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vehicle_driver
bird:test.json:191
How many drivers have not driven any cars?
SELECT count(*) FROM driver WHERE driver_id NOT IN ( SELECT driver_id FROM vehicle_driver )
[ "How", "many", "drivers", "have", "not", "driven", "any", "cars", "?" ]
[ { "id": 2, "type": "table", "value": "vehicle_driver" }, { "id": 1, "type": "column", "value": "driver_id" }, { "id": 0, "type": "table", "value": "driver" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
2,790
movie_platform
bird:train.json:62
What's the description of user 85981819's movie list with the most followers?
SELECT T1.list_description FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id AND T1.user_id = T2.user_id WHERE T1.user_id = 85981819 ORDER BY T1.list_followers DESC LIMIT 1
[ "What", "'s", "the", "description", "of", "user", "85981819", "'s", "movie", "list", "with", "the", "most", "followers", "?" ]
[ { "id": 0, "type": "column", "value": "list_description" }, { "id": 5, "type": "column", "value": "list_followers" }, { "id": 2, "type": "table", "value": "lists_users" }, { "id": 4, "type": "value", "value": "85981819" }, { "id": 3, "type": "column", "value": "user_id" }, { "id": 6, "type": "column", "value": "list_id" }, { "id": 1, "type": "table", "value": "lists" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-VALUE", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
2,791
toxicology
bird:dev.json:253
List the elements of all the triple bonds.
SELECT DISTINCT T3.element FROM bond AS T1 INNER JOIN connected AS T2 ON T1.bond_id = T2.bond_id INNER JOIN atom AS T3 ON T2.atom_id = T3.atom_id WHERE T1.bond_type = '#'
[ "List", "the", "elements", "of", "all", "the", "triple", "bonds", "." ]
[ { "id": 2, "type": "column", "value": "bond_type" }, { "id": 5, "type": "table", "value": "connected" }, { "id": 0, "type": "column", "value": "element" }, { "id": 6, "type": "column", "value": "atom_id" }, { "id": 7, "type": "column", "value": "bond_id" }, { "id": 1, "type": "table", "value": "atom" }, { "id": 4, "type": "table", "value": "bond" }, { "id": 3, "type": "value", "value": "#" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
2,792
formula_1
bird:dev.json:985
Among the drivers who participated in the French Grand Prix, who has the slowest time in the 3rd lap.
SELECT T1.driverId FROM lapTimes AS T1 INNER JOIN races AS T2 on T1.raceId = T2.raceId WHERE T2.name = 'French Grand Prix' AND T1.lap = 3 ORDER BY T1.time DESC LIMIT 1
[ "Among", "the", "drivers", "who", "participated", "in", "the", "French", "Grand", "Prix", ",", "who", "has", "the", "slowest", "time", "in", "the", "3rd", "lap", "." ]
[ { "id": 6, "type": "value", "value": "French Grand Prix" }, { "id": 0, "type": "column", "value": "driverid" }, { "id": 1, "type": "table", "value": "laptimes" }, { "id": 4, "type": "column", "value": "raceid" }, { "id": 2, "type": "table", "value": "races" }, { "id": 3, "type": "column", "value": "time" }, { "id": 5, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "lap" }, { "id": 8, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 7, 8, 9 ] }, { "entity_id": 7, "token_idxs": [ 19 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O" ]
2,793
public_review_platform
bird:train.json:4096
How many user's compliment in photo has medium in number?
SELECT COUNT(T2.user_id) FROM Compliments AS T1 INNER JOIN Users_Compliments AS T2 ON T1.compliment_id = T2.compliment_id WHERE T1.compliment_type = 'photos' AND T2.number_of_compliments = 'Medium'
[ "How", "many", "user", "'s", "compliment", "in", "photo", "has", "medium", "in", "number", "?" ]
[ { "id": 6, "type": "column", "value": "number_of_compliments" }, { "id": 1, "type": "table", "value": "users_compliments" }, { "id": 4, "type": "column", "value": "compliment_type" }, { "id": 3, "type": "column", "value": "compliment_id" }, { "id": 0, "type": "table", "value": "compliments" }, { "id": 2, "type": "column", "value": "user_id" }, { "id": 5, "type": "value", "value": "photos" }, { "id": 7, "type": "value", "value": "Medium" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 8 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O" ]
2,794
retail_world
bird:train.json:6459
Is (206) 555-1189 the home phone number for Laura Callahan?
SELECT CASE WHEN HomePhone = '(206) 555-1189' THEN 'YES' ELSE 'NO' END FROM Employees WHERE FirstName = 'Laura' AND LastName = 'Callahan'
[ "Is", "(", "206", ")", "555", "-", "1189", "the", "home", "phone", "number", "for", "Laura", "Callahan", "?" ]
[ { "id": 8, "type": "value", "value": "(206) 555-1189" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "firstname" }, { "id": 7, "type": "column", "value": "homephone" }, { "id": 4, "type": "column", "value": "lastname" }, { "id": 5, "type": "value", "value": "Callahan" }, { "id": 3, "type": "value", "value": "Laura" }, { "id": 6, "type": "value", "value": "YES" }, { "id": 1, "type": "value", "value": "NO" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 8, 9 ] }, { "entity_id": 8, "token_idxs": [ 1, 2, 3, 4, 5, 6 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "B-VALUE", "O" ]
2,795
world_development_indicators
bird:train.json:2213
How many countries are having their country's footnotes described as "unspecified"? Please provide the full names of any three of those countries.
SELECT COUNT(DISTINCT T1.CountryCode) FROM Country AS T1 INNER JOIN Footnotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T2.Description = 'Unspecified' OR T2.Description = 'Not specified' UNION SELECT T1.LongName FROM Country AS T1 INNER JOIN Footnotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T2.Description = 'Unspecified' OR T2.Description = 'Not specified' LIMIT 4
[ "How", "many", "countries", "are", "having", "their", "country", "'s", "footnotes", "described", "as", "\"", "unspecified", "\"", "?", "Please", "provide", "the", "full", "names", "of", "any", "three", "of", "those", "countries", "." ]
[ { "id": 6, "type": "value", "value": "Not specified" }, { "id": 3, "type": "column", "value": "countrycode" }, { "id": 4, "type": "column", "value": "description" }, { "id": 5, "type": "value", "value": "Unspecified" }, { "id": 1, "type": "table", "value": "footnotes" }, { "id": 2, "type": "column", "value": "longname" }, { "id": 0, "type": "table", "value": "country" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
2,796
works_cycles
bird:train.json:7303
Please list the products that are out of stock and purchased in house.
SELECT T2.Name FROM ProductVendor AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.MakeFlag = 0 AND (T1.OnOrderQty IS NULL OR T1.OnOrderQty = 0)
[ "Please", "list", "the", "products", "that", "are", "out", "of", "stock", "and", "purchased", "in", "house", "." ]
[ { "id": 1, "type": "table", "value": "productvendor" }, { "id": 6, "type": "column", "value": "onorderqty" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 4, "type": "column", "value": "makeflag" }, { "id": 2, "type": "table", "value": "product" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,797
perpetrator
spider:train_spider.json:2305
List the number of people injured by perpetrators in ascending order.
SELECT Injured FROM perpetrator ORDER BY Injured ASC
[ "List", "the", "number", "of", "people", "injured", "by", "perpetrators", "in", "ascending", "order", "." ]
[ { "id": 0, "type": "table", "value": "perpetrator" }, { "id": 1, "type": "column", "value": "injured" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O" ]
2,798
video_games
bird:train.json:3336
How many more sports games than simulation games?
SELECT COUNT(CASE WHEN T1.genre_name = 'Sports' THEN T2.id ELSE NULL END) - COUNT(CASE WHEN T1.genre_name = 'Simulation' THEN T2.id ELSE NULL END) FROM genre AS T1 INNER JOIN game AS T2 ON T1.id = T2.genre_id
[ "How", "many", "more", "sports", "games", "than", "simulation", "games", "?" ]
[ { "id": 4, "type": "column", "value": "genre_name" }, { "id": 6, "type": "value", "value": "Simulation" }, { "id": 3, "type": "column", "value": "genre_id" }, { "id": 5, "type": "value", "value": "Sports" }, { "id": 0, "type": "table", "value": "genre" }, { "id": 1, "type": "table", "value": "game" }, { "id": 2, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3 ] }, { "entity_id": 6, "token_idxs": [ 6 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-VALUE", "B-TABLE", "O", "B-VALUE", "O", "O" ]
2,799
works_cycles
bird:train.json:7087
Lists all companies by BusinessEntityID that increased their current year sales by more than 60% over last year's sales and have a bonus greater than 3,000.
SELECT BusinessEntityID FROM SalesPerson WHERE SalesYTD > SalesLastYear + SalesLastyear * 0.6 AND Bonus > 3000
[ "Lists", "all", "companies", "by", "BusinessEntityID", "that", "increased", "their", "current", "year", "sales", "by", "more", "than", "60", "%", "over", "last", "year", "'s", "sales", "and", "have", "a", "bonus", "greater", "than", "3,000", "." ]
[ { "id": 1, "type": "column", "value": "businessentityid" }, { "id": 5, "type": "column", "value": "saleslastyear" }, { "id": 0, "type": "table", "value": "salesperson" }, { "id": 2, "type": "column", "value": "salesytd" }, { "id": 3, "type": "column", "value": "bonus" }, { "id": 4, "type": "value", "value": "3000" }, { "id": 6, "type": "value", "value": "0.6" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 20 ] }, { "entity_id": 3, "token_idxs": [ 24 ] }, { "entity_id": 4, "token_idxs": [ 27 ] }, { "entity_id": 5, "token_idxs": [ 17, 18 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
2,800
allergy_1
spider:train_spider.json:527
List the first and last name of the students who do not have any food type allergy.
SELECT fname , lname FROM Student WHERE StuID NOT IN (SELECT T1.StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food")
[ "List", "the", "first", "and", "last", "name", "of", "the", "students", "who", "do", "not", "have", "any", "food", "type", "allergy", "." ]
[ { "id": 5, "type": "table", "value": "allergy_type" }, { "id": 4, "type": "table", "value": "has_allergy" }, { "id": 6, "type": "column", "value": "allergytype" }, { "id": 0, "type": "table", "value": "student" }, { "id": 8, "type": "column", "value": "allergy" }, { "id": 1, "type": "column", "value": "fname" }, { "id": 2, "type": "column", "value": "lname" }, { "id": 3, "type": "column", "value": "stuid" }, { "id": 7, "type": "column", "value": "food" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "entity_id": 8, "token_idxs": [ 16 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
2,801
superstore
bird:train.json:2348
How many orders has Aimee Bixby made?
SELECT COUNT(DISTINCT T2.`Order ID`) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T1.`Customer Name` = 'Aimee Bixby'
[ "How", "many", "orders", "has", "Aimee", "Bixby", "made", "?" ]
[ { "id": 1, "type": "table", "value": "central_superstore" }, { "id": 2, "type": "column", "value": "Customer Name" }, { "id": 3, "type": "value", "value": "Aimee Bixby" }, { "id": 5, "type": "column", "value": "Customer ID" }, { "id": 4, "type": "column", "value": "Order ID" }, { "id": 0, "type": "table", "value": "people" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4, 5 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O" ]
2,802
student_assessment
spider:train_spider.json:104
What are all details of the students who registered but did not attend any course?
SELECT * FROM student_course_registrations WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance)
[ "What", "are", "all", "details", "of", "the", "students", "who", "registered", "but", "did", "not", "attend", "any", "course", "?" ]
[ { "id": 0, "type": "table", "value": "student_course_registrations" }, { "id": 2, "type": "table", "value": "student_course_attendance" }, { "id": 1, "type": "column", "value": "student_id" } ]
[ { "entity_id": 0, "token_idxs": [ 7, 8 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O" ]
2,804
department_store
spider:train_spider.json:4767
Return the ids of all products that were ordered more than three times or supplied more than 80000.
SELECT product_id FROM Order_Items GROUP BY product_id HAVING count(*) > 3 UNION SELECT product_id FROM Product_Suppliers GROUP BY product_id HAVING sum(total_amount_purchased) > 80000
[ "Return", "the", "ids", "of", "all", "products", "that", "were", "ordered", "more", "than", "three", "times", "or", "supplied", "more", "than", "80000", "." ]
[ { "id": 5, "type": "column", "value": "total_amount_purchased" }, { "id": 2, "type": "table", "value": "product_suppliers" }, { "id": 0, "type": "table", "value": "order_items" }, { "id": 1, "type": "column", "value": "product_id" }, { "id": 4, "type": "value", "value": "80000" }, { "id": 3, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 17 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
2,805
pilot_1
bird:test.json:1177
Find the number of all pilots whose age is older than some pilot who has plane Piper Cub.
SELECT count(pilot_name) FROM pilotskills WHERE age > (SELECT min(age) FROM pilotskills WHERE plane_name = 'Piper Cub')
[ "Find", "the", "number", "of", "all", "pilots", "whose", "age", "is", "older", "than", "some", "pilot", "who", "has", "plane", "Piper", "Cub", "." ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 2, "type": "column", "value": "pilot_name" }, { "id": 3, "type": "column", "value": "plane_name" }, { "id": 4, "type": "value", "value": "Piper Cub" }, { "id": 1, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [ 16, 17 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "O" ]
2,806
decoration_competition
spider:train_spider.json:4490
Which countries have more than two members?
SELECT Country FROM member GROUP BY Country HAVING COUNT(*) > 2
[ "Which", "countries", "have", "more", "than", "two", "members", "?" ]
[ { "id": 1, "type": "column", "value": "country" }, { "id": 0, "type": "table", "value": "member" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
2,807
address
bird:train.json:5146
How many zip codes are under Barre, VT?
SELECT COUNT(T2.zip_code) FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_name = 'Barre, VT'
[ "How", "many", "zip", "codes", "are", "under", "Barre", ",", "VT", "?" ]
[ { "id": 2, "type": "column", "value": "cbsa_name" }, { "id": 3, "type": "value", "value": "Barre, VT" }, { "id": 1, "type": "table", "value": "zip_data" }, { "id": 4, "type": "column", "value": "zip_code" }, { "id": 0, "type": "table", "value": "cbsa" }, { "id": 5, "type": "column", "value": "cbsa" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 4, "token_idxs": [ 2, 3 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
2,808
cre_Doc_and_collections
bird:test.json:669
List document id of all documents.
SELECT Document_Object_ID FROM Document_Objects;
[ "List", "document", "i", "d", "of", "all", "documents", "." ]
[ { "id": 1, "type": "column", "value": "document_object_id" }, { "id": 0, "type": "table", "value": "document_objects" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 1, 2, 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O" ]
2,809
cre_Drama_Workshop_Groups
spider:train_spider.json:5158
Show all cities where at least one customer lives in but no performer lives in.
SELECT T1.City_Town FROM Addresses AS T1 JOIN Customers AS T2 ON T1.Address_ID = T2.Address_ID EXCEPT SELECT T1.City_Town FROM Addresses AS T1 JOIN Performers AS T2 ON T1.Address_ID = T2.Address_ID
[ "Show", "all", "cities", "where", "at", "least", "one", "customer", "lives", "in", "but", "no", "performer", "lives", "in", "." ]
[ { "id": 3, "type": "table", "value": "performers" }, { "id": 4, "type": "column", "value": "address_id" }, { "id": 0, "type": "column", "value": "city_town" }, { "id": 1, "type": "table", "value": "addresses" }, { "id": 2, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
2,810
cre_Drama_Workshop_Groups
spider:train_spider.json:5099
Find the phone number and email address of customer "Harold".
SELECT Customer_Phone , Customer_Email_Address FROM CUSTOMERS WHERE Customer_Name = "Harold"
[ "Find", "the", "phone", "number", "and", "email", "address", "of", "customer", "\"", "Harold", "\"", "." ]
[ { "id": 2, "type": "column", "value": "customer_email_address" }, { "id": 1, "type": "column", "value": "customer_phone" }, { "id": 3, "type": "column", "value": "customer_name" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 4, "type": "column", "value": "Harold" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3, 4, 5, 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "O", "O" ]
2,811
college_1
spider:train_spider.json:3234
How many courses does the department of Computer Information Systmes offer?
SELECT count(*) FROM department AS T1 JOIN course AS T2 ON T1.dept_code = T2.dept_code WHERE dept_name = "Computer Info. Systems"
[ "How", "many", "courses", "does", "the", "department", "of", "Computer", "Information", "Systmes", "offer", "?" ]
[ { "id": 3, "type": "column", "value": "Computer Info. Systems" }, { "id": 0, "type": "table", "value": "department" }, { "id": 2, "type": "column", "value": "dept_name" }, { "id": 4, "type": "column", "value": "dept_code" }, { "id": 1, "type": "table", "value": "course" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 7, 8, 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
2,812
human_resources
bird:train.json:8985
Among the employees with poor performance, provide the managers' full names, location city, address and its zip code.
SELECT T1.firstname, T1.lastname, T2.locationcity, T2.address, T2.zipcode FROM employee AS T1 INNER JOIN location AS T2 ON T1.locationID = T2.locationID INNER JOIN position AS T3 ON T3.positionID = T1.positionID WHERE T3.positiontitle = 'Manager' AND T1.performance = 'Poor'
[ "Among", "the", "employees", "with", "poor", "performance", ",", "provide", "the", "managers", "'", "full", "names", ",", "location", "city", ",", "address", "and", "its", "zip", "code", "." ]
[ { "id": 9, "type": "column", "value": "positiontitle" }, { "id": 2, "type": "column", "value": "locationcity" }, { "id": 11, "type": "column", "value": "performance" }, { "id": 8, "type": "column", "value": "positionid" }, { "id": 13, "type": "column", "value": "locationid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 5, "type": "table", "value": "position" }, { "id": 6, "type": "table", "value": "employee" }, { "id": 7, "type": "table", "value": "location" }, { "id": 3, "type": "column", "value": "address" }, { "id": 4, "type": "column", "value": "zipcode" }, { "id": 10, "type": "value", "value": "Manager" }, { "id": 12, "type": "value", "value": "Poor" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [ 17 ] }, { "entity_id": 4, "token_idxs": [ 20, 21 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 2 ] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 9 ] }, { "entity_id": 11, "token_idxs": [ 5 ] }, { "entity_id": 12, "token_idxs": [ 4 ] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
2,813
climbing
spider:train_spider.json:1139
How many climbers are from each country?
SELECT Country , COUNT(*) FROM climber GROUP BY Country
[ "How", "many", "climbers", "are", "from", "each", "country", "?" ]
[ { "id": 0, "type": "table", "value": "climber" }, { "id": 1, "type": "column", "value": "country" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
2,814
retails
bird:train.json:6871
What is the name of the supplier that provides the part "hot spring dodger dim light" with the lowest supply cost?
SELECT T2.s_name FROM partsupp AS T1 INNER JOIN supplier AS T2 ON T1.ps_suppkey = T2.s_suppkey INNER JOIN part AS T3 ON T1.ps_partkey = T3.p_partkey WHERE T3.p_name = 'hot spring dodger dim light' ORDER BY T1.ps_supplycost LIMIT 1
[ "What", "is", "the", "name", "of", "the", "supplier", "that", "provides", "the", "part", "\"", "hot", "spring", "dodger", "dim", "light", "\"", "with", "the", "lowest", "supply", "cost", "?" ]
[ { "id": 3, "type": "value", "value": "hot spring dodger dim light" }, { "id": 4, "type": "column", "value": "ps_supplycost" }, { "id": 7, "type": "column", "value": "ps_partkey" }, { "id": 9, "type": "column", "value": "ps_suppkey" }, { "id": 8, "type": "column", "value": "p_partkey" }, { "id": 10, "type": "column", "value": "s_suppkey" }, { "id": 5, "type": "table", "value": "partsupp" }, { "id": 6, "type": "table", "value": "supplier" }, { "id": 0, "type": "column", "value": "s_name" }, { "id": 2, "type": "column", "value": "p_name" }, { "id": 1, "type": "table", "value": "part" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
2,815
party_people
spider:train_spider.json:2074
What are the names of members who are not in charge of any events?
SELECT member_name FROM member EXCEPT SELECT T1.member_name FROM member AS T1 JOIN party_events AS T2 ON T1.member_id = T2.member_in_charge_id
[ "What", "are", "the", "names", "of", "members", "who", "are", "not", "in", "charge", "of", "any", "events", "?" ]
[ { "id": 4, "type": "column", "value": "member_in_charge_id" }, { "id": 2, "type": "table", "value": "party_events" }, { "id": 1, "type": "column", "value": "member_name" }, { "id": 3, "type": "column", "value": "member_id" }, { "id": 0, "type": "table", "value": "member" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
2,816
network_2
spider:train_spider.json:4483
What are the names of all of Alice's friends of friends?
SELECT DISTINCT T4.name FROM PersonFriend AS T1 JOIN Person AS T2 ON T1.name = T2.name JOIN PersonFriend AS T3 ON T1.friend = T3.name JOIN PersonFriend AS T4 ON T3.friend = T4.name WHERE T2.name = 'Alice' AND T4.name != 'Alice'
[ "What", "are", "the", "names", "of", "all", "of", "Alice", "'s", "friends", "of", "friends", "?" ]
[ { "id": 1, "type": "table", "value": "personfriend" }, { "id": 2, "type": "column", "value": "friend" }, { "id": 4, "type": "table", "value": "person" }, { "id": 3, "type": "value", "value": "Alice" }, { "id": 0, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-TABLE", "B-COLUMN", "O", "O", "O" ]
2,817
european_football_2
bird:dev.json:1026
Which home team had lost the fewest matches in the 2016 season?
SELECT teamDetails.team_long_name FROM Match AS matchData INNER JOIN Team AS teamDetails ON matchData.home_team_api_id = teamDetails.team_api_id WHERE matchData.season = '2015/2016' AND matchData.home_team_goal - matchData.away_team_goal < 0 GROUP BY matchData.home_team_api_id ORDER BY COUNT(*) ASC LIMIT 1
[ "Which", "home", "team", "had", "lost", "the", "fewest", "matches", "in", "the", "2016", "season", "?" ]
[ { "id": 0, "type": "column", "value": "home_team_api_id" }, { "id": 1, "type": "column", "value": "team_long_name" }, { "id": 8, "type": "column", "value": "home_team_goal" }, { "id": 9, "type": "column", "value": "away_team_goal" }, { "id": 4, "type": "column", "value": "team_api_id" }, { "id": 6, "type": "value", "value": "2015/2016" }, { "id": 5, "type": "column", "value": "season" }, { "id": 2, "type": "table", "value": "match" }, { "id": 3, "type": "table", "value": "team" }, { "id": 7, "type": "value", "value": "0" } ]
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[ "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,818
food_inspection
bird:train.json:8810
In 2016, which city has the highest number of establishments with the highest health and safety hazards?
SELECT T2.city FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE STRFTIME('%Y', T1.`date`) = '2016' AND T1.risk_category = 'High Risk' GROUP BY T2.city ORDER BY COUNT(T2.city) DESC LIMIT 1
[ "In", "2016", ",", "which", "city", "has", "the", "highest", "number", "of", "establishments", "with", "the", "highest", "health", "and", "safety", "hazards", "?" ]
[ { "id": 5, "type": "column", "value": "risk_category" }, { "id": 3, "type": "column", "value": "business_id" }, { "id": 1, "type": "table", "value": "violations" }, { "id": 2, "type": "table", "value": "businesses" }, { "id": 6, "type": "value", "value": "High Risk" }, { "id": 0, "type": "column", "value": "city" }, { "id": 4, "type": "value", "value": "2016" }, { "id": 8, "type": "column", "value": "date" }, { "id": 7, "type": "value", "value": "%Y" } ]
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[ "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,819
flight_1
spider:train_spider.json:360
What are the names of all aircrafts that can cover more distances than average?
SELECT name FROM Aircraft WHERE distance > (SELECT avg(distance) FROM Aircraft)
[ "What", "are", "the", "names", "of", "all", "aircrafts", "that", "can", "cover", "more", "distances", "than", "average", "?" ]
[ { "id": 0, "type": "table", "value": "aircraft" }, { "id": 2, "type": "column", "value": "distance" }, { "id": 1, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
2,820
hr_1
spider:train_spider.json:3481
get the details of employees who manage a department.
SELECT DISTINCT * FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id WHERE T1.employee_id = T2.manager_id
[ "get", "the", "details", "of", "employees", "who", "manage", "a", "department", "." ]
[ { "id": 4, "type": "column", "value": "department_id" }, { "id": 1, "type": "table", "value": "departments" }, { "id": 2, "type": "column", "value": "employee_id" }, { "id": 3, "type": "column", "value": "manager_id" }, { "id": 0, "type": "table", "value": "employees" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
2,821
regional_sales
bird:train.json:2683
List all the cities where Shawn Torres sells Audio products.
SELECT T FROM ( SELECT DISTINCT CASE WHEN T4.`Product Name` = 'Audio' AND T3.`Sales Team` = 'Shawn Torres' THEN T1.`City Name` ELSE NULL END AS T FROM `Store Locations` T1 INNER JOIN `Sales Orders` T2 ON T2._StoreID = T1.StoreID INNER JOIN `Sales Team` T3 ON T3.SalesTeamID = T2._SalesTeamID INNER JOIN Products T4 ON T4.ProductID = T2._ProductID ) WHERE T IS NOT NULL
[ "List", "all", "the", "cities", "where", "Shawn", "Torres", "sells", "Audio", "products", "." ]
[ { "id": 6, "type": "table", "value": "Store Locations" }, { "id": 7, "type": "table", "value": "Sales Orders" }, { "id": 9, "type": "column", "value": "_salesteamid" }, { "id": 12, "type": "column", "value": "Product Name" }, { "id": 15, "type": "value", "value": "Shawn Torres" }, { "id": 8, "type": "column", "value": "salesteamid" }, { "id": 2, "type": "table", "value": "Sales Team" }, { "id": 4, "type": "column", "value": "_productid" }, { "id": 14, "type": "column", "value": "Sales Team" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 5, "type": "column", "value": "City Name" }, { "id": 1, "type": "table", "value": "products" }, { "id": 10, "type": "column", "value": "_storeid" }, { "id": 11, "type": "column", "value": "storeid" }, { "id": 13, "type": "value", "value": "Audio" }, { "id": 0, "type": "column", "value": "t" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "O" ]
2,822
mondial_geo
bird:train.json:8306
Among the countries with a GDP of over 1000000, how many of them have mountains higher than 1000?
SELECT COUNT(DISTINCT T1.Name) FROM country AS T1 INNER JOIN geo_mountain AS T2 ON T1.Code = T2.Country INNER JOIN economy AS T3 ON T3.Country = T1.Code INNER JOIN mountain AS T4 ON T4.Name = T2.Mountain WHERE T3.GDP > 1000000 AND T4.Height > 1000
[ "Among", "the", "countries", "with", "a", "GDP", "of", "over", "1000000", ",", "how", "many", "of", "them", "have", "mountains", "higher", "than", "1000", "?" ]
[ { "id": 9, "type": "table", "value": "geo_mountain" }, { "id": 0, "type": "table", "value": "mountain" }, { "id": 3, "type": "column", "value": "mountain" }, { "id": 2, "type": "table", "value": "economy" }, { "id": 5, "type": "value", "value": "1000000" }, { "id": 8, "type": "table", "value": "country" }, { "id": 10, "type": "column", "value": "country" }, { "id": 6, "type": "column", "value": "height" }, { "id": 1, "type": "column", "value": "name" }, { "id": 7, "type": "value", "value": "1000" }, { "id": 11, "type": "column", "value": "code" }, { "id": 4, "type": "column", "value": "gdp" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "O" ]
2,823
local_govt_and_lot
spider:train_spider.json:4858
How many customers did not have any event?
SELECT count(*) FROM customers WHERE customer_id NOT IN ( SELECT customer_id FROM customer_events )
[ "How", "many", "customers", "did", "not", "have", "any", "event", "?" ]
[ { "id": 2, "type": "table", "value": "customer_events" }, { "id": 1, "type": "column", "value": "customer_id" }, { "id": 0, "type": "table", "value": "customers" } ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O" ]
2,824
entrepreneur
spider:train_spider.json:2290
Return the investor who have invested in the greatest number of entrepreneurs.
SELECT Investor FROM entrepreneur GROUP BY Investor ORDER BY COUNT(*) DESC LIMIT 1
[ "Return", "the", "investor", "who", "have", "invested", "in", "the", "greatest", "number", "of", "entrepreneurs", "." ]
[ { "id": 0, "type": "table", "value": "entrepreneur" }, { "id": 1, "type": "column", "value": "investor" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
2,825
music_platform_2
bird:train.json:7922
Name all the categories for podcast titled 'I Heart My Life Show'.
SELECT T1.category FROM categories AS T1 INNER JOIN podcasts AS T2 ON T2.podcast_id = T1.podcast_id WHERE T2.title = 'I Heart My Life Show'
[ "Name", "all", "the", "categories", "for", "podcast", "titled", "'", "I", "Heart", "My", "Life", "Show", "'", "." ]
[ { "id": 4, "type": "value", "value": "I Heart My Life Show" }, { "id": 1, "type": "table", "value": "categories" }, { "id": 5, "type": "column", "value": "podcast_id" }, { "id": 0, "type": "column", "value": "category" }, { "id": 2, "type": "table", "value": "podcasts" }, { "id": 3, "type": "column", "value": "title" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
2,826
student_loan
bird:train.json:4422
Which organization does student 313 belong to?
SELECT organ FROM enlist WHERE name = 'studenT113'
[ "Which", "organization", "does", "student", "313", "belong", "to", "?" ]
[ { "id": 3, "type": "value", "value": "studenT113" }, { "id": 0, "type": "table", "value": "enlist" }, { "id": 1, "type": "column", "value": "organ" }, { "id": 2, "type": "column", "value": "name" } ]
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[ "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O", "O" ]
2,827
toxicology
bird:dev.json:230
What are the elements of the toxicology and label of molecule TR060?
SELECT DISTINCT T1.element, T2.label FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T2.molecule_id = 'TR060'
[ "What", "are", "the", "elements", "of", "the", "toxicology", "and", "label", "of", "molecule", "TR060", "?" ]
[ { "id": 4, "type": "column", "value": "molecule_id" }, { "id": 3, "type": "table", "value": "molecule" }, { "id": 0, "type": "column", "value": "element" }, { "id": 1, "type": "column", "value": "label" }, { "id": 5, "type": "value", "value": "TR060" }, { "id": 2, "type": "table", "value": "atom" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-VALUE", "O" ]
2,828
regional_sales
bird:train.json:2679
What are the top 10 products with the highest net profit?
SELECT T2.`Product Name` FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID GROUP BY T1._ProductID ORDER BY SUM(REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '')) DESC LIMIT 10
[ "What", "are", "the", "top", "10", "products", "with", "the", "highest", "net", "profit", "?" ]
[ { "id": 1, "type": "column", "value": "Product Name" }, { "id": 2, "type": "table", "value": "Sales Orders" }, { "id": 0, "type": "column", "value": "_productid" }, { "id": 5, "type": "column", "value": "Unit Price" }, { "id": 4, "type": "column", "value": "productid" }, { "id": 7, "type": "column", "value": "Unit Cost" }, { "id": 3, "type": "table", "value": "products" }, { "id": 6, "type": "value", "value": "," } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
2,829
game_1
spider:train_spider.json:5980
What type of game is Call of Destiny?
SELECT gtype FROM Video_games WHERE gname = "Call of Destiny"
[ "What", "type", "of", "game", "is", "Call", "of", "Destiny", "?" ]
[ { "id": 3, "type": "column", "value": "Call of Destiny" }, { "id": 0, "type": "table", "value": "video_games" }, { "id": 1, "type": "column", "value": "gtype" }, { "id": 2, "type": "column", "value": "gname" } ]
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[ "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
2,830
voter_2
spider:train_spider.json:5477
What are the distinct ages of students who have secretary votes in the fall election cycle?
SELECT DISTINCT T1.Age FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Secretary_Vote WHERE T2.Election_Cycle = "Fall"
[ "What", "are", "the", "distinct", "ages", "of", "students", "who", "have", "secretary", "votes", "in", "the", "fall", "election", "cycle", "?" ]
[ { "id": 3, "type": "column", "value": "election_cycle" }, { "id": 6, "type": "column", "value": "secretary_vote" }, { "id": 2, "type": "table", "value": "voting_record" }, { "id": 1, "type": "table", "value": "student" }, { "id": 5, "type": "column", "value": "stuid" }, { "id": 4, "type": "column", "value": "Fall" }, { "id": 0, "type": "column", "value": "age" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O" ]
2,831
vehicle_driver
bird:test.json:162
Return the top speed and power of the vehicle that was built in the year 1996.
SELECT top_speed , power FROM vehicle WHERE build_year = 1996
[ "Return", "the", "top", "speed", "and", "power", "of", "the", "vehicle", "that", "was", "built", "in", "the", "year", "1996", "." ]
[ { "id": 3, "type": "column", "value": "build_year" }, { "id": 1, "type": "column", "value": "top_speed" }, { "id": 0, "type": "table", "value": "vehicle" }, { "id": 2, "type": "column", "value": "power" }, { "id": 4, "type": "value", "value": "1996" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
2,832
planet_1
bird:test.json:1876
What are the package contents of all those sent by John Zoidfarb?
SELECT T1.Contents FROM PACKAGE AS T1 JOIN Client AS T2 ON T1.Sender = T2.AccountNumber WHERE T2.Name = "John Zoidfarb";
[ "What", "are", "the", "package", "contents", "of", "all", "those", "sent", "by", "John", "Zoidfarb", "?" ]
[ { "id": 4, "type": "column", "value": "John Zoidfarb" }, { "id": 6, "type": "column", "value": "accountnumber" }, { "id": 0, "type": "column", "value": "contents" }, { "id": 1, "type": "table", "value": "package" }, { "id": 2, "type": "table", "value": "client" }, { "id": 5, "type": "column", "value": "sender" }, { "id": 3, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
2,833
synthea
bird:train.json:1521
How many white patients whose birth year is 1935 have a stroke?
SELECT COUNT(DISTINCT T1.patient) FROM patients AS T1 INNER JOIN conditions AS T2 ON T1.patient = T2.patient WHERE strftime('%Y', T1.birthdate) = '1935' AND T1.race = 'white' AND T2.DESCRIPTION = 'Stroke'
[ "How", "many", "white", "patients", "whose", "birth", "year", "is", "1935", "have", "a", "stroke", "?" ]
[ { "id": 6, "type": "column", "value": "description" }, { "id": 1, "type": "table", "value": "conditions" }, { "id": 9, "type": "column", "value": "birthdate" }, { "id": 0, "type": "table", "value": "patients" }, { "id": 2, "type": "column", "value": "patient" }, { "id": 7, "type": "value", "value": "Stroke" }, { "id": 5, "type": "value", "value": "white" }, { "id": 3, "type": "value", "value": "1935" }, { "id": 4, "type": "column", "value": "race" }, { "id": 8, "type": "value", "value": "%Y" } ]
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[ "O", "O", "B-VALUE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "B-VALUE", "O" ]
2,834
hockey
bird:train.json:7691
For the coach who co-coached with Dave Lewis in 1998, where was his birth place?
SELECT T1.birthCountry FROM Master AS T1 INNER JOIN Coaches AS T2 ON T1.coachID = T2.coachID WHERE T2.year = 1998 AND T2.notes = 'co-coach with Dave Lewis'
[ "For", "the", "coach", "who", "co", "-", "coached", "with", "Dave", "Lewis", "in", "1998", ",", "where", "was", "his", "birth", "place", "?" ]
[ { "id": 7, "type": "value", "value": "co-coach with Dave Lewis" }, { "id": 0, "type": "column", "value": "birthcountry" }, { "id": 2, "type": "table", "value": "coaches" }, { "id": 3, "type": "column", "value": "coachid" }, { "id": 1, "type": "table", "value": "master" }, { "id": 6, "type": "column", "value": "notes" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "1998" } ]
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[ "O", "O", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
2,835
world
bird:train.json:7900
What are the official languages used in Greece?
SELECT T1.Language FROM CountryLanguage AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T1.IsOfficial = 'T' AND T2.name = 'Greece'
[ "What", "are", "the", "official", "languages", "used", "in", "Greece", "?" ]
[ { "id": 1, "type": "table", "value": "countrylanguage" }, { "id": 3, "type": "column", "value": "countrycode" }, { "id": 5, "type": "column", "value": "isofficial" }, { "id": 0, "type": "column", "value": "language" }, { "id": 2, "type": "table", "value": "country" }, { "id": 8, "type": "value", "value": "Greece" }, { "id": 4, "type": "column", "value": "code" }, { "id": 7, "type": "column", "value": "name" }, { "id": 6, "type": "value", "value": "T" } ]
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[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
2,836
olympics
bird:train.json:5030
Who is the youngest competitor that participated in 2014 Winter?
SELECT T3.full_name FROM games AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.games_id INNER JOIN person AS T3 ON T2.person_id = T3.id WHERE T1.games_name = '2014 Winter' ORDER BY T2.age LIMIT 1
[ "Who", "is", "the", "youngest", "competitor", "that", "participated", "in", "2014", "Winter", "?" ]
[ { "id": 6, "type": "table", "value": "games_competitor" }, { "id": 3, "type": "value", "value": "2014 Winter" }, { "id": 2, "type": "column", "value": "games_name" }, { "id": 0, "type": "column", "value": "full_name" }, { "id": 7, "type": "column", "value": "person_id" }, { "id": 9, "type": "column", "value": "games_id" }, { "id": 1, "type": "table", "value": "person" }, { "id": 5, "type": "table", "value": "games" }, { "id": 4, "type": "column", "value": "age" }, { "id": 8, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
2,837
products_for_hire
spider:train_spider.json:1970
What is the average amount due for all the payments?
SELECT avg(amount_due) FROM payments
[ "What", "is", "the", "average", "amount", "due", "for", "all", "the", "payments", "?" ]
[ { "id": 1, "type": "column", "value": "amount_due" }, { "id": 0, "type": "table", "value": "payments" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
2,838
products_gen_characteristics
spider:train_spider.json:5533
Count the number of products in the category 'Seeds'.
SELECT count(*) FROM products WHERE product_category_code = "Seeds"
[ "Count", "the", "number", "of", "products", "in", "the", "category", "'", "Seeds", "'", "." ]
[ { "id": 1, "type": "column", "value": "product_category_code" }, { "id": 0, "type": "table", "value": "products" }, { "id": 2, "type": "column", "value": "Seeds" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 5, 6, 7 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O" ]
2,839
student_club
bird:dev.json:1399
Did Maya Mclean attend the 'Women's Soccer' event?
SELECT CASE WHEN T3.event_name = 'Women''s Soccer' THEN 'YES' END AS result FROM member AS T1 INNER JOIN attendance AS T2 ON T1.member_id = T2.link_to_member INNER JOIN event AS T3 ON T2.link_to_event = T3.event_id WHERE T1.first_name = 'Maya' AND T1.last_name = 'Mclean'
[ "Did", "Maya", "Mclean", "attend", "the", "'", "Women", "'s", "Soccer", "'", "event", "?" ]
[ { "id": 11, "type": "column", "value": "link_to_member" }, { "id": 13, "type": "value", "value": "Women's Soccer" }, { "id": 3, "type": "column", "value": "link_to_event" }, { "id": 2, "type": "table", "value": "attendance" }, { "id": 5, "type": "column", "value": "first_name" }, { "id": 12, "type": "column", "value": "event_name" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 10, "type": "column", "value": "member_id" }, { "id": 4, "type": "column", "value": "event_id" }, { "id": 1, "type": "table", "value": "member" }, { "id": 8, "type": "value", "value": "Mclean" }, { "id": 0, "type": "table", "value": "event" }, { "id": 6, "type": "value", "value": "Maya" }, { "id": 9, "type": "value", "value": "YES" } ]
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[ "O", "B-VALUE", "B-VALUE", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
2,840
app_store
bird:train.json:2527
Which apps have not been updated since year 2015 and what kind of sentiment users hold on it?
SELECT DISTINCT App, Sentiment FROM user_reviews WHERE App IN ( SELECT App FROM playstore WHERE CAST(SUBSTR('Last Updated', -4, 4) AS INTEGER) < 2015 )
[ "Which", "apps", "have", "not", "been", "updated", "since", "year", "2015", "and", "what", "kind", "of", "sentiment", "users", "hold", "on", "it", "?" ]
[ { "id": 0, "type": "table", "value": "user_reviews" }, { "id": 5, "type": "value", "value": "Last Updated" }, { "id": 2, "type": "column", "value": "sentiment" }, { "id": 3, "type": "table", "value": "playstore" }, { "id": 4, "type": "value", "value": "2015" }, { "id": 1, "type": "column", "value": "app" }, { "id": 6, "type": "value", "value": "-4" }, { "id": 7, "type": "value", "value": "4" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O" ]
2,841
sales_in_weather
bird:train.json:8178
How many stores are in weather station 12?
SELECT SUM(store_nbr) FROM relation WHERE station_nbr = 12
[ "How", "many", "stores", "are", "in", "weather", "station", "12", "?" ]
[ { "id": 1, "type": "column", "value": "station_nbr" }, { "id": 3, "type": "column", "value": "store_nbr" }, { "id": 0, "type": "table", "value": "relation" }, { "id": 2, "type": "value", "value": "12" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-VALUE", "O" ]
2,842
authors
bird:train.json:3591
Please list the titles of any two papers that Jundu has written.
SELECT T1.Title FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T2.Name LIKE 'Jun du%' LIMIT 2
[ "Please", "list", "the", "titles", "of", "any", "two", "papers", "that", "Jundu", "has", "written", "." ]
[ { "id": 2, "type": "table", "value": "paperauthor" }, { "id": 4, "type": "value", "value": "Jun du%" }, { "id": 6, "type": "column", "value": "paperid" }, { "id": 0, "type": "column", "value": "title" }, { "id": 1, "type": "table", "value": "paper" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-TABLE", "B-VALUE", "O", "O", "O" ]
2,843
university
bird:train.json:8030
What is the university ID with the most students in 2011?
SELECT university_id FROM university_year WHERE year = 2011 ORDER BY num_students DESC LIMIT 1
[ "What", "is", "the", "university", "ID", "with", "the", "most", "students", "in", "2011", "?" ]
[ { "id": 0, "type": "table", "value": "university_year" }, { "id": 1, "type": "column", "value": "university_id" }, { "id": 4, "type": "column", "value": "num_students" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "2011" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
2,844
music_1
spider:train_spider.json:3548
How many Bangladeshi artists are listed?
SELECT count(*) FROM artist WHERE country = "Bangladesh"
[ "How", "many", "Bangladeshi", "artists", "are", "listed", "?" ]
[ { "id": 2, "type": "column", "value": "Bangladesh" }, { "id": 1, "type": "column", "value": "country" }, { "id": 0, "type": "table", "value": "artist" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O" ]
2,845
public_review_platform
bird:train.json:3905
Which business in fashion category has the most review?
SELECT T3.business_id FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id INNER JOIN Reviews AS T4 ON T3.business_id = T4.business_id WHERE T1.category_name LIKE 'Fashion' AND T1.category_id = 7 GROUP BY T3.business_id ORDER BY COUNT(T4.user_id) DESC LIMIT 1
[ "Which", "business", "in", "fashion", "category", "has", "the", "most", "review", "?" ]
[ { "id": 9, "type": "table", "value": "business_categories" }, { "id": 3, "type": "column", "value": "category_name" }, { "id": 0, "type": "column", "value": "business_id" }, { "id": 5, "type": "column", "value": "category_id" }, { "id": 8, "type": "table", "value": "categories" }, { "id": 2, "type": "table", "value": "business" }, { "id": 1, "type": "table", "value": "reviews" }, { "id": 4, "type": "value", "value": "Fashion" }, { "id": 7, "type": "column", "value": "user_id" }, { "id": 6, "type": "value", "value": "7" } ]
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[ "O", "B-TABLE", "B-TABLE", "B-VALUE", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
2,846
formula_1
spider:train_spider.json:2157
Find the names of all races held in 2017.
SELECT name FROM races WHERE YEAR = 2017
[ "Find", "the", "names", "of", "all", "races", "held", "in", "2017", "." ]
[ { "id": 0, "type": "table", "value": "races" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "2017" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
2,847
cre_Drama_Workshop_Groups
spider:train_spider.json:5112
List all product names in ascending order of price.
SELECT Product_Name FROM Products ORDER BY Product_Price ASC
[ "List", "all", "product", "names", "in", "ascending", "order", "of", "price", "." ]
[ { "id": 2, "type": "column", "value": "product_price" }, { "id": 1, "type": "column", "value": "product_name" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
2,848
restaurant
bird:train.json:1675
List all cities in the Northern California Region.
SELECT city FROM geographic WHERE region = 'northern california'
[ "List", "all", "cities", "in", "the", "Northern", "California", "Region", "." ]
[ { "id": 3, "type": "value", "value": "northern california" }, { "id": 0, "type": "table", "value": "geographic" }, { "id": 2, "type": "column", "value": "region" }, { "id": 1, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 5, 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O" ]
2,849
medicine_enzyme_interaction
spider:train_spider.json:973
Which enzyme names have the substring "ALA"?
SELECT name FROM enzyme WHERE name LIKE "%ALA%"
[ "Which", "enzyme", "names", "have", "the", "substring", "\"", "ALA", "\"", "?" ]
[ { "id": 0, "type": "table", "value": "enzyme" }, { "id": 2, "type": "column", "value": "%ALA%" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
2,850
shop_membership
spider:train_spider.json:5420
Show all member names and registered branch names sorted by register year.
SELECT T3.name , T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id ORDER BY T1.register_year
[ "Show", "all", "member", "names", "and", "registered", "branch", "names", "sorted", "by", "register", "year", "." ]
[ { "id": 3, "type": "table", "value": "membership_register_branch" }, { "id": 2, "type": "column", "value": "register_year" }, { "id": 5, "type": "column", "value": "member_id" }, { "id": 6, "type": "column", "value": "branch_id" }, { "id": 1, "type": "table", "value": "member" }, { "id": 4, "type": "table", "value": "branch" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 10, 11 ] }, { "entity_id": 3, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-TABLE", "I-TABLE", "I-TABLE", "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
2,852
architecture
spider:train_spider.json:6955
What are the ids, names and genders of the architects who built two bridges or one mill?
SELECT T1.id , T1.name , T1.gender FROM architect AS T1 JOIN bridge AS T2 ON T1.id = T2.architect_id GROUP BY T1.id HAVING count(*) = 2 UNION SELECT T1.id , T1.name , T1.gender FROM architect AS T1 JOIN mill AS T2 ON T1.id = T2.architect_id GROUP BY T1.id HAVING count(*) = 1
[ "What", "are", "the", "ids", ",", "names", "and", "genders", "of", "the", "architects", "who", "built", "two", "bridges", "or", "one", "mill", "?" ]
[ { "id": 8, "type": "column", "value": "architect_id" }, { "id": 3, "type": "table", "value": "architect" }, { "id": 2, "type": "column", "value": "gender" }, { "id": 4, "type": "table", "value": "bridge" }, { "id": 1, "type": "column", "value": "name" }, { "id": 6, "type": "table", "value": "mill" }, { "id": 0, "type": "column", "value": "id" }, { "id": 5, "type": "value", "value": "2" }, { "id": 7, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 14 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 17 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
2,853
music_tracker
bird:train.json:2056
What are the tags of the release "sugarhill gang"?
SELECT T2.tag FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T1.groupName = 'sugarhill gang'
[ "What", "are", "the", "tags", "of", "the", "release", "\"", "sugarhill", "gang", "\"", "?" ]
[ { "id": 4, "type": "value", "value": "sugarhill gang" }, { "id": 3, "type": "column", "value": "groupname" }, { "id": 1, "type": "table", "value": "torrents" }, { "id": 2, "type": "table", "value": "tags" }, { "id": 0, "type": "column", "value": "tag" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 8, 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O" ]
2,854
store_product
spider:train_spider.json:4917
What are the names of all the stores located in Khanewal District?
SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t3.district_name = "Khanewal District"
[ "What", "are", "the", "names", "of", "all", "the", "stores", "located", "in", "Khanewal", "District", "?" ]
[ { "id": 3, "type": "column", "value": "Khanewal District" }, { "id": 5, "type": "table", "value": "store_district" }, { "id": 2, "type": "column", "value": "district_name" }, { "id": 6, "type": "column", "value": "district_id" }, { "id": 0, "type": "column", "value": "store_name" }, { "id": 1, "type": "table", "value": "district" }, { "id": 7, "type": "column", "value": "store_id" }, { "id": 4, "type": "table", "value": "store" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-TABLE", "O" ]
2,855
cre_Doc_Workflow
bird:test.json:2046
How many documents have a process?
SELECT count(DISTINCT document_id) FROM Documents_processes
[ "How", "many", "documents", "have", "a", "process", "?" ]
[ { "id": 0, "type": "table", "value": "documents_processes" }, { "id": 1, "type": "column", "value": "document_id" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "I-TABLE", "O" ]
2,856
movielens
bird:train.json:2304
Please list the actor IDs whose movies have the newest published date.
SELECT T1.actorid FROM movies2actors AS T1 INNER JOIN movies AS T2 ON T1.movieid = T2.movieid WHERE T2.year = 4
[ "Please", "list", "the", "actor", "IDs", "whose", "movies", "have", "the", "newest", "published", "date", "." ]
[ { "id": 1, "type": "table", "value": "movies2actors" }, { "id": 0, "type": "column", "value": "actorid" }, { "id": 5, "type": "column", "value": "movieid" }, { "id": 2, "type": "table", "value": "movies" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "4" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
2,857
network_2
spider:train_spider.json:4408
Who is the oldest person?
SELECT name FROM Person WHERE age = (SELECT max(age) FROM person)
[ "Who", "is", "the", "oldest", "person", "?" ]
[ { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O" ]
2,858
student_loan
bird:train.json:4553
How many students have never been absent in school?
SELECT COUNT(name) FROM longest_absense_from_school WHERE month = 0
[ "How", "many", "students", "have", "never", "been", "absent", "in", "school", "?" ]
[ { "id": 0, "type": "table", "value": "longest_absense_from_school" }, { "id": 1, "type": "column", "value": "month" }, { "id": 3, "type": "column", "value": "name" }, { "id": 2, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,859
college_2
spider:train_spider.json:1479
What are the ids for courses that were offered in both Fall of 2009 and Spring of 2010?
SELECT course_id FROM SECTION WHERE semester = 'Fall' AND YEAR = 2009 INTERSECT SELECT course_id FROM SECTION WHERE semester = 'Spring' AND YEAR = 2010
[ "What", "are", "the", "ids", "for", "courses", "that", "were", "offered", "in", "both", "Fall", "of", "2009", "and", "Spring", "of", "2010", "?" ]
[ { "id": 1, "type": "column", "value": "course_id" }, { "id": 2, "type": "column", "value": "semester" }, { "id": 0, "type": "table", "value": "section" }, { "id": 6, "type": "value", "value": "Spring" }, { "id": 3, "type": "value", "value": "Fall" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "2009" }, { "id": 7, "type": "value", "value": "2010" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 15 ] }, { "entity_id": 7, "token_idxs": [ 17 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
2,860
card_games
bird:dev.json:447
Give the code of sets have expansion commander type?
SELECT T2.setCode FROM sets AS T1 INNER JOIN set_translations AS T2 ON T2.setCode = T1.code WHERE T1.type = 'commander'
[ "Give", "the", "code", "of", "sets", "have", "expansion", "commander", "type", "?" ]
[ { "id": 2, "type": "table", "value": "set_translations" }, { "id": 4, "type": "value", "value": "commander" }, { "id": 0, "type": "column", "value": "setcode" }, { "id": 1, "type": "table", "value": "sets" }, { "id": 3, "type": "column", "value": "type" }, { "id": 5, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": [ 2 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,861
customers_and_invoices
spider:train_spider.json:1581
How many transaction does account with name 337 have?
SELECT count(*) FROM Financial_transactions AS T1 JOIN Accounts AS T2 ON T1.account_id = T2.account_id WHERE T2.account_name = "337"
[ "How", "many", "transaction", "does", "account", "with", "name", "337", "have", "?" ]
[ { "id": 0, "type": "table", "value": "financial_transactions" }, { "id": 2, "type": "column", "value": "account_name" }, { "id": 4, "type": "column", "value": "account_id" }, { "id": 1, "type": "table", "value": "accounts" }, { "id": 3, "type": "column", "value": "337" } ]
[ { "entity_id": 0, "token_idxs": [ 1, 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "I-TABLE", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O", "O" ]
2,862
planet_1
bird:test.json:1877
What is the heaviest package sent by the clients which 'John' is part of their name? List package number and weight.
SELECT T1.PackageNumber , max(T1.Weight) FROM PACKAGE AS T1 JOIN Client AS T2 ON T1.Sender = T2.AccountNumber WHERE T2.Name LIKE "John";
[ "What", "is", "the", "heaviest", "package", "sent", "by", "the", "clients", "which", "'", "John", "'", "is", "part", "of", "their", "name", "?", "List", "package", "number", "and", "weight", "." ]
[ { "id": 0, "type": "column", "value": "packagenumber" }, { "id": 7, "type": "column", "value": "accountnumber" }, { "id": 1, "type": "table", "value": "package" }, { "id": 2, "type": "table", "value": "client" }, { "id": 5, "type": "column", "value": "weight" }, { "id": 6, "type": "column", "value": "sender" }, { "id": 3, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "John" } ]
[ { "entity_id": 0, "token_idxs": [ 20 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 17 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 23 ] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [ 21 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "O" ]
2,863
cre_Doc_Tracking_DB
spider:train_spider.json:4245
What are the ids of all the employees who have destroyed documents?
SELECT DISTINCT Destroyed_by_Employee_ID FROM Documents_to_be_destroyed
[ "What", "are", "the", "ids", "of", "all", "the", "employees", "who", "have", "destroyed", "documents", "?" ]
[ { "id": 0, "type": "table", "value": "documents_to_be_destroyed" }, { "id": 1, "type": "column", "value": "destroyed_by_employee_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,864
bakery_1
bird:test.json:1590
On what dates did the bakery sell more than 100 dollars worth of goods in total?
SELECT T3.date FROM goods AS T1 JOIN items AS T2 ON T1.id = T2.item JOIN receipts AS T3 ON T2.receipt = T3.ReceiptNumber GROUP BY T3.date HAVING sum(T1.price) > 100
[ "On", "what", "dates", "did", "the", "bakery", "sell", "more", "than", "100", "dollars", "worth", "of", "goods", "in", "total", "?" ]
[ { "id": 6, "type": "column", "value": "receiptnumber" }, { "id": 1, "type": "table", "value": "receipts" }, { "id": 5, "type": "column", "value": "receipt" }, { "id": 3, "type": "table", "value": "goods" }, { "id": 4, "type": "table", "value": "items" }, { "id": 7, "type": "column", "value": "price" }, { "id": 0, "type": "column", "value": "date" }, { "id": 9, "type": "column", "value": "item" }, { "id": 2, "type": "value", "value": "100" }, { "id": 8, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
2,865
district_spokesman
bird:test.json:1193
Find the names of spokesmen who have served some district before 2004.
SELECT t1.name FROM spokesman AS t1 JOIN spokesman_district AS t2 ON t1.Spokesman_ID = t2.Spokesman_ID WHERE t2.start_year < 2004
[ "Find", "the", "names", "of", "spokesmen", "who", "have", "served", "some", "district", "before", "2004", "." ]
[ { "id": 2, "type": "table", "value": "spokesman_district" }, { "id": 5, "type": "column", "value": "spokesman_id" }, { "id": 3, "type": "column", "value": "start_year" }, { "id": 1, "type": "table", "value": "spokesman" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "2004" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 8, 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "B-VALUE", "O" ]
2,866
beer_factory
bird:train.json:5346
Which of the root beer brand have the lowest purchase?
SELECT T2.BrandName FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID GROUP BY T2.BrandID ORDER BY COUNT(T1.BrandID) LIMIT 1
[ "Which", "of", "the", "root", "beer", "brand", "have", "the", "lowest", "purchase", "?" ]
[ { "id": 3, "type": "table", "value": "rootbeerbrand" }, { "id": 1, "type": "column", "value": "brandname" }, { "id": 2, "type": "table", "value": "rootbeer" }, { "id": 0, "type": "column", "value": "brandid" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O" ]
2,867
candidate_poll
spider:train_spider.json:2413
What are the average and minimum weights for people of each sex?
SELECT avg(weight) , min(weight) , sex FROM people GROUP BY sex
[ "What", "are", "the", "average", "and", "minimum", "weights", "for", "people", "of", "each", "sex", "?" ]
[ { "id": 0, "type": "table", "value": "people" }, { "id": 2, "type": "column", "value": "weight" }, { "id": 1, "type": "column", "value": "sex" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
2,868
restaurant_bills
bird:test.json:621
Which customers have nationality "England" or "Australia"? Give me their names.
SELECT Name FROM customer WHERE Nationality = "England" OR Nationality = "Australia"
[ "Which", "customers", "have", "nationality", "\"", "England", "\"", "or", "\"", "Australia", "\"", "?", "Give", "me", "their", "names", "." ]
[ { "id": 2, "type": "column", "value": "nationality" }, { "id": 4, "type": "column", "value": "Australia" }, { "id": 0, "type": "table", "value": "customer" }, { "id": 3, "type": "column", "value": "England" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 15 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
2,869
beer_factory
bird:train.json:5361
Please name any three root beer brands that have the highest market evaluation and acceptance.
SELECT DISTINCT T1.BrandName FROM rootbeerbrand AS T1 INNER JOIN rootbeerreview AS T2 ON T1.BrandID = T2.BrandID WHERE T2.StarRating = 5 LIMIT 3
[ "Please", "name", "any", "three", "root", "beer", "brands", "that", "have", "the", "highest", "market", "evaluation", "and", "acceptance", "." ]
[ { "id": 2, "type": "table", "value": "rootbeerreview" }, { "id": 1, "type": "table", "value": "rootbeerbrand" }, { "id": 3, "type": "column", "value": "starrating" }, { "id": 0, "type": "column", "value": "brandname" }, { "id": 5, "type": "column", "value": "brandid" }, { "id": 4, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,870
beer_factory
bird:train.json:5284
List the brands of root beer produced by Dr Pepper Snapple Group and calculate their percentage of purchases between 2014 to 2016.
SELECT T1.BrandName , CAST(SUM(CASE WHEN T2.PurchaseDate >= '2014-01-01' AND T2.PurchaseDate <= '2016-12-31' THEN 1 ELSE 0 END) AS REAL) / COUNT(T2.BrandID) AS purchase FROM rootbeerbrand AS T1 INNER JOIN rootbeer AS T2 ON T1.BrandID = T2.BrandID WHERE T1.BreweryName = 'Dr Pepper Snapple Group' GROUP BY T2.BrandID
[ "List", "the", "brands", "of", "root", "beer", "produced", "by", "Dr", "Pepper", "Snapple", "Group", "and", "calculate", "their", "percentage", "of", "purchases", "between", "2014", "to", "2016", "." ]
[ { "id": 5, "type": "value", "value": "Dr Pepper Snapple Group" }, { "id": 2, "type": "table", "value": "rootbeerbrand" }, { "id": 8, "type": "column", "value": "purchasedate" }, { "id": 4, "type": "column", "value": "breweryname" }, { "id": 9, "type": "value", "value": "2014-01-01" }, { "id": 10, "type": "value", "value": "2016-12-31" }, { "id": 1, "type": "column", "value": "brandname" }, { "id": 3, "type": "table", "value": "rootbeer" }, { "id": 0, "type": "column", "value": "brandid" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4, 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 8, 9, 10, 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 17 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
2,871
ship_mission
spider:train_spider.json:4024
List the name of ships that are not involved in any mission
SELECT Name FROM ship WHERE Ship_ID NOT IN (SELECT Ship_ID FROM mission)
[ "List", "the", "name", "of", "ships", "that", "are", "not", "involved", "in", "any", "mission" ]
[ { "id": 2, "type": "column", "value": "ship_id" }, { "id": 3, "type": "table", "value": "mission" }, { "id": 0, "type": "table", "value": "ship" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE" ]
2,872
soccer_2016
bird:train.json:1896
From which country does the most umpires are from? How many of them are from the mentioned country?
SELECT T2.Country_Id, COUNT(T1.Umpire_Id) FROM Umpire AS T1 INNER JOIN Country AS T2 ON T2.Country_Id = T1.Umpire_Country GROUP BY T2.Country_Id ORDER BY COUNT(T1.Umpire_Id) DESC LIMIT 1
[ "From", "which", "country", "does", "the", "most", "umpires", "are", "from", "?", "How", "many", "of", "them", "are", "from", "the", "mentioned", "country", "?", "\n" ]
[ { "id": 4, "type": "column", "value": "umpire_country" }, { "id": 0, "type": "column", "value": "country_id" }, { "id": 3, "type": "column", "value": "umpire_id" }, { "id": 2, "type": "table", "value": "country" }, { "id": 1, "type": "table", "value": "umpire" } ]
[ { "entity_id": 0, "token_idxs": [ 18 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
2,873
soccer_2
spider:train_spider.json:4955
How many hours do the players train on average?
SELECT avg(HS) FROM Player
[ "How", "many", "hours", "do", "the", "players", "train", "on", "average", "?" ]
[ { "id": 0, "type": "table", "value": "player" }, { "id": 1, "type": "column", "value": "hs" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
2,874
cre_Docs_and_Epenses
spider:train_spider.json:6415
Show the ids for projects with at least 2 documents.
SELECT project_id FROM Documents GROUP BY project_id HAVING count(*) >= 2
[ "Show", "the", "ids", "for", "projects", "with", "at", "least", "2", "documents", "." ]
[ { "id": 1, "type": "column", "value": "project_id" }, { "id": 0, "type": "table", "value": "documents" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
2,875
student_loan
bird:train.json:4429
How many unemployed students are enlisted in the navy organization?
SELECT COUNT(T1.name) FROM unemployed AS T1 INNER JOIN enlist AS T2 ON T1.name = T2.name WHERE T2.organ = 'navy'
[ "How", "many", "unemployed", "students", "are", "enlisted", "in", "the", "navy", "organization", "?" ]
[ { "id": 0, "type": "table", "value": "unemployed" }, { "id": 1, "type": "table", "value": "enlist" }, { "id": 2, "type": "column", "value": "organ" }, { "id": 3, "type": "value", "value": "navy" }, { "id": 4, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,876
product_catalog
spider:train_spider.json:320
Find the level name of the catalog with the lowest price (in USD).
SELECT t2.catalog_level_name FROM catalog_contents AS t1 JOIN catalog_structure AS t2 ON t1.catalog_level_number = t2.catalog_level_number ORDER BY t1.price_in_dollars LIMIT 1
[ "Find", "the", "level", "name", "of", "the", "catalog", "with", "the", "lowest", "price", "(", "in", "USD", ")", "." ]
[ { "id": 4, "type": "column", "value": "catalog_level_number" }, { "id": 0, "type": "column", "value": "catalog_level_name" }, { "id": 2, "type": "table", "value": "catalog_structure" }, { "id": 1, "type": "table", "value": "catalog_contents" }, { "id": 3, "type": "column", "value": "price_in_dollars" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O" ]
2,877
codebase_community
bird:dev.json:573
Write the contents of comments with a score of 17.
SELECT Text FROM comments WHERE Score = 17
[ "Write", "the", "contents", "of", "comments", "with", "a", "score", "of", "17", "." ]
[ { "id": 0, "type": "table", "value": "comments" }, { "id": 2, "type": "column", "value": "score" }, { "id": 1, "type": "column", "value": "text" }, { "id": 3, "type": "value", "value": "17" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
2,878
loan_1
spider:train_spider.json:3061
What are the names of the different bank branches, and what are their total loan amounts?
SELECT sum(amount) , T1.bname FROM bank AS T1 JOIN loan AS T2 ON T1.branch_id = T2.branch_id GROUP BY T1.bname
[ "What", "are", "the", "names", "of", "the", "different", "bank", "branches", ",", "and", "what", "are", "their", "total", "loan", "amounts", "?" ]
[ { "id": 4, "type": "column", "value": "branch_id" }, { "id": 3, "type": "column", "value": "amount" }, { "id": 0, "type": "column", "value": "bname" }, { "id": 1, "type": "table", "value": "bank" }, { "id": 2, "type": "table", "value": "loan" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
2,879
public_review_platform
bird:train.json:3774
Give the percentage of "Automotive" businesses among all the Yelp businesses.
SELECT CAST(SUM(CASE WHEN T2.category_name LIKE 'Automotive' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) AS "percentage" FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id
[ "Give", "the", "percentage", "of", "\"", "Automotive", "\"", "businesses", "among", "all", "the", "Yelp", "businesses", "." ]
[ { "id": 0, "type": "table", "value": "business_categories" }, { "id": 7, "type": "column", "value": "category_name" }, { "id": 2, "type": "column", "value": "category_id" }, { "id": 4, "type": "column", "value": "business_id" }, { "id": 1, "type": "table", "value": "categories" }, { "id": 8, "type": "value", "value": "Automotive" }, { "id": 3, "type": "value", "value": "100" }, { "id": 5, "type": "value", "value": "0" }, { "id": 6, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
2,880
theme_gallery
spider:train_spider.json:1651
Show all artist name, age, and country ordered by the yeared they joined.
SELECT name , age , country FROM artist ORDER BY Year_Join
[ "Show", "all", "artist", "name", ",", "age", ",", "and", "country", "ordered", "by", "the", "yeared", "they", "joined", "." ]
[ { "id": 4, "type": "column", "value": "year_join" }, { "id": 3, "type": "column", "value": "country" }, { "id": 0, "type": "table", "value": "artist" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "age" } ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
2,882
book_publishing_company
bird:train.json:216
Which job level is O'Rourke at?
SELECT job_lvl FROM employee WHERE lname = 'O''Rourke'
[ "Which", "job", "level", "is", "O'Rourke", "at", "?" ]
[ { "id": 0, "type": "table", "value": "employee" }, { "id": 3, "type": "value", "value": "O'Rourke" }, { "id": 1, "type": "column", "value": "job_lvl" }, { "id": 2, "type": "column", "value": "lname" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O" ]
2,883
superhero
bird:dev.json:826
Identify the heaviest superhero in DC Comics.
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id WHERE T2.publisher_name = 'DC Comics' ORDER BY T1.weight_kg DESC LIMIT 1
[ "Identify", "the", "heaviest", "superhero", "in", "DC", "Comics", "." ]
[ { "id": 0, "type": "column", "value": "superhero_name" }, { "id": 3, "type": "column", "value": "publisher_name" }, { "id": 6, "type": "column", "value": "publisher_id" }, { "id": 1, "type": "table", "value": "superhero" }, { "id": 2, "type": "table", "value": "publisher" }, { "id": 4, "type": "value", "value": "DC Comics" }, { "id": 5, "type": "column", "value": "weight_kg" }, { "id": 7, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
2,884
beer_factory
bird:train.json:5291
How many brands of root beers are available in cans and contain corn syrup and artificial sweeteners?
SELECT COUNT(BrandID) FROM rootbeerbrand WHERE CornSyrup = 'TRUE' AND ArtificialSweetener = 'TRUE' AND AvailableInCans = 'TRUE'
[ "How", "many", "brands", "of", "root", "beers", "are", "available", "in", "cans", "and", "contain", "corn", "syrup", "and", "artificial", "sweeteners", "?" ]
[ { "id": 4, "type": "column", "value": "artificialsweetener" }, { "id": 5, "type": "column", "value": "availableincans" }, { "id": 0, "type": "table", "value": "rootbeerbrand" }, { "id": 2, "type": "column", "value": "cornsyrup" }, { "id": 1, "type": "column", "value": "brandid" }, { "id": 3, "type": "value", "value": "TRUE" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
2,885
store_1
spider:train_spider.json:636
What are the names of all tracks that are on playlists titled Movies?
SELECT T1.name FROM tracks AS T1 JOIN playlist_tracks AS T2 ON T1.id = T2.track_id JOIN playlists AS T3 ON T3.id = T2.playlist_id WHERE T3.name = "Movies";
[ "What", "are", "the", "names", "of", "all", "tracks", "that", "are", "on", "playlists", "titled", "Movies", "?" ]
[ { "id": 4, "type": "table", "value": "playlist_tracks" }, { "id": 6, "type": "column", "value": "playlist_id" }, { "id": 1, "type": "table", "value": "playlists" }, { "id": 7, "type": "column", "value": "track_id" }, { "id": 2, "type": "column", "value": "Movies" }, { "id": 3, "type": "table", "value": "tracks" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O" ]
2,886
chinook_1
spider:train_spider.json:871
Please show the employee last names that serves no more than 20 customers.
SELECT T1.LastName FROM CUSTOMER AS T1 JOIN EMPLOYEE AS T2 ON T1.SupportRepId = T2.EmployeeId GROUP BY T1.SupportRepId HAVING COUNT(*) <= 20
[ "Please", "show", "the", "employee", "last", "names", "that", "serves", "no", "more", "than", "20", "customers", "." ]
[ { "id": 0, "type": "column", "value": "supportrepid" }, { "id": 5, "type": "column", "value": "employeeid" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 2, "type": "table", "value": "customer" }, { "id": 3, "type": "table", "value": "employee" }, { "id": 4, "type": "value", "value": "20" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
2,888
assets_maintenance
spider:train_spider.json:3130
What is the name and id of the staff who recorded the fault log but has not contacted any visiting engineers?
SELECT T1.staff_name , T1.staff_id FROM Staff AS T1 JOIN Fault_Log AS T2 ON T1.staff_id = T2.recorded_by_staff_id EXCEPT SELECT T3.staff_name , T3.staff_id FROM Staff AS T3 JOIN Engineer_Visits AS T4 ON T3.staff_id = T4.contact_staff_id
[ "What", "is", "the", "name", "and", "i", "d", "of", "the", "staff", "who", "recorded", "the", "fault", "log", "but", "has", "not", "contacted", "any", "visiting", "engineers", "?" ]
[ { "id": 5, "type": "column", "value": "recorded_by_staff_id" }, { "id": 6, "type": "column", "value": "contact_staff_id" }, { "id": 4, "type": "table", "value": "engineer_visits" }, { "id": 0, "type": "column", "value": "staff_name" }, { "id": 3, "type": "table", "value": "fault_log" }, { "id": 1, "type": "column", "value": "staff_id" }, { "id": 2, "type": "table", "value": "staff" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
2,889
formula_1
bird:dev.json:994
Which constructor scored most points from Monaco Grand Prix between 1980 and 2010? List the score, name and nationality of this team.
SELECT SUM(T1.points), T2.name, T2.nationality FROM constructorResults AS T1 INNER JOIN constructors AS T2 ON T1.constructorId = T2.constructorId INNER JOIN races AS T3 ON T3.raceid = T1.raceid WHERE T3.name = 'Monaco Grand Prix' AND T3.year BETWEEN 1980 AND 2010 GROUP BY T2.name ORDER BY SUM(T1.points) DESC LIMIT 1
[ "Which", "constructor", "scored", "most", "points", "from", "Monaco", "Grand", "Prix", "between", "1980", "and", "2010", "?", "List", "the", "score", ",", "name", "and", "nationality", "of", "this", "team", "." ]
[ { "id": 4, "type": "table", "value": "constructorresults" }, { "id": 7, "type": "value", "value": "Monaco Grand Prix" }, { "id": 11, "type": "column", "value": "constructorid" }, { "id": 5, "type": "table", "value": "constructors" }, { "id": 1, "type": "column", "value": "nationality" }, { "id": 3, "type": "column", "value": "points" }, { "id": 6, "type": "column", "value": "raceid" }, { "id": 2, "type": "table", "value": "races" }, { "id": 0, "type": "column", "value": "name" }, { "id": 8, "type": "column", "value": "year" }, { "id": 9, "type": "value", "value": "1980" }, { "id": 10, "type": "value", "value": "2010" } ]
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[ "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O" ]
2,890
simpson_episodes
bird:train.json:4221
Describe the birth country, height and person name who were not included in credit list with category of casting.
SELECT T1.birth_country, T1.height_meters, T1.name FROM Person AS T1 INNER JOIN Credit AS T2 ON T1.name = T2.person WHERE T2.category = 'Cast' AND T2.credited = 'false';
[ "Describe", "the", "birth", "country", ",", "height", "and", "person", "name", "who", "were", "not", "included", "in", "credit", "list", "with", "category", "of", "casting", "." ]
[ { "id": 0, "type": "column", "value": "birth_country" }, { "id": 1, "type": "column", "value": "height_meters" }, { "id": 6, "type": "column", "value": "category" }, { "id": 8, "type": "column", "value": "credited" }, { "id": 3, "type": "table", "value": "person" }, { "id": 4, "type": "table", "value": "credit" }, { "id": 5, "type": "column", "value": "person" }, { "id": 9, "type": "value", "value": "false" }, { "id": 2, "type": "column", "value": "name" }, { "id": 7, "type": "value", "value": "Cast" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 14 ] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [ 17 ] }, { "entity_id": 7, "token_idxs": [ 19 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
2,891
music_1
spider:train_spider.json:3568
How many songs were released for each format?
SELECT count(*) , formats FROM files GROUP BY formats
[ "How", "many", "songs", "were", "released", "for", "each", "format", "?" ]
[ { "id": 1, "type": "column", "value": "formats" }, { "id": 0, "type": "table", "value": "files" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
2,892
insurance_and_eClaims
spider:train_spider.json:1530
Which customers have the substring "Diana" in their names? Return the customer details.
SELECT customer_details FROM customers WHERE customer_details LIKE "%Diana%"
[ "Which", "customers", "have", "the", "substring", "\"", "Diana", "\"", "in", "their", "names", "?", "Return", "the", "customer", "details", "." ]
[ { "id": 1, "type": "column", "value": "customer_details" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 2, "type": "column", "value": "%Diana%" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 14, 15 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]