded 23.10.12), Approved (awarded 15.11.12)\nchip_model : X50 Advanced, X5, X3i, X51v, X30 low-end, X50 Standard\nscreen_mode : 1, 2, 5, 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 \"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 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 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" }, { "role": "user", "content": "What is the minimum, mean, and maximum age across all students?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age.\nThe SQL query I'll be generating is:\nSELECT min(age) , avg(age) , max(age) FROM Student" } ]
[ { "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 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 \"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 \"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 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 \"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 \"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 \"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 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 \"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 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 \"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 \"Medication\" (\n\t\"Code\" INTEGER NOT NULL, \n\t\"Name\" VARCHAR(30) NOT NULL, \n\t\"Brand\" VARCHAR(30) NOT NULL, \n\t\"Description\" VARCHAR(30) NOT NULL, \n\tPRIMARY KEY (\"Code\")\n)\n/\nColumns in Medication and all categories for low cardinality columns :\nCode : 1, 2, 5, 4, 3\nName : Melioraurin, Procrastin-X, Awakin, Crescavitin, Thesisin\nBrand : Snafu Pharmaceuticals, Baz Industries, Bar Laboratories, Foo Labs, X\nDescription : N/A\n/\n \nCREATE TABLE \"Employee\" (\n\t\"EmployeeId\" INTEGER NOT NULL, \n\t\"LastName\" VARCHAR(20) NOT NULL, \n\t\"FirstName\" VARCHAR(20) NOT NULL, \n\t\"Title\" VARCHAR(30) DEFAULT NULL, \n\t\"ReportsTo\" INTEGER DEFAULT NULL, \n\t\"BirthDate\" DATETIME DEFAULT NULL, \n\t\"HireDate\" DATETIME DEFAULT NULL, \n\t\"Address\" VARCHAR(70) DEFAULT NULL, \n\t\"City\" VARCHAR(40) DEFAULT NULL, \n\t\"State\" VARCHAR(40) DEFAULT NULL, \n\t\"Country\" VARCHAR(40) DEFAULT NULL, \n\t\"PostalCode\" VARCHAR(10) DEFAULT NULL, \n\t\"Phone\" VARCHAR(24) DEFAULT NULL, \n\t\"Fax\" VARCHAR(24) DEFAULT NULL, \n\t\"Email\" VARCHAR(60) DEFAULT NULL, \n\tPRIMARY KEY (\"EmployeeId\"), \n\tFOREIGN KEY(\"ReportsTo\") REFERENCES \"Employee\" (\"EmployeeId\")\n)\n/\nColumns in Employee and all categories for low cardinality columns :\nEmployeeId : 1, 2, 5, 7, 8, 4, 6, 3\nLastName : Callahan, Mitchell, Adams, Park, Edwards, Peacock, Johnson, King\nFirstName : Jane, Michael, Steve, Laura, Margaret, Andrew, Robert, Nancy\nTitle : IT Staff, Sales Manager, IT Manager, Sales Support Agent, General Manager\nReportsTo : 1, None, 2, 6\nBirthDate : 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\nHireDate : 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\nPostalCode : 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 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 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" }, { "role": "user", "content": "What is the last name of the youngest student?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: LName, age.\nThe SQL query I'll be generating is:\nSELECT LName FROM Student WHERE age = (SELECT min(age) FROM Student)" } ]
[ { "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_type_code VARCHAR(20) NOT NULL, \n\taddress_line_1 VARCHAR(80), \n\taddress_line_2 VARCHAR(80), \n\ttown_city VARCHAR(80), \n\tstate VARCHAR(80), \n\temail_address VARCHAR(255), \n\tphone_number VARCHAR(80), \n\tPRIMARY KEY (customer_id)\n)\n/\nColumns in Customers and all categories for low cardinality columns :\ncustomer_id : 120, 114, 113, 116, 117, 115, 119, 118\ncustomer_type_code : Defaults on payments, Good Credit Rating\naddress_line_1 : 92189 Gulgowski Ranch Apt. 683, 05355 Marcelle Radial, 039 Jedidiah Estate Suite 537, 72144 Katlynn Flat Suite 512, 518 Mann Park, 425 Roman Tunnel, 1566 Ramona Overpass Apt. 464, 144 Legros Landing\naddress_line_2 : Suite 151, Apt. 551, Suite 035, Suite 959, Apt. 245, Apt. 495, Apt. 828, Suite 054\ntown_city : Funkstad, Tyreekhaven, North Alisaville, Maryamport, Hansenbury, Port Joshuah, West Annamariestad, Sauerberg\nstate : Pennsylvania, Hawaii, Tennessee, Kansas, Colorado, Iowa, Florida\nemail_address : hsteuber@example.org, vbogisich@example.org, rzulauf@example.org, cayla.satterfield@example.net, paige.hyatt@example.com, lavonne.frami@example.com, ubeier@example.org, vida86@example.com\nphone_number : 548.373.3603x59134, 044-468-4549, 06963347450, 997.698.4779x882, +38(3)9011433816, 578.019.7943x328, 1-369-302-7623x576, 470-803-0244\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 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 \"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 \"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 \"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 \"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 \"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 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 \nCREATE TABLE phone (\n\t\"Company_name\" TEXT, \n\t\"Hardware_Model_name\" TEXT, \n\t\"Accreditation_type\" TEXT, \n\t\"Accreditation_level\" TEXT, \n\t\"Date\" TEXT, \n\tchip_model TEXT, \n\tscreen_mode TEXT, \n\tPRIMARY KEY (\"Hardware_Model_name\"), \n\tFOREIGN KEY(chip_model) REFERENCES chip_model (\"Model_name\"), \n\tFOREIGN KEY(screen_mode) REFERENCES screen_mode (\"Graphics_mode\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nCompany_name : Samsung Electronics Co Ltd, Huawei Technologies Co.Ltd., HTC Corporation, Nokia Corporation, LG Electronics, Sony Mobile Communications\nHardware_Model_name : GT-I9300, U8815 Asura, Lumia 920, Lumia 820, Lumia 620, GT-I9100, Nokia 700, LG-P760, Z520e, XPERIA T, XPERIA J\nAccreditation_type : Provisional, Full\nAccreditation_level : joyn Hot Fixes, joyn\nDate : Approved (valid until 03.05.13), Approved (valid until 06.04.13), Approved (awarded 19.11.12), Approved (awarded 05.12.12), Approved (valid until 14.09.13), Approved (awarded 23.10.12), Approved (awarded 15.11.12)\nchip_model : X50 Advanced, X5, X3i, X51v, X30 low-end, X50 Standard\nscreen_mode : 1, 2, 5, 4, 6, 3\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 \"Faculty\" (\n\t\"FacID\" INTEGER, \n\t\"Lname\" VARCHAR(15), \n\t\"Fname\" VARCHAR(15), \n\t\"Rank\" VARCHAR(15), \n\t\"Sex\" VARCHAR(1), \n\t\"Phone\" INTEGER, \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\tPRIMARY KEY (\"FacID\")\n)\n/\nColumns in Faculty and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\nLname : Glaser, Han, James\nFname : Rao, Brenda, James\nPhone : 2105, 3593, 1035\nRoom : 288, 218, 219\n/\n/\nColumns in Faculty and all categories for low cardinality columns :\nRank : AssocProf, AsstProf, Professor, Instructor\nSex : F, M\nBuilding : Krieger, NEB, Barton\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 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 \"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 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 \"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" }, { "role": "user", "content": "Provide the last name of the youngest student." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: LName, age.\nThe SQL query I'll be generating is:\nSELECT LName FROM Student WHERE age = (SELECT min(age) FROM Student)" } ]
[ { "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 \"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 \"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 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 \"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 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 artwork (\n\t\"Artwork_ID\" INTEGER, \n\t\"Type\" TEXT, \n\t\"Name\" TEXT, \n\tPRIMARY KEY (\"Artwork_ID\")\n)\n/\nColumns in artwork and all categories for low cardinality columns :\nArtwork_ID : 1, 2, 5, 7, 8, 4, 6, 3, 9\nType : Presenter Talent Show, Program Talent Show, Presenter Music/Variety Show, Program Music/Variety Show\nName : Why, I Know, Martin, Indonesian Idol, Loving you, Daniel Mananta, Back Home, Cats, Boys\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 \"Products\" (\n\tproduct_id INTEGER, \n\tcolor_code VARCHAR(15) NOT NULL, \n\tproduct_category_code VARCHAR(15) NOT NULL, \n\tproduct_name VARCHAR(80), \n\ttypical_buying_price VARCHAR(20), \n\ttypical_selling_price VARCHAR(20), \n\tproduct_description VARCHAR(255), \n\tother_product_details VARCHAR(255), \n\tPRIMARY KEY (product_id), \n\tFOREIGN KEY(color_code) REFERENCES \"Ref_Colors\" (color_code), \n\tFOREIGN KEY(product_category_code) REFERENCES \"Ref_Product_Categories\" (product_category_code)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : peper, cumin, chili\ntypical_buying_price : , 5.578, 503.8431967\ntypical_selling_price : , 149, 10377614.847385\nproduct_description : ut, et, vel\n/\n/\nColumns in Products and all categories for low cardinality columns :\ncolor_code : 1, 2, 5, 7, 4, 9\nproduct_category_code : Spices, Seeds, Herbs\nother_product_details : None\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 \"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 \"Products_Booked\" (\n\tbooking_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\treturned_yn VARCHAR(1), \n\treturned_late_yn VARCHAR(1), \n\tbooked_count INTEGER, \n\tbooked_amount FLOAT, \n\tPRIMARY KEY (booking_id, product_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in Products_Booked and 3 examples in each column for high cardinality columns :\nbooked_amount : 398.68, 123.43, 344.38\n/\n/\nColumns in Products_Booked and all categories for low cardinality columns :\nbooking_id : 1, 13, 11, 10, 2, 4, 14, 3, 15\nproduct_id : 1, 2, 5, 4, 3\nreturned_yn : 1\nreturned_late_yn : 1, 0\nbooked_count : 1, 2, 5, 4, 6, 3, 9\n/\n \nCREATE TABLE \"Parts\" (\n\tpart_id INTEGER, \n\tpart_name VARCHAR(255), \n\tchargeable_yn VARCHAR(1), \n\tchargeable_amount VARCHAR(20), \n\tother_part_details VARCHAR(255), \n\tPRIMARY KEY (part_id)\n)\n/\nColumns in Parts and all categories for low cardinality columns :\npart_id : 1, 2, 3\npart_name : top, middle, package\nchargeable_yn : 1, 0\nchargeable_amount : 4, 9\nother_part_details : None\n/\n \nCREATE TABLE \"Faculty\" (\n\t\"FacID\" INTEGER, \n\t\"Lname\" VARCHAR(15), \n\t\"Fname\" VARCHAR(15), \n\t\"Rank\" VARCHAR(15), \n\t\"Sex\" VARCHAR(1), \n\t\"Phone\" INTEGER, \n\t\"Room\" VARCHAR(5), \n\t\"Building\" VARCHAR(13), \n\tPRIMARY KEY (\"FacID\")\n)\n/\nColumns in Faculty and 3 examples in each column for high cardinality columns :\nFacID : 6112, 9199, 7134\nLname : Glaser, Han, James\nFname : Rao, Brenda, James\nPhone : 2105, 3593, 1035\nRoom : 288, 218, 219\n/\n/\nColumns in Faculty and all categories for low cardinality columns :\nRank : AssocProf, AsstProf, Professor, Instructor\nSex : F, M\nBuilding : Krieger, NEB, Barton\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 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 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 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 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" }, { "role": "user", "content": "Show the student id of the oldest student." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: StuID, age.\nThe SQL query I'll be generating is:\nSELECT StuID FROM Student WHERE age = (SELECT max(age) FROM Student)" } ]
[ { "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 degrees (\n\t\"Year\" INTEGER, \n\t\"Campus\" INTEGER, \n\t\"Degrees\" INTEGER, \n\tPRIMARY KEY (\"Year\", \"Campus\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in degrees and 3 examples in each column for high cardinality columns :\nYear : 2004, 1992, 1993\nCampus : 1, 13, 11\nDegrees : 2719, 4232, 2735\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 \"match\" (\n\t\"Match_ID\" INTEGER, \n\t\"Date\" TEXT, \n\t\"Venue\" TEXT, \n\t\"Score\" TEXT, \n\t\"Result\" TEXT, \n\t\"Competition\" TEXT, \n\tPRIMARY KEY (\"Match_ID\")\n)\n/\nColumns in match and all categories for low cardinality columns :\nMatch_ID : 1, 2, 5, 4, 6, 3\nDate : 23 July 1992, 18 February 1992, 19 July 1992, 23 July 2000, 4 April 1993\nVenue : Estadio Rigoberto López , Managua , Nicaragua, Estadio Cuscatlán , San Salvador , El Salvador\nScore : 3-0, 2–1, 1-0, 1–0\nResult : 5-1, 7–1, 5-0, 2–1, 2-0\nCompetition : 1994 FIFA World Cup qualification, Friendly match, 2002 FIFA World Cup qualification\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 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 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 \"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 \"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 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 \"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 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_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 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 \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 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 \"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 \"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 player (\n\t\"Player_ID\" INTEGER, \n\tname TEXT, \n\t\"Position\" TEXT, \n\t\"Club_ID\" INTEGER, \n\t\"Apps\" REAL, \n\t\"Tries\" REAL, \n\t\"Goals\" TEXT, \n\t\"Points\" REAL, \n\tPRIMARY KEY (\"Player_ID\"), \n\tFOREIGN KEY(\"Club_ID\") REFERENCES club (\"Club_ID\")\n)\n/\nColumns in player and 3 examples in each column for high cardinality columns :\nPlayer_ID : 1, 13, 11\nname : Michael Platt, Tame Tupou, Terry Newton\nApps : 30.0, 29.0, 24.0\n/\n/\nColumns in player and all categories for low cardinality columns :\nPosition : Scrum Half, Right Centre, Prop, Loose Forward, Hooker, Right Wing, Stand Off, Second Row, Left Wing, Full Back\nClub_ID : 1, 2, 5, 4, 3\nTries : 3.0, 8.0, 1.0, 6.0, 9.0, 2.0, 4.0, 5.0\nGoals : 50/60, 90/106, 0/1, 0\nPoints : 36.0, 8.0, 16.0, 12.0, 24.0, 188.0, 32.0, 110.0, 4.0, 20.0\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" }, { "role": "user", "content": "What student id corresponds to the oldest student?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: StuID, age.\nThe SQL query I'll be generating is:\nSELECT StuID FROM Student WHERE age = (SELECT max(age) FROM Student)" } ]
[ { "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 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 \"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 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 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 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 \"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 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 \"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 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 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 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 \"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 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 \"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 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 \"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_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" }, { "role": "user", "content": "Show all majors and corresponding number of students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: major.\nThe SQL query I'll be generating is:\nSELECT major , count(*) FROM Student GROUP BY major" } ]
[ { "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 \"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 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 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 \"Customer_Events\" (\n\t\"Customer_Event_ID\" INTEGER NOT NULL, \n\tcustomer_id INTEGER, \n\tdate_moved_in DATETIME, \n\tproperty_id INTEGER, \n\tresident_id INTEGER, \n\tthing_id INTEGER NOT NULL, \n\tPRIMARY KEY (\"Customer_Event_ID\"), \n\tFOREIGN KEY(thing_id) REFERENCES \"Things\" (thing_id), \n\tFOREIGN KEY(customer_id) REFERENCES \"Customers\" (customer_id), \n\tFOREIGN KEY(resident_id, property_id, date_moved_in) REFERENCES \"Residents\" (resident_id, property_id, date_moved_in)\n)\n/\nColumns in Customer_Events and 3 examples in each column for high cardinality columns :\nCustomer_Event_ID : 428, 216, 226\nresident_id : 87, 38, 37\n/\n/\nColumns in Customer_Events and all categories for low cardinality columns :\ncustomer_id : 79, 91, 16, 5, 4, 63, 19, 31\ndate_moved_in : 2016-09-27 12:00:00, 2015-03-27 12:00:00\nproperty_id : 954, 120, 108, 605, 629, 748, 669, 445, 879, 107\nthing_id : 1, 46, 10, 80, 2, 92, 14, 85, 68\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 \"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 \"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 film_text (\n\tfilm_id SMALLINT NOT NULL, \n\ttitle VARCHAR(255) NOT NULL, \n\tdescription TEXT, \n\tPRIMARY KEY (film_id)\n)\n/\nColumns in film_text and all categories for low cardinality columns :\nfilm_id : \ntitle : \ndescription : \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 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 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 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 \"Products\" (\n\tproduct_id INTEGER, \n\tcolor_code VARCHAR(15) NOT NULL, \n\tproduct_category_code VARCHAR(15) NOT NULL, \n\tproduct_name VARCHAR(80), \n\ttypical_buying_price VARCHAR(20), \n\ttypical_selling_price VARCHAR(20), \n\tproduct_description VARCHAR(255), \n\tother_product_details VARCHAR(255), \n\tPRIMARY KEY (product_id), \n\tFOREIGN KEY(color_code) REFERENCES \"Ref_Colors\" (color_code), \n\tFOREIGN KEY(product_category_code) REFERENCES \"Ref_Product_Categories\" (product_category_code)\n)\n/\nColumns in Products and 3 examples in each column for high cardinality columns :\nproduct_id : 1, 13, 11\nproduct_name : peper, cumin, chili\ntypical_buying_price : , 5.578, 503.8431967\ntypical_selling_price : , 149, 10377614.847385\nproduct_description : ut, et, vel\n/\n/\nColumns in Products and all categories for low cardinality columns :\ncolor_code : 1, 2, 5, 7, 4, 9\nproduct_category_code : Spices, Seeds, Herbs\nother_product_details : None\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 \"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 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 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 college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\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" }, { "role": "user", "content": "How many students are there for each major?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: major.\nThe SQL query I'll be generating is:\nSELECT major , count(*) FROM Student GROUP BY major" } ]
[ { "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 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 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 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 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 \"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 \"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 flight (\n\tid INTEGER, \n\t\"Vehicle_Flight_number\" TEXT, \n\t\"Date\" TEXT, \n\t\"Pilot\" TEXT, \n\t\"Velocity\" REAL, \n\t\"Altitude\" REAL, \n\tairport_id INTEGER, \n\tcompany_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(company_id) REFERENCES operate_company (id), \n\tFOREIGN KEY(airport_id) REFERENCES airport (id)\n)\n/\nColumns in flight and 3 examples in each column for high cardinality columns :\nid : 1, 13, 11\nVehicle_Flight_number : M2-F1 #14, M2-F1 #61, M2-F1 #0\nDate : July 16, 1965, May 19, 1964, March 28, 1966\n/\n/\nColumns in flight and all categories for low cardinality columns :\nPilot : Thompson, Peterson\nVelocity : 240.0, 135.0\nAltitude : 3650.0, 0.0\nairport_id : 1, 2, 5, 8, 4, 6, 3, 9\ncompany_id : 1, 13, 11, 2, 5, 7, 4, 6, 3, 9\n/\n \nCREATE TABLE enrollments (\n\t\"Campus\" INTEGER, \n\t\"Year\" INTEGER, \n\t\"TotalEnrollment_AY\" INTEGER, \n\t\"FTE_AY\" INTEGER, \n\tPRIMARY KEY (\"Campus\", \"Year\"), \n\tFOREIGN KEY(\"Campus\") REFERENCES \"Campuses\" (\"Id\")\n)\n/\nColumns in enrollments and 3 examples in each column for high cardinality columns :\nYear : 1979, 2004, 1937\nTotalEnrollment_AY : 495, 5734, 9547\nFTE_AY : 3877, 14324, 12876\n/\n/\nColumns in enrollments and all categories for low cardinality columns :\nCampus : 1, 2, 5, 4, 3\n/\n \nCREATE TABLE \"Appointment\" (\n\t\"AppointmentID\" INTEGER NOT NULL, \n\t\"Patient\" INTEGER NOT NULL, \n\t\"PrepNurse\" INTEGER, \n\t\"Physician\" INTEGER NOT NULL, \n\t\"Start\" DATETIME NOT NULL, \n\t\"End\" DATETIME NOT NULL, \n\t\"ExaminationRoom\" TEXT NOT NULL, \n\tPRIMARY KEY (\"AppointmentID\"), \n\tCONSTRAINT \"fk_Appointment_Patient_SSN\" FOREIGN KEY(\"Patient\") REFERENCES \"Patient\" (\"SSN\"), \n\tCONSTRAINT \"fk_Appointment_Nurse_EmployeeID\" FOREIGN KEY(\"PrepNurse\") REFERENCES \"Nurse\" (\"EmployeeID\"), \n\tCONSTRAINT \"fk_Appointment_Physician_EmployeeID\" FOREIGN KEY(\"Physician\") REFERENCES \"Physician\" (\"EmployeeID\")\n)\n/\nColumns in Appointment and all categories for low cardinality columns :\nAppointmentID : 59871321, 13216584, 46846589, 26548913, 69879231, 76983231, 36549879, 86213939, 93216548\nPatient : 100000001, 100000002, 100000004, 100000003\nPrepNurse : 102, 101, None, 103\nPhysician : 1, 2, 4, 3, 9\nStart : 2008-04-24 10:00:00, 2008-04-25 10:00:00, 2008-04-26 11:00:00, 2008-04-26 10:00:00, 2008-04-26 12:00:00, 2008-04-27 10:00:00\nEnd : 2008-04-25 11:00:00, 2008-04-26 13:00:00, 2008-04-27 11:00:00, 2008-04-21 11:00:00, 2008-04-26 11:00:00, 2008-04-24 11:00:00, 2008-04-26 12:00:00\nExaminationRoom : A, C, B\n/\n \nCREATE TABLE certificate (\n\teid NUMERIC(9, 0), \n\taid NUMERIC(9, 0), \n\tPRIMARY KEY (eid, aid), \n\tFOREIGN KEY(aid) REFERENCES aircraft (aid), \n\tFOREIGN KEY(eid) REFERENCES employee (eid)\n)\n/\nColumns in certificate and 3 examples in each column for high cardinality columns :\neid : 573284895, 90873519, 552455318\naid : 1, 13, 11\n/\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 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 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 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 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 \"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 \"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" }, { "role": "user", "content": "Which major has most number of students?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: major.\nThe SQL query I'll be generating is:\nSELECT major FROM Student GROUP BY major 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 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 \"Documents_Mailed\" (\n\tdocument_id INTEGER NOT NULL, \n\tmailed_to_address_id INTEGER NOT NULL, \n\tmailing_date DATETIME, \n\tPRIMARY KEY (document_id, mailed_to_address_id), \n\tFOREIGN KEY(document_id) REFERENCES \"Documents\" (document_id), \n\tFOREIGN KEY(mailed_to_address_id) REFERENCES \"Addresses\" (address_id)\n)\n/\nColumns in Documents_Mailed and 3 examples in each column for high cardinality columns :\nmailing_date : 2007-01-01 22:32:11, 2007-03-20 05:22:01, 1992-11-07 15:03:41\n/\n/\nColumns in Documents_Mailed and all categories for low cardinality columns :\ndocument_id : 13, 20, 2, 7, 24, 23, 4, 12, 14, 10\nmailed_to_address_id : 2, 5, 7, 8, 4, 3, 9, 0\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 \"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 \"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 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 \"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 \"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 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 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 \"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 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 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 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 \"Invoices\" (\n\tinvoice_number INTEGER, \n\torder_id INTEGER NOT NULL, \n\tinvoice_date DATETIME, \n\tPRIMARY KEY (invoice_number), \n\tFOREIGN KEY(order_id) REFERENCES \"Orders\" (order_id)\n)\n/\nColumns in Invoices and 3 examples in each column for high cardinality columns :\ninvoice_number : 1, 13, 11\ninvoice_date : 2018-03-16 21:57:43, 2018-03-20 00:21:41, 2018-03-05 08:47:33\n/\n/\nColumns in Invoices and all categories for low cardinality columns :\norder_id : 13, 11, 5, 8, 4, 12, 3, 14, 10, 9\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 \"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 \"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_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 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 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" }, { "role": "user", "content": "What is the largest major?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: major.\nThe SQL query I'll be generating is:\nSELECT major FROM Student GROUP BY major 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 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 \"Regular_Order_Products\" (\n\tregular_order_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\tFOREIGN KEY(regular_order_id) REFERENCES \"Regular_Orders\" (regular_order_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products\" (product_id)\n)\n/\nColumns in Regular_Order_Products and 3 examples in each column for high cardinality columns :\nregular_order_id : 1, 13, 2\n/\n/\nColumns in Regular_Order_Products and all categories for low cardinality columns :\nproduct_id : 1, 2, 5, 4, 6, 3\n/\n \nCREATE TABLE \"Products_Booked\" (\n\tbooking_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\treturned_yn VARCHAR(1), \n\treturned_late_yn VARCHAR(1), \n\tbooked_count INTEGER, \n\tbooked_amount FLOAT, \n\tPRIMARY KEY (booking_id, product_id), \n\tFOREIGN KEY(product_id) REFERENCES \"Products_for_Hire\" (product_id), \n\tFOREIGN KEY(booking_id) REFERENCES \"Bookings\" (booking_id)\n)\n/\nColumns in Products_Booked and 3 examples in each column for high cardinality columns :\nbooked_amount : 398.68, 123.43, 344.38\n/\n/\nColumns in Products_Booked and all categories for low cardinality columns :\nbooking_id : 1, 13, 11, 10, 2, 4, 14, 3, 15\nproduct_id : 1, 2, 5, 4, 3\nreturned_yn : 1\nreturned_late_yn : 1, 0\nbooked_count : 1, 2, 5, 4, 6, 3, 9\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 \"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 \"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 \"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 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 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 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 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 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 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 \"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 \"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 college (\n\t\"College_ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Leader_Name\" TEXT, \n\t\"College_Location\" TEXT, \n\tPRIMARY KEY (\"College_ID\")\n)\n/\nColumns in college and all categories for low cardinality columns :\nCollege_ID : 1, 2, 5, 4, 3\nName : Toronto School, Saskatchewan School, B.C. School, Calgary School, Edmonton School\nLeader_Name : Samir Chahine, Andre Arlain, Ryan Thelwell, Roger Dunbrack, Ousame Tounkara\nCollege_Location : St. Francis Xavier, McGill, Ottawa, Western Ontario, Minnesota\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 \"Organizations\" (\n\torganization_id INTEGER, \n\tdate_formed DATETIME, \n\torganization_name VARCHAR(255), \n\tuk_vat_number VARCHAR(20), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 1, 2, 5, 4, 3\ndate_formed : 2016-08-24 23:52:48, 2016-07-28 01:45:10, 2016-10-09 07:22:53, 2017-04-06 23:59:16, 2016-10-01 12:42:01\norganization_name : Liberal Democrats, Green Party, Labour Party, Conservative, Plaid Cymru\nuk_vat_number : 2157, 1211, 7459, 7237, 4271\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 locations (\n\t\"LOCATION_ID\" DECIMAL(4, 0) DEFAULT '0' NOT NULL, \n\t\"STREET_ADDRESS\" VARCHAR(40) DEFAULT NULL, \n\t\"POSTAL_CODE\" VARCHAR(12) DEFAULT NULL, \n\t\"CITY\" VARCHAR(30) NOT NULL, \n\t\"STATE_PROVINCE\" VARCHAR(25) DEFAULT NULL, \n\t\"COUNTRY_ID\" VARCHAR(2) DEFAULT NULL, \n\tPRIMARY KEY (\"LOCATION_ID\"), \n\tFOREIGN KEY(\"COUNTRY_ID\") REFERENCES countries (\"COUNTRY_ID\")\n)\n/\nColumns in locations and 3 examples in each column for high cardinality columns :\nLOCATION_ID : 1900, 1700, 1200\nSTREET_ADDRESS : 2004 Charade Rd, Mariano Escobedo 9991, 9450 Kamiya-cho\nPOSTAL_CODE : , 1689, 98199\nCITY : Tokyo, Southlake, South San Francisco\nSTATE_PROVINCE : , New South Wales, Sao Paulo\nCOUNTRY_ID : AU, NL, JP\n/\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": "Show all ages and corresponding number of students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age.\nThe SQL query I'll be generating is:\nSELECT age , count(*) FROM Student GROUP BY age" } ]
[ { "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 \"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 \"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 \"Participates_in\" (\n\tstuid INTEGER, \n\tactid INTEGER, \n\tFOREIGN KEY(stuid) REFERENCES \"Student\" (\"StuID\"), \n\tFOREIGN KEY(actid) REFERENCES \"Activity\" (actid)\n)\n/\nColumns in Participates_in and 3 examples in each column for high cardinality columns :\nstuid : 1003, 1017, 1002\nactid : 771, 782, 770\n/\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 \"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 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 \"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 \"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 \"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 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 member_attendance (\n\t\"Member_ID\" INTEGER, \n\t\"Performance_ID\" INTEGER, \n\t\"Num_of_Pieces\" INTEGER, \n\tPRIMARY KEY (\"Member_ID\", \"Performance_ID\"), \n\tFOREIGN KEY(\"Performance_ID\") REFERENCES performance (\"Performance_ID\"), \n\tFOREIGN KEY(\"Member_ID\") REFERENCES member (\"Member_ID\")\n)\n/\nColumns in member_attendance and all categories for low cardinality columns :\nMember_ID : 1, 11, 2, 5, 7, 4, 3\nPerformance_ID : 1, 2, 4, 6, 3\nNum_of_Pieces : 1, 2, 4, 3\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 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 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 \"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 \"Party_Services\" (\n\tbooking_id INTEGER NOT NULL, \n\tcustomer_id INTEGER NOT NULL, \n\tservice_id INTEGER NOT NULL, \n\tservice_datetime DATETIME NOT NULL, \n\tbooking_made_date DATETIME, \n\tFOREIGN KEY(customer_id) REFERENCES \"Parties\" (party_id), \n\tFOREIGN KEY(service_id) REFERENCES \"Services\" (service_id)\n)\n/\nColumns in Party_Services and 3 examples in each column for high cardinality columns :\nbooking_id : 1, 13, 11\ncustomer_id : 13, 2, 5\nservice_datetime : 2018-02-28 16:29:04, 2018-03-01 18:31:32, 2018-03-09 07:27:30\nbooking_made_date : 2018-03-25 15:09:54, 2018-03-24 07:55:33, 2018-03-24 12:21:20\n/\n/\nColumns in Party_Services and all categories for low cardinality columns :\nservice_id : 1, 13, 11, 5, 7, 6, 12, 3\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 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 phone (\n\t\"Company_name\" TEXT, \n\t\"Hardware_Model_name\" TEXT, \n\t\"Accreditation_type\" TEXT, \n\t\"Accreditation_level\" TEXT, \n\t\"Date\" TEXT, \n\tchip_model TEXT, \n\tscreen_mode TEXT, \n\tPRIMARY KEY (\"Hardware_Model_name\"), \n\tFOREIGN KEY(chip_model) REFERENCES chip_model (\"Model_name\"), \n\tFOREIGN KEY(screen_mode) REFERENCES screen_mode (\"Graphics_mode\")\n)\n/\nColumns in phone and all categories for low cardinality columns :\nCompany_name : Samsung Electronics Co Ltd, Huawei Technologies Co.Ltd., HTC Corporation, Nokia Corporation, LG Electronics, Sony Mobile Communications\nHardware_Model_name : GT-I9300, U8815 Asura, Lumia 920, Lumia 820, Lumia 620, GT-I9100, Nokia 700, LG-P760, Z520e, XPERIA T, XPERIA J\nAccreditation_type : Provisional, Full\nAccreditation_level : joyn Hot Fixes, joyn\nDate : Approved (valid until 03.05.13), Approved (valid until 06.04.13), Approved (awarded 19.11.12), Approved (awarded 05.12.12), Approved (valid until 14.09.13), Approved (awarded 23.10.12), Approved (awarded 15.11.12)\nchip_model : X50 Advanced, X5, X3i, X51v, X30 low-end, X50 Standard\nscreen_mode : 1, 2, 5, 4, 6, 3\n/\n" }, { "role": "user", "content": "How old is each student and how many students are each age?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age.\nThe SQL query I'll be generating is:\nSELECT age , count(*) FROM Student GROUP BY age" } ]
[ { "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 \"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 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 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 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 event (\n\t\"ID\" INTEGER, \n\t\"Name\" TEXT, \n\t\"Stadium_ID\" INTEGER, \n\t\"Year\" TEXT, \n\tPRIMARY KEY (\"ID\"), \n\tFOREIGN KEY(\"Stadium_ID\") REFERENCES stadium (\"ID\")\n)\n/\nColumns in event and all categories for low cardinality columns :\nID : 1, 2, 5, 4, 6, 3\nName : Pacific, European FINA, FINA, World Master, IPC, World Junior\nStadium_ID : 1, 2, 8, 4, 3, 10\nYear : 2016, 2013, 2012, 2017, 2011, 2014\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 \"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 \"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 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 \"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 \"Restaurant_Type\" (\n\t\"ResTypeID\" INTEGER, \n\t\"ResTypeName\" VARCHAR(40), \n\t\"ResTypeDescription\" VARCHAR(100), \n\tPRIMARY KEY (\"ResTypeID\")\n)\n/\nColumns in Restaurant_Type and all categories for low cardinality columns :\nResTypeID : 1, 2\nResTypeName : Sandwich, Stir-fry\nResTypeDescription : Classic Chinese cooking., Simplest there is.\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 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 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 customers (\n\tid INTEGER, \n\tfirst_name VARCHAR(40) NOT NULL, \n\tlast_name VARCHAR(20) NOT NULL, \n\tcompany VARCHAR(80), \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) NOT NULL, \n\tsupport_rep_id INTEGER, \n\tPRIMARY KEY (id), \n\tFOREIGN KEY(support_rep_id) REFERENCES employees (id)\n)\n/\nColumns in customers and 3 examples in each column for high cardinality columns :\nid : 53, 56, 49\nfirst_name : Astrid, Emma, Fynn\nlast_name : Sullivan, Schneider, Mercier\ncompany : Apple Inc., Microsoft Corporation, Rogers Canada\naddress : 696 Osborne Street, 796 Dundas Street West, Grétrystraat 63\ncity : Oslo, Lisbon, Mountain View\nstate : AZ, NSW, Dublin\ncountry : Sweden, Australia, India\npostal_code : 85719, B3S 1C5, 1106\nphone : +1 (801) 531-7272, +49 030 26550280, +33 05 56 96 96 96\nfax : +1 (212) 221-4679, +55 (12) 3923-5566, +1 (650) 253-0000\nemail : mphilips12@shaw.ca, luisg@embraer.com.br, marc.dubois@hotmail.com\n/\n/\nColumns in customers and all categories for low cardinality columns :\nsupport_rep_id : 4, 5, 3\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 \"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" }, { "role": "user", "content": "Show the average age for male and female students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age, sex.\nThe SQL query I'll be generating is:\nSELECT avg(age) , sex FROM Student GROUP BY sex" } ]
[ { "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 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 \"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 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 \"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 \"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 \"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 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 \"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 film_text (\n\tfilm_id SMALLINT NOT NULL, \n\ttitle VARCHAR(255) NOT NULL, \n\tdescription TEXT, \n\tPRIMARY KEY (film_id)\n)\n/\nColumns in film_text and all categories for low cardinality columns :\nfilm_id : \ntitle : \ndescription : \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 \"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 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 \"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 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 \"Bookings\" (\n\t\"Booking_ID\" INTEGER NOT NULL, \n\t\"Customer_ID\" INTEGER NOT NULL, \n\t\"Workshop_Group_ID\" VARCHAR(100) NOT NULL, \n\t\"Status_Code\" CHAR(15) NOT NULL, \n\t\"Store_ID\" INTEGER NOT NULL, \n\t\"Order_Date\" DATETIME NOT NULL, \n\t\"Planned_Delivery_Date\" DATETIME NOT NULL, \n\t\"Actual_Delivery_Date\" DATETIME NOT NULL, \n\t\"Other_Order_Details\" VARCHAR(255), \n\tPRIMARY KEY (\"Booking_ID\"), \n\tFOREIGN KEY(\"Customer_ID\") REFERENCES \"Clients\" (\"Client_ID\"), \n\tFOREIGN KEY(\"Workshop_Group_ID\") REFERENCES \"Drama_Workshop_Groups\" (\"Workshop_Group_ID\"), \n\tUNIQUE (\"Booking_ID\")\n)\n/\nColumns in Bookings and 3 examples in each column for high cardinality columns :\nBooking_ID : 1, 13, 11\nCustomer_ID : 938, 605, 591\nOrder_Date : 1971-05-11 06:53:01, 1975-11-23 06:28:47, 1975-12-30 14:12:32\nPlanned_Delivery_Date : 2014-06-05 10:19:46, 2013-03-10 18:47:05, 1993-04-17 23:53:01\nActual_Delivery_Date : 1983-02-07 20:27:10, 1971-01-13 13:24:52, 1983-10-09 10:48:48\n/\n/\nColumns in Bookings and all categories for low cardinality columns :\nWorkshop_Group_ID : 954, 838, 405, 735, 140, 708, 176, 685, 136\nStatus_Code : stop, good\nStore_ID : 1, 2, 5, 7, 8, 4, 6, 9\nOther_Order_Details : None\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 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 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 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 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" }, { "role": "user", "content": "What are the average ages for male and female students?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: age, sex.\nThe SQL query I'll be generating is:\nSELECT avg(age) , sex FROM Student GROUP BY sex" } ]
[ { "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_Type\" (\n\t\"ResTypeID\" INTEGER, \n\t\"ResTypeName\" VARCHAR(40), \n\t\"ResTypeDescription\" VARCHAR(100), \n\tPRIMARY KEY (\"ResTypeID\")\n)\n/\nColumns in Restaurant_Type and all categories for low cardinality columns :\nResTypeID : 1, 2\nResTypeName : Sandwich, Stir-fry\nResTypeDescription : Classic Chinese cooking., Simplest there is.\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 \"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 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 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 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 entrepreneur (\n\t\"Entrepreneur_ID\" INTEGER, \n\t\"People_ID\" INTEGER, \n\t\"Company\" TEXT, \n\t\"Money_Requested\" REAL, \n\t\"Investor\" TEXT, \n\tPRIMARY KEY (\"Entrepreneur_ID\"), \n\tFOREIGN KEY(\"People_ID\") REFERENCES people (\"People_ID\")\n)\n/\nColumns in entrepreneur and all categories for low cardinality columns :\nEntrepreneur_ID : 1, 2, 5, 4, 6, 3\nPeople_ID : 1, 2, 5, 8, 6, 3\nCompany : Mycorrhizal Systems, Le Beanock, Umbrolly, IV Cam, Elizabeth Galton Ltd, Grails Ltd\nMoney_Requested : 150000.0, 110000.0, 120000.0, 75000.0, 50000.0, 54000.0\nInvestor : Duncan Bannatyne, Doug Richard, Peter Jones, Rachel Elnaugh, Simon Woodroffe\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 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 \"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 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 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 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 \"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 \"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 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 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 \"Order_Items\" (\n\torder_id INTEGER NOT NULL, \n\tproduct_id INTEGER NOT NULL, \n\torder_quantity VARCHAR(15), \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 all categories for low cardinality columns :\norder_id : 13, 11, 2, 5, 7, 8, 14, 10\nproduct_id : 1, 2, 3\norder_quantity : 1, 2, 5, 7, 8, 6, 9\n/\n" }, { "role": "user", "content": "Show all cities and corresponding number of students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code.\nThe SQL query I'll be generating is:\nSELECT city_code , count(*) FROM Student GROUP BY city_code" } ]
[ { "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 \"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 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 \"Organizations\" (\n\torganization_id INTEGER, \n\tdate_formed DATETIME, \n\torganization_name VARCHAR(255), \n\tuk_vat_number VARCHAR(20), \n\tPRIMARY KEY (organization_id)\n)\n/\nColumns in Organizations and all categories for low cardinality columns :\norganization_id : 1, 2, 5, 4, 3\ndate_formed : 2016-08-24 23:52:48, 2016-07-28 01:45:10, 2016-10-09 07:22:53, 2017-04-06 23:59:16, 2016-10-01 12:42:01\norganization_name : Liberal Democrats, Green Party, Labour Party, Conservative, Plaid Cymru\nuk_vat_number : 2157, 1211, 7459, 7237, 4271\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 airport (\n\t\"Airport_ID\" INTEGER, \n\t\"Airport_Name\" TEXT, \n\t\"Total_Passengers\" REAL, \n\t\"%_Change_2007\" TEXT, \n\t\"International_Passengers\" REAL, \n\t\"Domestic_Passengers\" REAL, \n\t\"Transit_Passengers\" REAL, \n\t\"Aircraft_Movements\" REAL, \n\t\"Freight_Metric_Tonnes\" REAL, \n\tPRIMARY KEY (\"Airport_ID\")\n)\n/\nColumns in airport and all categories for low cardinality columns :\nAirport_ID : 1, 2, 5, 7, 8, 4, 6, 3, 10, 9\nAirport_Name : Bristol, London Luton, East Midlands, Birmingham Airport, Glasgow International, London Stansted, London Heathrow, London Gatwick, Edinburgh, Manchester\nTotal_Passengers : 8178891.0, 5620673.0, 34205887.0, 9627589.0, 67054745.0, 6267114.0, 10180734.0, 21219195.0, 22360364.0, 9006702.0\n%_Change_2007 : 2.6%, 4.0%, 6.0%, 1.5%, 0.5%, 5.7%, 2.9%, 4.3%, 3.8%, 7.0%\nInternational_Passengers : 3711140.0, 8105162.0, 3943139.0, 19996947.0, 5057051.0, 4870184.0, 8853224.0, 61344438.0, 30431051.0, 18119230.0\nDomestic_Passengers : 746094.0, 5562516.0, 1171605.0, 2943719.0, 1471538.0, 4192121.0, 3730963.0, 1320678.0, 2343428.0, 5281038.0\nTransit_Passengers : 156246.0, 50889.0, 6832.0, 19989.0, 43873.0, 43631.0, 14524.0, 38458.0, 4395.0, 147791.0\nAircraft_Movements : 478693.0, 117859.0, 204610.0, 193282.0, 125550.0, 76517.0, 112227.0, 100087.0, 93038.0, 263653.0\nFreight_Metric_Tonnes : 3.0, 261507.0, 12418.0, 40518.0, 197738.0, 141781.0, 107702.0, 3546.0, 12192.0, 1397054.0\n/\n \nCREATE TABLE \"Addresses\" (\n\taddress_id INTEGER, \n\taddress_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_details : 28481 Crist Circle\nEast Burdettestad, IA 21232, 69275 Mose Drive\nWilkinsonstad, CO 79055-7622, 92594 Marvin Trafficway\nPourosfurt, IA 98649\n/\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 \"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 \"Products\" (\n\tproduct_id INTEGER, \n\tproduct_type_code VARCHAR(15), \n\tproduct_name VARCHAR(80), \n\tproduct_price DOUBLE, \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_price : 5927021.8748021, 622.79275984494, 22956668.699482\n/\n/\nColumns in Products and all categories for low cardinality columns :\nproduct_type_code : Hardware, Clothes\nproduct_name : Apple, jcrew, Sony, gucci\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 \"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 \"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 \"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 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 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" }, { "role": "user", "content": "How many students live in each city?" }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: city_code.\nThe SQL query I'll be generating is:\nSELECT city_code , count(*) FROM Student GROUP BY city_code" } ]
[ { "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 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 \"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 \"Scientists\" (\n\t\"SSN\" INTEGER, \n\t\"Name\" CHAR(30) NOT NULL, \n\tPRIMARY KEY (\"SSN\")\n)\n/\nColumns in Scientists and 3 examples in each column for high cardinality columns :\nSSN : 546523478, 332569843, 845657246\nName : Kumar Swamy, John Doe, David Smith\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 \"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 \"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 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 \"View_Unit_Status\" (\n\tapt_id INTEGER, \n\tapt_booking_id INTEGER, \n\tstatus_date DATETIME NOT NULL, \n\tavailable_yn NUMERIC, \n\tPRIMARY KEY (status_date), \n\tFOREIGN KEY(apt_id) REFERENCES \"Apartments\" (apt_id), \n\tFOREIGN KEY(apt_booking_id) REFERENCES \"Apartment_Bookings\" (apt_booking_id)\n)\n/\nColumns in View_Unit_Status and 3 examples in each column for high cardinality columns :\napt_id : 1, 13, 11\napt_booking_id : 924, 497, 575\nstatus_date : 2011-02-12 09:04:07, 2003-07-25 10:13:48, 2000-02-04 07:50:09\n/\n/\nColumns in View_Unit_Status and all categories for low cardinality columns :\navailable_yn : 0E-10, 1.0000000000\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 \"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 \"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 \"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 \"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 \"Authors\" (\n\t\"authID\" INTEGER, \n\tlname TEXT, \n\tfname TEXT, \n\tPRIMARY KEY (\"authID\")\n)\n/\nColumns in Authors and 3 examples in each column for high cardinality columns :\nauthID : 53, 56, 57\nlname : Gibbons, Turon, Ueno\nfname : Daniel W. H., Tim, Ralf\n/\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 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 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" }, { "role": "user", "content": "Show all advisors and corresponding number of students." }, { "role": "assistant", "content": "\nTo construct the query, I'll be working with the following tables: Student.\nFrom these tables, I'll be using the following columns: advisor.\nThe SQL query I'll be generating is:\nSELECT advisor , count(*) FROM Student GROUP BY advisor" } ]