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cars
bird:train.json:3093
How much is the car with the highest sweep volume?
SELECT T2.price FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID ORDER BY T1.displacement / T1.cylinders DESC LIMIT 1
[ "How", "much", "is", "the", "car", "with", "the", "highest", "sweep", "volume", "?" ]
[ { "id": 4, "type": "column", "value": "displacement" }, { "id": 5, "type": "column", "value": "cylinders" }, { "id": 0, "type": "column", "value": "price" }, { "id": 2, "type": "table", "value": "price" }, { "id": 1, "type": "table", "value": "data" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,667
entrepreneur
spider:train_spider.json:2299
How many distinct companies are there?
SELECT count(DISTINCT Company) FROM entrepreneur
[ "How", "many", "distinct", "companies", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "entrepreneur" }, { "id": 1, "type": "column", "value": "company" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
14,668
loan_1
spider:train_spider.json:3036
Find the name of customers who have both saving and checking account types.
SELECT cust_name FROM customer WHERE acc_type = 'saving' INTERSECT SELECT cust_name FROM customer WHERE acc_type = 'checking'
[ "Find", "the", "name", "of", "customers", "who", "have", "both", "saving", "and", "checking", "account", "types", "." ]
[ { "id": 1, "type": "column", "value": "cust_name" }, { "id": 0, "type": "table", "value": "customer" }, { "id": 2, "type": "column", "value": "acc_type" }, { "id": 4, "type": "value", "value": "checking" }, { "id": 3, "type": "value", "value": "saving" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O" ]
14,669
customers_and_orders
bird:test.json:245
What is the average price for products with type Clothes?
SELECT avg(product_price) FROM Products WHERE product_type_code = "Clothes"
[ "What", "is", "the", "average", "price", "for", "products", "with", "type", "Clothes", "?" ]
[ { "id": 1, "type": "column", "value": "product_type_code" }, { "id": 3, "type": "column", "value": "product_price" }, { "id": 0, "type": "table", "value": "products" }, { "id": 2, "type": "column", "value": "Clothes" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
14,670
wine_1
spider:train_spider.json:6520
What is the winery at which the wine with the highest score was made?
SELECT Winery FROM WINE ORDER BY SCORE LIMIT 1
[ "What", "is", "the", "winery", "at", "which", "the", "wine", "with", "the", "highest", "score", "was", "made", "?" ]
[ { "id": 1, "type": "column", "value": "winery" }, { "id": 2, "type": "column", "value": "score" }, { "id": 0, "type": "table", "value": "wine" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
14,671
formula_1
bird:dev.json:968
What is reference name of Robert Kubica?
SELECT driverRef FROM drivers WHERE forename = 'Robert' AND surname = 'Kubica'
[ "What", "is", "reference", "name", "of", "Robert", "Kubica", "?" ]
[ { "id": 1, "type": "column", "value": "driverref" }, { "id": 2, "type": "column", "value": "forename" }, { "id": 0, "type": "table", "value": "drivers" }, { "id": 4, "type": "column", "value": "surname" }, { "id": 3, "type": "value", "value": "Robert" }, { "id": 5, "type": "value", "value": "Kubica" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-VALUE", "O" ]
14,672
professional_basketball
bird:train.json:2844
In 1975, what was the average point of all-star players coming from the USA?
SELECT AVG(T2.points) FROM players AS T1 INNER JOIN player_allstar AS T2 ON T1.playerID = T2.playerID WHERE T2.season_id = 1975
[ "In", "1975", ",", "what", "was", "the", "average", "point", "of", "all", "-", "star", "players", "coming", "from", "the", "USA", "?" ]
[ { "id": 1, "type": "table", "value": "player_allstar" }, { "id": 2, "type": "column", "value": "season_id" }, { "id": 5, "type": "column", "value": "playerid" }, { "id": 0, "type": "table", "value": "players" }, { "id": 4, "type": "column", "value": "points" }, { "id": 3, "type": "value", "value": "1975" } ]
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[ "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
14,673
bike_share_1
bird:train.json:9078
Convert all temperature recorded at San Francisco city during August 2013 into degree Celsius.
SELECT (max_temperature_f - 32) / 1.8000 , (mean_temperature_f - 32) / 1.8000 , (min_temperature_f - 32) / 1.8000 FROM weather WHERE SUBSTR(CAST(date AS TEXT), 1, INSTR(date, '/') - 1) = '8' AND SUBSTR(CAST(date AS TEXT), -4) = '2013' AND zip_code = 94107
[ "Convert", "all", "temperature", "recorded", "at", "San", "Francisco", "city", "during", "August", "2013", "into", "degree", "Celsius", "." ]
[ { "id": 8, "type": "column", "value": "mean_temperature_f" }, { "id": 6, "type": "column", "value": "max_temperature_f" }, { "id": 9, "type": "column", "value": "min_temperature_f" }, { "id": 4, "type": "column", "value": "zip_code" }, { "id": 0, "type": "table", "value": "weather" }, { "id": 1, "type": "value", "value": "1.8000" }, { "id": 5, "type": "value", "value": "94107" }, { "id": 3, "type": "value", "value": "2013" }, { "id": 12, "type": "column", "value": "date" }, { "id": 7, "type": "value", "value": "32" }, { "id": 11, "type": "value", "value": "-4" }, { "id": 2, "type": "value", "value": "8" }, { "id": 10, "type": "value", "value": "1" }, { "id": 13, "type": "value", "value": "/" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
14,674
video_games
bird:train.json:3342
How many times more is the number of games which were published by Atari than Athena?
SELECT CAST(COUNT(CASE WHEN T1.publisher_name = 'Atari' THEN T2.game_id ELSE NULL END) AS REAL) / COUNT(CASE WHEN T1.publisher_name = 'Athena' THEN T2.game_id ELSE NULL END) FROM publisher AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.publisher_id
[ "How", "many", "times", "more", "is", "the", "number", "of", "games", "which", "were", "published", "by", "Atari", "than", "Athena", "?" ]
[ { "id": 1, "type": "table", "value": "game_publisher" }, { "id": 5, "type": "column", "value": "publisher_name" }, { "id": 3, "type": "column", "value": "publisher_id" }, { "id": 0, "type": "table", "value": "publisher" }, { "id": 4, "type": "column", "value": "game_id" }, { "id": 6, "type": "value", "value": "Athena" }, { "id": 7, "type": "value", "value": "Atari" }, { "id": 2, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
14,675
voter_2
spider:train_spider.json:5460
What are the maximum and minimum age of students with major 600?
SELECT max(Age) , min(Age) FROM STUDENT WHERE Major = 600
[ "What", "are", "the", "maximum", "and", "minimum", "age", "of", "students", "with", "major", "600", "?" ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "major" }, { "id": 2, "type": "value", "value": "600" }, { "id": 3, "type": "column", "value": "age" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "B-VALUE", "O" ]
14,676
retail_world
bird:train.json:6540
List the employees' full names and ages in 2022 who lived in London.
SELECT TitleOfCourtesy, FirstName, LastName , TIMESTAMPDIFF(YEAR, BirthDate, NOW()) AS ages FROM Employees WHERE City = 'London'
[ "List", "the", "employees", "'", "full", "names", "and", "ages", "in", "2022", "who", "lived", "in", "London", "." ]
[ { "id": 1, "type": "column", "value": "titleofcourtesy" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "firstname" }, { "id": 7, "type": "column", "value": "birthdate" }, { "id": 3, "type": "column", "value": "lastname" }, { "id": 5, "type": "value", "value": "London" }, { "id": 4, "type": "column", "value": "city" }, { "id": 6, "type": "column", "value": "year" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,677
college_1
spider:train_spider.json:3326
What is the last name of the student who received an A in the class with the code 10018?
SELECT T1.stu_lname FROM student AS T1 JOIN enroll AS T2 ON T1.stu_num = T2.stu_num WHERE T2.enroll_grade = 'A' AND T2.class_code = 10018
[ "What", "is", "the", "last", "name", "of", "the", "student", "who", "received", "an", "A", "in", "the", "class", "with", "the", "code", "10018", "?" ]
[ { "id": 4, "type": "column", "value": "enroll_grade" }, { "id": 6, "type": "column", "value": "class_code" }, { "id": 0, "type": "column", "value": "stu_lname" }, { "id": 1, "type": "table", "value": "student" }, { "id": 3, "type": "column", "value": "stu_num" }, { "id": 2, "type": "table", "value": "enroll" }, { "id": 7, "type": "value", "value": "10018" }, { "id": 5, "type": "value", "value": "A" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
14,678
video_games
bird:train.json:3356
List down the game ID of games with genre ID 2.
SELECT T.id FROM game AS T WHERE T.genre_id = 2
[ "List", "down", "the", "game", "ID", "of", "games", "with", "genre", "ID", "2", "." ]
[ { "id": 2, "type": "column", "value": "genre_id" }, { "id": 0, "type": "table", "value": "game" }, { "id": 1, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "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", "B-COLUMN", "B-COLUMN", "B-VALUE", "O" ]
14,679
party_people
spider:train_spider.json:2063
Show names of parties that does not have any members.
SELECT party_name FROM party WHERE party_id NOT IN (SELECT party_id FROM Member)
[ "Show", "names", "of", "parties", "that", "does", "not", "have", "any", "members", "." ]
[ { "id": 1, "type": "column", "value": "party_name" }, { "id": 2, "type": "column", "value": "party_id" }, { "id": 3, "type": "table", "value": "member" }, { "id": 0, "type": "table", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "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", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,680
race_track
spider:train_spider.json:783
Show the name and date for each race and its track name.
SELECT T1.name , T1.date , T2.name FROM race AS T1 JOIN track AS T2 ON T1.track_id = T2.track_id
[ "Show", "the", "name", "and", "date", "for", "each", "race", "and", "its", "track", "name", "." ]
[ { "id": 4, "type": "column", "value": "track_id" }, { "id": 3, "type": "table", "value": "track" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "column", "value": "date" }, { "id": 2, "type": "table", "value": "race" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "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", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
14,681
chinook_1
spider:train_spider.json:839
Show the album names and ids for albums that contain tracks with unit price bigger than 1.
SELECT T1.Title , T2.AlbumID FROM ALBUM AS T1 JOIN TRACK AS T2 ON T1.AlbumId = T2.AlbumId WHERE T2.UnitPrice > 1 GROUP BY T2.AlbumID
[ "Show", "the", "album", "names", "and", "ids", "for", "albums", "that", "contain", "tracks", "with", "unit", "price", "bigger", "than", "1", "." ]
[ { "id": 4, "type": "column", "value": "unitprice" }, { "id": 0, "type": "column", "value": "albumid" }, { "id": 1, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "album" }, { "id": 3, "type": "table", "value": "track" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 12, 13 ] }, { "entity_id": 5, "token_idxs": [ 16 ] }, { "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", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
14,682
hr_1
spider:train_spider.json:3452
What are department ids for departments with managers managing more than 3 employees?
SELECT DISTINCT department_id FROM employees GROUP BY department_id , manager_id HAVING COUNT(employee_id) >= 4
[ "What", "are", "department", "ids", "for", "departments", "with", "managers", "managing", "more", "than", "3", "employees", "?" ]
[ { "id": 1, "type": "column", "value": "department_id" }, { "id": 4, "type": "column", "value": "employee_id" }, { "id": 2, "type": "column", "value": "manager_id" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 3, "type": "value", "value": "4" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "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", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
14,683
hockey
bird:train.json:7813
In 1976, how many goals achieved by team 'BIR' in Division 'EW'?
SELECT SUM(T2.G) FROM Teams AS T1 INNER JOIN Scoring AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.divID = 'EW' AND T1.tmID = 'BIR' AND T1.year = 1976
[ "In", "1976", ",", "how", "many", "goals", "achieved", "by", "team", "'", "BIR", "'", "in", "Division", "'", "EW", "'", "?" ]
[ { "id": 1, "type": "table", "value": "scoring" }, { "id": 0, "type": "table", "value": "teams" }, { "id": 3, "type": "column", "value": "divid" }, { "id": 5, "type": "column", "value": "tmid" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "1976" }, { "id": 6, "type": "value", "value": "BIR" }, { "id": 4, "type": "value", "value": "EW" }, { "id": 2, "type": "column", "value": "g" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 13 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 1 ] }, { "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", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
14,684
planet_1
bird:test.json:1893
List the dates of all shipments.
SELECT Date FROM Shipment;
[ "List", "the", "dates", "of", "all", "shipments", "." ]
[ { "id": 0, "type": "table", "value": "shipment" }, { "id": 1, "type": "column", "value": "date" } ]
[ { "entity_id": 0, "token_idxs": [ 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", "O", "O", "B-TABLE", "O" ]
14,685
superstore
bird:train.json:2428
What is the shipment duration for order number CA-2011-134103?
SELECT DISTINCT strftime('%J', `Ship Date`) - strftime('%J', `Order Date`) AS duration FROM central_superstore WHERE `Order ID` = 'CA-2011-134103'
[ "What", "is", "the", "shipment", "duration", "for", "order", "number", "CA-2011", "-", "134103", "?" ]
[ { "id": 0, "type": "table", "value": "central_superstore" }, { "id": 2, "type": "value", "value": "CA-2011-134103" }, { "id": 5, "type": "column", "value": "Order Date" }, { "id": 4, "type": "column", "value": "Ship Date" }, { "id": 1, "type": "column", "value": "Order ID" }, { "id": 3, "type": "value", "value": "%J" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 3, 4 ] }, { "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-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,686
university_basketball
spider:train_spider.json:977
List all schools and their nicknames in the order of founded year.
SELECT school , nickname FROM university ORDER BY founded
[ "List", "all", "schools", "and", "their", "nicknames", "in", "the", "order", "of", "founded", "year", "." ]
[ { "id": 0, "type": "table", "value": "university" }, { "id": 2, "type": "column", "value": "nickname" }, { "id": 3, "type": "column", "value": "founded" }, { "id": 1, "type": "column", "value": "school" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "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-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,687
customers_and_addresses
spider:train_spider.json:6108
Find the name of the customer who made the order of the largest amount of goods.
SELECT t1.customer_name FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id JOIN order_items AS t3 ON t2.order_id = t3.order_id WHERE t3.order_quantity = ( SELECT max(order_quantity) FROM order_items)
[ "Find", "the", "name", "of", "the", "customer", "who", "made", "the", "order", "of", "the", "largest", "amount", "of", "goods", "." ]
[ { "id": 4, "type": "table", "value": "customer_orders" }, { "id": 2, "type": "column", "value": "order_quantity" }, { "id": 0, "type": "column", "value": "customer_name" }, { "id": 1, "type": "table", "value": "order_items" }, { "id": 6, "type": "column", "value": "customer_id" }, { "id": 3, "type": "table", "value": "customers" }, { "id": 5, "type": "column", "value": "order_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "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", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
14,688
legislator
bird:train.json:4799
Among the legislators who have served in the U.S. House, provide the party and the state of the legislators who were born in 1738.
SELECT T1.party, T1.state FROM `historical-terms` AS T1 INNER JOIN historical AS T2 ON T2.bioguide_id = T1.bioguide WHERE T2.house_history_id IS NOT NULL AND T2.birthday_bio LIKE '%1738%'
[ "Among", "the", "legislators", "who", "have", "served", "in", "the", "U.S.", "House", ",", "provide", "the", "party", "and", "the", "state", "of", "the", "legislators", "who", "were", "born", "in", "1738", "." ]
[ { "id": 2, "type": "table", "value": "historical-terms" }, { "id": 6, "type": "column", "value": "house_history_id" }, { "id": 7, "type": "column", "value": "birthday_bio" }, { "id": 4, "type": "column", "value": "bioguide_id" }, { "id": 3, "type": "table", "value": "historical" }, { "id": 5, "type": "column", "value": "bioguide" }, { "id": 8, "type": "value", "value": "%1738%" }, { "id": 0, "type": "column", "value": "party" }, { "id": 1, "type": "column", "value": "state" } ]
[ { "entity_id": 0, "token_idxs": [ 13 ] }, { "entity_id": 1, "token_idxs": [ 16 ] }, { "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": [ 24 ] }, { "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", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,689
superstore
bird:train.json:2353
Please list the names of all the customers who had ordered the product "Telescoping Adjustable Floor Lamp".
SELECT DISTINCT T1.`Customer Name` FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T2.`Product ID` WHERE T3.`Product Name` = 'Telescoping Adjustable Floor Lamp'
[ "Please", "list", "the", "names", "of", "all", "the", "customers", "who", "had", "ordered", "the", "product", "\"", "Telescoping", "Adjustable", "Floor", "Lamp", "\"", "." ]
[ { "id": 3, "type": "value", "value": "Telescoping Adjustable Floor Lamp" }, { "id": 5, "type": "table", "value": "central_superstore" }, { "id": 0, "type": "column", "value": "Customer Name" }, { "id": 2, "type": "column", "value": "Product Name" }, { "id": 7, "type": "column", "value": "Customer ID" }, { "id": 6, "type": "column", "value": "Product ID" }, { "id": 1, "type": "table", "value": "product" }, { "id": 4, "type": "table", "value": "people" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 14, 15, 16, 17 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 13 ] }, { "entity_id": 7, "token_idxs": [ 7 ] }, { "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", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
14,690
shop_membership
spider:train_spider.json:5416
Show card number, name, and hometown for all members in a descending order of level.
SELECT card_number , name , hometown FROM member ORDER BY LEVEL DESC
[ "Show", "card", "number", ",", "name", ",", "and", "hometown", "for", "all", "members", "in", "a", "descending", "order", "of", "level", "." ]
[ { "id": 1, "type": "column", "value": "card_number" }, { "id": 3, "type": "column", "value": "hometown" }, { "id": 0, "type": "table", "value": "member" }, { "id": 4, "type": "column", "value": "level" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 1, 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "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", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,691
flight_1
spider:train_spider.json:421
Show ids for all employees who don't have a certificate.
SELECT eid FROM Employee EXCEPT SELECT eid FROM Certificate
[ "Show", "ids", "for", "all", "employees", "who", "do", "n't", "have", "a", "certificate", "." ]
[ { "id": 1, "type": "table", "value": "certificate" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 2, "type": "column", "value": "eid" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 1 ] }, { "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", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,692
bike_share_1
bird:train.json:9077
What is the longest trip duration according? Convert the it to number of days.
SELECT MAX(duration), CAST(MAX(duration) AS REAL) / 86400 FROM trip
[ "What", "is", "the", "longest", "trip", "duration", "according", "?", "Convert", "the", "it", "to", "number", "of", "days", "." ]
[ { "id": 1, "type": "column", "value": "duration" }, { "id": 2, "type": "value", "value": "86400" }, { "id": 0, "type": "table", "value": "trip" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "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", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,693
university
bird:train.json:8073
How many students did Harvard University have in 2011?
SELECT T1.num_students FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T2.university_name = 'Harvard University' AND T1.year = 2011
[ "How", "many", "students", "did", "Harvard", "University", "have", "in", "2011", "?" ]
[ { "id": 6, "type": "value", "value": "Harvard University" }, { "id": 1, "type": "table", "value": "university_year" }, { "id": 5, "type": "column", "value": "university_name" }, { "id": 3, "type": "column", "value": "university_id" }, { "id": 0, "type": "column", "value": "num_students" }, { "id": 2, "type": "table", "value": "university" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "2011" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 3 ] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [ 4 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 8 ] }, { "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-COLUMN", "B-VALUE", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
14,694
insurance_policies
spider:train_spider.json:3897
What is total amount claimed summed across all the claims?
SELECT sum(Amount_Claimed) FROM Claims
[ "What", "is", "total", "amount", "claimed", "summed", "across", "all", "the", "claims", "?" ]
[ { "id": 1, "type": "column", "value": "amount_claimed" }, { "id": 0, "type": "table", "value": "claims" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "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", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
14,695
cre_Docs_and_Epenses
spider:train_spider.json:6462
Give the ids of documents that have expenses and contain the letter s in their names.
SELECT T1.document_id FROM Documents AS T1 JOIN Documents_with_expenses AS T2 ON T1.document_id = T2.document_id WHERE T1.document_name LIKE '%s%'
[ "Give", "the", "ids", "of", "documents", "that", "have", "expenses", "and", "contain", "the", "letter", "s", "in", "their", "names", "." ]
[ { "id": 2, "type": "table", "value": "documents_with_expenses" }, { "id": 3, "type": "column", "value": "document_name" }, { "id": 0, "type": "column", "value": "document_id" }, { "id": 1, "type": "table", "value": "documents" }, { "id": 4, "type": "value", "value": "%s%" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 5, 6, 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", "O", "O", "O", "B-TABLE", "B-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,696
warehouse_1
bird:test.json:1685
Select contents of all boxes with a value larger than $150.
SELECT CONTENTS FROM boxes WHERE Value > 150
[ "Select", "contents", "of", "all", "boxes", "with", "a", "value", "larger", "than", "$", "150", "." ]
[ { "id": 1, "type": "column", "value": "contents" }, { "id": 0, "type": "table", "value": "boxes" }, { "id": 2, "type": "column", "value": "value" }, { "id": 3, "type": "value", "value": "150" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "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", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
14,697
image_and_language
bird:train.json:7491
State the total number of the attribute classes.
SELECT COUNT(ATT_CLASS_ID) FROM ATT_CLASSES
[ "State", "the", "total", "number", "of", "the", "attribute", "classes", "." ]
[ { "id": 1, "type": "column", "value": "att_class_id" }, { "id": 0, "type": "table", "value": "att_classes" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "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", "B-TABLE", "O" ]
14,698
driving_school
spider:train_spider.json:6687
What is the zip code of the customer Carole Bernhard?
SELECT T2.zip_postcode FROM Customers AS T1 JOIN Addresses AS T2 ON T1.customer_address_id = T2.address_id WHERE T1.first_name = "Carole" AND T1.last_name = "Bernhard"
[ "What", "is", "the", "zip", "code", "of", "the", "customer", "Carole", "Bernhard", "?" ]
[ { "id": 3, "type": "column", "value": "customer_address_id" }, { "id": 0, "type": "column", "value": "zip_postcode" }, { "id": 4, "type": "column", "value": "address_id" }, { "id": 5, "type": "column", "value": "first_name" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "addresses" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 8, "type": "column", "value": "Bernhard" }, { "id": 6, "type": "column", "value": "Carole" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "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": [ 8 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 9 ] }, { "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", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O" ]
14,700
real_estate_rentals
bird:test.json:1447
Count the number of properties with at least two features.
SELECT count(*) FROM Properties GROUP BY property_id HAVING count(*) >= 2;
[ "Count", "the", "number", "of", "properties", "with", "at", "least", "two", "features", "." ]
[ { "id": 1, "type": "column", "value": "property_id" }, { "id": 0, "type": "table", "value": "properties" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "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", "O", "O", "O", "O", "O" ]
14,701
works_cycles
bird:train.json:7059
What is the pay rate of the employee who has the longest vacation hours?
SELECT T1.Rate FROM EmployeePayHistory AS T1 INNER JOIN Employee AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID ORDER BY T2.VacationHours DESC LIMIT 1
[ "What", "is", "the", "pay", "rate", "of", "the", "employee", "who", "has", "the", "longest", "vacation", "hours", "?" ]
[ { "id": 1, "type": "table", "value": "employeepayhistory" }, { "id": 4, "type": "column", "value": "businessentityid" }, { "id": 3, "type": "column", "value": "vacationhours" }, { "id": 2, "type": "table", "value": "employee" }, { "id": 0, "type": "column", "value": "rate" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 12, 13 ] }, { "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", "B-TABLE", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,702
county_public_safety
spider:train_spider.json:2545
Return the hispanic percentage for cities in which the black percentage is greater than 10.
SELECT Hispanic FROM city WHERE Black > 10
[ "Return", "the", "hispanic", "percentage", "for", "cities", "in", "which", "the", "black", "percentage", "is", "greater", "than", "10", "." ]
[ { "id": 1, "type": "column", "value": "hispanic" }, { "id": 2, "type": "column", "value": "black" }, { "id": 0, "type": "table", "value": "city" }, { "id": 3, "type": "value", "value": "10" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "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", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O" ]
14,703
dorm_1
spider:train_spider.json:5699
What are the names and types of the dorms that have a capacity greater than 300 or less than 100?
SELECT dorm_name , gender FROM dorm WHERE student_capacity > 300 OR student_capacity < 100
[ "What", "are", "the", "names", "and", "types", "of", "the", "dorms", "that", "have", "a", "capacity", "greater", "than", "300", "or", "less", "than", "100", "?" ]
[ { "id": 3, "type": "column", "value": "student_capacity" }, { "id": 1, "type": "column", "value": "dorm_name" }, { "id": 2, "type": "column", "value": "gender" }, { "id": 0, "type": "table", "value": "dorm" }, { "id": 4, "type": "value", "value": "300" }, { "id": 5, "type": "value", "value": "100" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [ 19 ] }, { "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", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O" ]
14,704
address
bird:train.json:5084
Please list the numbers of males in all the residential areas in Arecibo county.
SELECT SUM(T1.male_population) FROM zip_data AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T2.county = 'ARECIBO'
[ "Please", "list", "the", "numbers", "of", "males", "in", "all", "the", "residential", "areas", "in", "Arecibo", "county", "." ]
[ { "id": 4, "type": "column", "value": "male_population" }, { "id": 0, "type": "table", "value": "zip_data" }, { "id": 5, "type": "column", "value": "zip_code" }, { "id": 1, "type": "table", "value": "country" }, { "id": 3, "type": "value", "value": "ARECIBO" }, { "id": 2, "type": "column", "value": "county" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,705
superstore
bird:train.json:2382
Provide the order ID of Frank Olsen of the South region.
SELECT T1.`Order ID` FROM south_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T2.Region = 'South' AND T2.`Customer Name` = 'Frank Olsen'
[ "Provide", "the", "order", "ID", "of", "Frank", "Olsen", "of", "the", "South", "region", "." ]
[ { "id": 1, "type": "table", "value": "south_superstore" }, { "id": 6, "type": "column", "value": "Customer Name" }, { "id": 3, "type": "column", "value": "Customer ID" }, { "id": 7, "type": "value", "value": "Frank Olsen" }, { "id": 0, "type": "column", "value": "Order ID" }, { "id": 2, "type": "table", "value": "people" }, { "id": 4, "type": "column", "value": "region" }, { "id": 5, "type": "value", "value": "South" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,706
codebase_comments
bird:train.json:571
What is the most liked repository? Indicate its github address and the amount of stars it has received.
SELECT Url, Stars FROM Repo WHERE Stars = ( SELECT MAX(Stars) FROM Repo )
[ "What", "is", "the", "most", "liked", "repository", "?", "Indicate", "its", "github", "address", "and", "the", "amount", "of", "stars", "it", "has", "received", "." ]
[ { "id": 2, "type": "column", "value": "stars" }, { "id": 0, "type": "table", "value": "repo" }, { "id": 1, "type": "column", "value": "url" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "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", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
14,707
synthea
bird:train.json:1435
How many stroke patients have married?
SELECT COUNT(DISTINCT T1.patient) FROM patients AS T1 INNER JOIN conditions AS T2 ON T1.patient = T2.PATIENT WHERE T2.DESCRIPTION = 'Stroke' AND T1.marital = 'M'
[ "How", "many", "stroke", "patients", "have", "married", "?" ]
[ { "id": 3, "type": "column", "value": "description" }, { "id": 1, "type": "table", "value": "conditions" }, { "id": 0, "type": "table", "value": "patients" }, { "id": 2, "type": "column", "value": "patient" }, { "id": 5, "type": "column", "value": "marital" }, { "id": 4, "type": "value", "value": "Stroke" }, { "id": 6, "type": "value", "value": "M" } ]
[ { "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": [ 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-VALUE", "B-COLUMN", "O", "O", "O" ]
14,708
perpetrator
spider:train_spider.json:2319
List the names of people that are not perpetrators.
SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM perpetrator)
[ "List", "the", "names", "of", "people", "that", "are", "not", "perpetrators", "." ]
[ { "id": 3, "type": "table", "value": "perpetrator" }, { "id": 2, "type": "column", "value": "people_id" }, { "id": 0, "type": "table", "value": "people" }, { "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": [ 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", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
14,710
race_track
spider:train_spider.json:756
Return the minimum, maximum, and average seating across all tracks.
SELECT min(seating) , max(seating) , avg(seating) FROM track
[ "Return", "the", "minimum", ",", "maximum", ",", "and", "average", "seating", "across", "all", "tracks", "." ]
[ { "id": 1, "type": "column", "value": "seating" }, { "id": 0, "type": "table", "value": "track" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,711
e_learning
spider:train_spider.json:3787
Count the number of tests with "Fail" result.
SELECT count(*) FROM Student_Tests_Taken WHERE test_result = "Fail"
[ "Count", "the", "number", "of", "tests", "with", "\"", "Fail", "\"", "result", "." ]
[ { "id": 0, "type": "table", "value": "student_tests_taken" }, { "id": 1, "type": "column", "value": "test_result" }, { "id": 2, "type": "column", "value": "Fail" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "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", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
14,712
thrombosis_prediction
bird:dev.json:1278
Of the patients with an normal level of IGG, how many of them admitted to the hospital?
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.IGG > 900 AND T2.IGG <2000 AND T1.Admission = '+'
[ "Of", "the", "patients", "with", "an", "normal", "level", "of", "IGG", ",", "how", "many", "of", "them", "admitted", "to", "the", "hospital", "?" ]
[ { "id": 1, "type": "table", "value": "laboratory" }, { "id": 6, "type": "column", "value": "admission" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 5, "type": "value", "value": "2000" }, { "id": 3, "type": "column", "value": "igg" }, { "id": 4, "type": "value", "value": "900" }, { "id": 2, "type": "column", "value": "id" }, { "id": 7, "type": "value", "value": "+" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,713
sales
bird:train.json:5445
How many types of "HL Touring Frames" are there?
SELECT COUNT(ProductID) FROM Products WHERE Name LIKE '%HL Touring Frame%'
[ "How", "many", "types", "of", "\"", "HL", "Touring", "Frames", "\"", "are", "there", "?" ]
[ { "id": 2, "type": "value", "value": "%HL Touring Frame%" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 0, "type": "table", "value": "products" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 5, 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", "B-VALUE", "I-VALUE", "B-COLUMN", "O", "O", "O", "O" ]
14,714
computer_student
bird:train.json:1007
List down the advised student IDs and IDs of employing professor in faculty.
SELECT T1.p_id, T2.p_id FROM advisedBy AS T1 INNER JOIN person AS T2 ON T1.p_id_dummy = T2.p_id WHERE hasPosition = 'Faculty_eme'
[ "List", "down", "the", "advised", "student", "IDs", "and", "IDs", "of", "employing", "professor", "in", "faculty", "." ]
[ { "id": 3, "type": "column", "value": "hasposition" }, { "id": 4, "type": "value", "value": "Faculty_eme" }, { "id": 5, "type": "column", "value": "p_id_dummy" }, { "id": 1, "type": "table", "value": "advisedby" }, { "id": 2, "type": "table", "value": "person" }, { "id": 0, "type": "column", "value": "p_id" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,715
student_loan
bird:train.json:4543
Among the male students, list down the names of students with payment due.
SELECT T1.name FROM male AS T1 INNER JOIN no_payment_due AS T2 ON T1.name = T2.name WHERE T2.bool = 'pos'
[ "Among", "the", "male", "students", ",", "list", "down", "the", "names", "of", "students", "with", "payment", "due", "." ]
[ { "id": 2, "type": "table", "value": "no_payment_due" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "table", "value": "male" }, { "id": 3, "type": "column", "value": "bool" }, { "id": 4, "type": "value", "value": "pos" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
14,716
gas_company
spider:train_spider.json:2025
Show company name and main industry without a gas station.
SELECT company , main_industry FROM company WHERE company_id NOT IN (SELECT company_id FROM station_company)
[ "Show", "company", "name", "and", "main", "industry", "without", "a", "gas", "station", "." ]
[ { "id": 4, "type": "table", "value": "station_company" }, { "id": 2, "type": "column", "value": "main_industry" }, { "id": 3, "type": "column", "value": "company_id" }, { "id": 0, "type": "table", "value": "company" }, { "id": 1, "type": "column", "value": "company" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 4, 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 0 ] }, { "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": [] } ]
[ "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
14,717
works_cycles
bird:train.json:7009
List all product names that are high in quality. Please also state its selling price.
SELECT Name, ListPrice FROM Product WHERE Class = 'H'
[ "List", "all", "product", "names", "that", "are", "high", "in", "quality", ".", "Please", "also", "state", "its", "selling", "price", "." ]
[ { "id": 2, "type": "column", "value": "listprice" }, { "id": 0, "type": "table", "value": "product" }, { "id": 3, "type": "column", "value": "class" }, { "id": 1, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "H" } ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,718
music_tracker
bird:train.json:2064
Provide the name of the artist who released his or her Single-Table in 2012 with the highest number of downloads. Name the Single-Table title as well.
SELECT artist, groupName FROM torrents WHERE groupYear = 2012 AND releaseType LIKE 'Single' ORDER BY totalSnatched DESC LIMIT 1
[ "Provide", "the", "name", "of", "the", "artist", "who", "released", "his", "or", "her", "Single", "-", "Table", "in", "2012", "with", "the", "highest", "number", "of", "downloads", ".", "Name", "the", "Single", "-", "Table", "title", "as", "well", "." ]
[ { "id": 3, "type": "column", "value": "totalsnatched" }, { "id": 6, "type": "column", "value": "releasetype" }, { "id": 2, "type": "column", "value": "groupname" }, { "id": 4, "type": "column", "value": "groupyear" }, { "id": 0, "type": "table", "value": "torrents" }, { "id": 1, "type": "column", "value": "artist" }, { "id": 7, "type": "value", "value": "Single" }, { "id": 5, "type": "value", "value": "2012" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 23 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [ 7 ] }, { "entity_id": 7, "token_idxs": [ 25 ] }, { "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-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O" ]
14,719
talkingdata
bird:train.json:1136
How many more devices are there of the brand vivo than of the brand LG?
SELECT SUM(IIF(phone_brand = 'vivo', 1, 0)) - SUM(IIF(phone_brand = 'LG', 1, 0)) AS num FROM phone_brand_device_model2
[ "How", "many", "more", "devices", "are", "there", "of", "the", "brand", "vivo", "than", "of", "the", "brand", "LG", "?" ]
[ { "id": 0, "type": "table", "value": "phone_brand_device_model2" }, { "id": 3, "type": "column", "value": "phone_brand" }, { "id": 4, "type": "value", "value": "vivo" }, { "id": 5, "type": "value", "value": "LG" }, { "id": 1, "type": "value", "value": "1" }, { "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": [ 7, 8 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "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", "I-COLUMN", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O" ]
14,720
card_games
bird:dev.json:454
Among the cards with a white border color, how many of them have unknown power?
SELECT SUM(CASE WHEN power LIKE '%*%' OR power IS NULL THEN 1 ELSE 0 END) FROM cards WHERE borderColor = 'white'
[ "Among", "the", "cards", "with", "a", "white", "border", "color", ",", "how", "many", "of", "them", "have", "unknown", "power", "?" ]
[ { "id": 1, "type": "column", "value": "bordercolor" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 2, "type": "value", "value": "white" }, { "id": 5, "type": "column", "value": "power" }, { "id": 6, "type": "value", "value": "%*%" }, { "id": 3, "type": "value", "value": "0" }, { "id": 4, "type": "value", "value": "1" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,721
superhero
bird:dev.json:749
Provide the superpowers of the superhero called Deathlok.
SELECT T3.power_name FROM superhero AS T1 INNER JOIN hero_power AS T2 ON T1.id = T2.hero_id INNER JOIN superpower AS T3 ON T2.power_id = T3.id WHERE T1.superhero_name = 'Deathlok'
[ "Provide", "the", "superpowers", "of", "the", "superhero", "called", "Deathlok", "." ]
[ { "id": 2, "type": "column", "value": "superhero_name" }, { "id": 0, "type": "column", "value": "power_name" }, { "id": 1, "type": "table", "value": "superpower" }, { "id": 5, "type": "table", "value": "hero_power" }, { "id": 4, "type": "table", "value": "superhero" }, { "id": 3, "type": "value", "value": "Deathlok" }, { "id": 6, "type": "column", "value": "power_id" }, { "id": 8, "type": "column", "value": "hero_id" }, { "id": 7, "type": "column", "value": "id" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
14,722
retail_complains
bird:train.json:294
How many complaints are not in process with an agent?
SELECT COUNT(outcome) FROM callcenterlogs WHERE outcome != 'AGENT'
[ "How", "many", "complaints", "are", "not", "in", "process", "with", "an", "agent", "?" ]
[ { "id": 0, "type": "table", "value": "callcenterlogs" }, { "id": 1, "type": "column", "value": "outcome" }, { "id": 2, "type": "value", "value": "AGENT" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "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", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,723
cre_Drama_Workshop_Groups
spider:train_spider.json:5115
Find the phone number of performer "Ashley".
SELECT Customer_Phone FROM PERFORMERS WHERE Customer_Name = "Ashley"
[ "Find", "the", "phone", "number", "of", "performer", "\"", "Ashley", "\"", "." ]
[ { "id": 1, "type": "column", "value": "customer_phone" }, { "id": 2, "type": "column", "value": "customer_name" }, { "id": 0, "type": "table", "value": "performers" }, { "id": 3, "type": "column", "value": "Ashley" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 1, 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "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-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O" ]
14,724
public_review_platform
bird:train.json:3998
How many photos type compliment given from users with high cool votes?
SELECT COUNT(T1.user_id) FROM Users AS T1 INNER JOIN Users_Compliments AS T2 ON T1.user_id = T2.user_id INNER JOIN Compliments AS T3 ON T2.compliment_id = T3.compliment_id INNER JOIN Reviews AS T4 ON T1.user_id = T4.user_id WHERE T3.compliment_type = 'photos' AND T4.review_votes_cool = 'High'
[ "How", "many", "photos", "type", "compliment", "given", "from", "users", "with", "high", "cool", "votes", "?" ]
[ { "id": 5, "type": "column", "value": "review_votes_cool" }, { "id": 8, "type": "table", "value": "users_compliments" }, { "id": 3, "type": "column", "value": "compliment_type" }, { "id": 9, "type": "column", "value": "compliment_id" }, { "id": 2, "type": "table", "value": "compliments" }, { "id": 0, "type": "table", "value": "reviews" }, { "id": 1, "type": "column", "value": "user_id" }, { "id": 4, "type": "value", "value": "photos" }, { "id": 7, "type": "table", "value": "users" }, { "id": 6, "type": "value", "value": "High" } ]
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[ "O", "O", "B-VALUE", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O" ]
14,725
toxicology
bird:dev.json:338
What is the atom ID of double bonded carbon in TR012 molecule?
SELECT T1.atom_id FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id INNER JOIN bond AS T3 ON T2.molecule_id = T3.molecule_id WHERE T2.molecule_id = 'TR012' AND T3.bond_type = '=' AND T1.element = 'c'
[ "What", "is", "the", "atom", "ID", "of", "double", "bonded", "carbon", "in", "TR012", "molecule", "?" ]
[ { "id": 4, "type": "column", "value": "molecule_id" }, { "id": 6, "type": "column", "value": "bond_type" }, { "id": 3, "type": "table", "value": "molecule" }, { "id": 0, "type": "column", "value": "atom_id" }, { "id": 8, "type": "column", "value": "element" }, { "id": 5, "type": "value", "value": "TR012" }, { "id": 1, "type": "table", "value": "bond" }, { "id": 2, "type": "table", "value": "atom" }, { "id": 7, "type": "value", "value": "=" }, { "id": 9, "type": "value", "value": "c" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-TABLE", "O" ]
14,726
college_completion
bird:train.json:3741
In female students in year 2012, how many of them from a state with number of schools ranges from 10 to 20?
SELECT COUNT(T2.race) FROM state_sector_details AS T1 INNER JOIN state_sector_grads AS T2 ON T2.stateid = T1.stateid WHERE T2.gender = 'F' AND schools_count BETWEEN 10 AND 20 AND T2.year = 2012
[ "In", "female", "students", "in", "year", "2012", ",", "how", "many", "of", "them", "from", "a", "state", "with", "number", "of", "schools", "ranges", "from", "10", "to", "20", "?" ]
[ { "id": 0, "type": "table", "value": "state_sector_details" }, { "id": 1, "type": "table", "value": "state_sector_grads" }, { "id": 6, "type": "column", "value": "schools_count" }, { "id": 3, "type": "column", "value": "stateid" }, { "id": 4, "type": "column", "value": "gender" }, { "id": 2, "type": "column", "value": "race" }, { "id": 9, "type": "column", "value": "year" }, { "id": 10, "type": "value", "value": "2012" }, { "id": 7, "type": "value", "value": "10" }, { "id": 8, "type": "value", "value": "20" }, { "id": 5, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O" ]
14,729
country_language
bird:test.json:1375
What is the name of the country with the highest politics score?
SELECT name FROM countries ORDER BY politics_score DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "country", "with", "the", "highest", "politics", "score", "?" ]
[ { "id": 2, "type": "column", "value": "politics_score" }, { "id": 0, "type": "table", "value": "countries" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 10, 11 ] }, { "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", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,730
gymnast
spider:train_spider.json:1751
Return the age of the person with the greatest height.
SELECT Age FROM people ORDER BY Height DESC LIMIT 1
[ "Return", "the", "age", "of", "the", "person", "with", "the", "greatest", "height", "." ]
[ { "id": 0, "type": "table", "value": "people" }, { "id": 2, "type": "column", "value": "height" }, { "id": 1, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "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", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,731
hospital_1
spider:train_spider.json:3908
Find the id of the appointment with the most recent start date?
SELECT appointmentid FROM appointment ORDER BY START DESC LIMIT 1
[ "Find", "the", "i", "d", "of", "the", "appointment", "with", "the", "most", "recent", "start", "date", "?" ]
[ { "id": 1, "type": "column", "value": "appointmentid" }, { "id": 0, "type": "table", "value": "appointment" }, { "id": 2, "type": "column", "value": "start" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "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-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,732
shop_membership
spider:train_spider.json:5408
List all open years when at least two shops are opened.
SELECT open_year FROM branch GROUP BY open_year HAVING count(*) >= 2
[ "List", "all", "open", "years", "when", "at", "least", "two", "shops", "are", "opened", "." ]
[ { "id": 1, "type": "column", "value": "open_year" }, { "id": 0, "type": "table", "value": "branch" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 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", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,733
professional_basketball
bird:train.json:2808
What division did the team coached by the winner of the 1977 NBA Coach of the Year award play in in 1976?
SELECT DISTINCT T3.divID FROM awards_coaches AS T1 INNER JOIN coaches AS T2 ON T1.coachID = T2.coachID INNER JOIN teams AS T3 ON T2.tmID = T3.tmID WHERE T1.year = 1977 AND T1.award = 'NBA Coach of the Year' AND T3.year = 1976
[ "What", "division", "did", "the", "team", "coached", "by", "the", "winner", "of", "the", "1977", "NBA", "Coach", "of", "the", "Year", "award", "play", "in", "in", "1976", "?" ]
[ { "id": 8, "type": "value", "value": "NBA Coach of the Year" }, { "id": 2, "type": "table", "value": "awards_coaches" }, { "id": 3, "type": "table", "value": "coaches" }, { "id": 10, "type": "column", "value": "coachid" }, { "id": 0, "type": "column", "value": "divid" }, { "id": 1, "type": "table", "value": "teams" }, { "id": 7, "type": "column", "value": "award" }, { "id": 4, "type": "column", "value": "tmid" }, { "id": 5, "type": "column", "value": "year" }, { "id": 6, "type": "value", "value": "1977" }, { "id": 9, "type": "value", "value": "1976" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
14,734
bike_share_1
bird:train.json:9017
On 11/3/2013, which stations are often empty? Indicate the names of the stations.
SELECT DISTINCT T1.name FROM station AS T1 INNER JOIN status AS T2 ON T2.station_id = T1.id WHERE T2.bikes_available = 0 AND T2.time LIKE '2013/11/03%'
[ "On", "11/3/2013", ",", "which", "stations", "are", "often", "empty", "?", "Indicate", "the", "names", "of", "the", "stations", "." ]
[ { "id": 5, "type": "column", "value": "bikes_available" }, { "id": 8, "type": "value", "value": "2013/11/03%" }, { "id": 3, "type": "column", "value": "station_id" }, { "id": 1, "type": "table", "value": "station" }, { "id": 2, "type": "table", "value": "status" }, { "id": 0, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "time" }, { "id": 4, "type": "column", "value": "id" }, { "id": 6, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,735
game_1
spider:train_spider.json:5978
What are the names of all video games that are collectible cards?
SELECT gname FROM Video_games WHERE gtype = "Collectible card game"
[ "What", "are", "the", "names", "of", "all", "video", "games", "that", "are", "collectible", "cards", "?" ]
[ { "id": 3, "type": "column", "value": "Collectible card game" }, { "id": 0, "type": "table", "value": "video_games" }, { "id": 1, "type": "column", "value": "gname" }, { "id": 2, "type": "column", "value": "gtype" } ]
[ { "entity_id": 0, "token_idxs": [ 6, 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10, 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", "O", "B-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,736
cre_Drama_Workshop_Groups
spider:train_spider.json:5144
What are the actual delivery dates of orders with quantity 1?
SELECT T1.Actual_Delivery_Date FROM Customer_Orders AS T1 JOIN ORDER_ITEMS AS T2 ON T1.Order_ID = T2.Order_ID WHERE T2.Order_Quantity = 1
[ "What", "are", "the", "actual", "delivery", "dates", "of", "orders", "with", "quantity", "1", "?" ]
[ { "id": 0, "type": "column", "value": "actual_delivery_date" }, { "id": 1, "type": "table", "value": "customer_orders" }, { "id": 3, "type": "column", "value": "order_quantity" }, { "id": 2, "type": "table", "value": "order_items" }, { "id": 5, "type": "column", "value": "order_id" }, { "id": 4, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8, 9 ] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "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", "B-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
14,738
college_completion
bird:train.json:3738
List the site of institution within the student count of 500 to 1000 that has the recent year of data release.
SELECT DISTINCT T1.site FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T1.student_count BETWEEN 500 AND 1000 AND T2.year = ( SELECT MAX(T2.year) FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid )
[ "List", "the", "site", "of", "institution", "within", "the", "student", "count", "of", "500", "to", "1000", "that", "has", "the", "recent", "year", "of", "data", "release", "." ]
[ { "id": 1, "type": "table", "value": "institution_details" }, { "id": 2, "type": "table", "value": "institution_grads" }, { "id": 4, "type": "column", "value": "student_count" }, { "id": 3, "type": "column", "value": "unitid" }, { "id": 0, "type": "column", "value": "site" }, { "id": 6, "type": "value", "value": "1000" }, { "id": 7, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "500" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
14,740
retail_complains
bird:train.json:362
What is the email address of clients who submitted their complaints via postal mail?
SELECT T1.email FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Submitted via` = 'Postal mail'
[ "What", "is", "the", "email", "address", "of", "clients", "who", "submitted", "their", "complaints", "via", "postal", "mail", "?" ]
[ { "id": 3, "type": "column", "value": "Submitted via" }, { "id": 4, "type": "value", "value": "Postal mail" }, { "id": 5, "type": "column", "value": "client_id" }, { "id": 1, "type": "table", "value": "client" }, { "id": 2, "type": "table", "value": "events" }, { "id": 0, "type": "column", "value": "email" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 12, 13 ] }, { "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", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
14,741
ice_hockey_draft
bird:train.json:6924
How much taller is David Bornhammar than Pauli Levokari in centimeters?
SELECT ( SELECT T2.height_in_cm FROM PlayerInfo AS T1 INNER JOIN height_info AS T2 ON T1.height = T2.height_id WHERE T1.PlayerName = 'David Bornhammar' ) - ( SELECT T2.height_in_cm FROM PlayerInfo AS T1 INNER JOIN height_info AS T2 ON T1.height = T2.height_id WHERE T1.PlayerName = 'Pauli Levokari' )
[ "How", "much", "taller", "is", "David", "Bornhammar", "than", "Pauli", "Levokari", "in", "centimeters", "?" ]
[ { "id": 4, "type": "value", "value": "David Bornhammar" }, { "id": 5, "type": "value", "value": "Pauli Levokari" }, { "id": 0, "type": "column", "value": "height_in_cm" }, { "id": 2, "type": "table", "value": "height_info" }, { "id": 1, "type": "table", "value": "playerinfo" }, { "id": 3, "type": "column", "value": "playername" }, { "id": 7, "type": "column", "value": "height_id" }, { "id": 6, "type": "column", "value": "height" } ]
[ { "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": [ 4, 5 ] }, { "entity_id": 5, "token_idxs": [ 7, 8 ] }, { "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-VALUE", "I-VALUE", "O", "B-VALUE", "I-VALUE", "O", "O", "O" ]
14,742
bbc_channels
bird:test.json:126
Find the name and age of the director who is in charge of the most programs?
SELECT t2.name , t2.age FROM program AS t1 JOIN director AS t2 ON t1.director_id = t2.director_id GROUP BY t1.director_id ORDER BY count(*) DESC LIMIT 1
[ "Find", "the", "name", "and", "age", "of", "the", "director", "who", "is", "in", "charge", "of", "the", "most", "programs", "?" ]
[ { "id": 0, "type": "column", "value": "director_id" }, { "id": 4, "type": "table", "value": "director" }, { "id": 3, "type": "table", "value": "program" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "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", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,743
mountain_photos
spider:train_spider.json:3726
List the camera lens names containing substring "Digital".
SELECT name FROM camera_lens WHERE name LIKE "%Digital%"
[ "List", "the", "camera", "lens", "names", "containing", "substring", "\"", "Digital", "\"", "." ]
[ { "id": 0, "type": "table", "value": "camera_lens" }, { "id": 2, "type": "column", "value": "%Digital%" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "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", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,744
world_development_indicators
bird:train.json:2139
Which country has the highest value of Merchandise imports by the reporting economy (current US$)?
SELECT CountryName FROM Indicators WHERE IndicatorName = 'Merchandise imports by the reporting economy (current US$)' ORDER BY Value DESC LIMIT 1
[ "Which", "country", "has", "the", "highest", "value", "of", "Merchandise", "imports", "by", "the", "reporting", "economy", "(", "current", "US$", ")", "?" ]
[ { "id": 3, "type": "value", "value": "Merchandise imports by the reporting economy (current US$)" }, { "id": 2, "type": "column", "value": "indicatorname" }, { "id": 1, "type": "column", "value": "countryname" }, { "id": 0, "type": "table", "value": "indicators" }, { "id": 4, "type": "column", "value": "value" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "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", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,745
address_1
bird:test.json:805
Show ids for all students who don't live in USA.
SELECT StuID FROM Student EXCEPT SELECT StuID FROM City AS T1 JOIN Student AS T2 ON T1.city_code = T2.city_code WHERE country = "USA"
[ "Show", "ids", "for", "all", "students", "who", "do", "n't", "live", "in", "USA", "." ]
[ { "id": 5, "type": "column", "value": "city_code" }, { "id": 0, "type": "table", "value": "student" }, { "id": 3, "type": "column", "value": "country" }, { "id": 1, "type": "column", "value": "stuid" }, { "id": 2, "type": "table", "value": "city" }, { "id": 4, "type": "column", "value": "USA" } ]
[ { "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": [ 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", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,747
law_episode
bird:train.json:1312
What is the title of the episode with the most nominations?
SELECT T2.title FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id WHERE T1.result = 'Nominee' GROUP BY T2.episode_id ORDER BY COUNT(T1.result) DESC LIMIT 1
[ "What", "is", "the", "title", "of", "the", "episode", "with", "the", "most", "nominations", "?" ]
[ { "id": 0, "type": "column", "value": "episode_id" }, { "id": 3, "type": "table", "value": "episode" }, { "id": 5, "type": "value", "value": "Nominee" }, { "id": 4, "type": "column", "value": "result" }, { "id": 1, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "award" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 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", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
14,748
food_inspection_2
bird:train.json:6183
How many inspections were done under the display of inspection report summary category?
SELECT COUNT(T2.inspection_id) FROM inspection_point AS T1 INNER JOIN violation AS T2 ON T1.point_id = T2.point_id WHERE T1.category = 'Display of Inspection Report Summary'
[ "How", "many", "inspections", "were", "done", "under", "the", "display", "of", "inspection", "report", "summary", "category", "?" ]
[ { "id": 3, "type": "value", "value": "Display of Inspection Report Summary" }, { "id": 0, "type": "table", "value": "inspection_point" }, { "id": 4, "type": "column", "value": "inspection_id" }, { "id": 1, "type": "table", "value": "violation" }, { "id": 2, "type": "column", "value": "category" }, { "id": 5, "type": "column", "value": "point_id" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 7, 8, 11 ] }, { "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", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "B-TABLE", "B-VALUE", "B-COLUMN", "O" ]
14,749
product_catalog
spider:train_spider.json:341
Name all the products with next entry ID greater than 8.
SELECT catalog_entry_name FROM catalog_contents WHERE next_entry_id > 8
[ "Name", "all", "the", "products", "with", "next", "entry", "ID", "greater", "than", "8", "." ]
[ { "id": 1, "type": "column", "value": "catalog_entry_name" }, { "id": 0, "type": "table", "value": "catalog_contents" }, { "id": 2, "type": "column", "value": "next_entry_id" }, { "id": 3, "type": "value", "value": "8" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5, 6, 7 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "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", "I-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
14,750
car_retails
bird:train.json:1591
For the planes which has the hightest total price, how much it exceeds the average?
SELECT MAX(quantityOrdered * priceEach) - AVG(priceEach) FROM orderdetails WHERE productCode IN ( SELECT productCode FROM products WHERE productLine = 'Planes' )
[ "For", "the", "planes", "which", "has", "the", "hightest", "total", "price", ",", "how", "much", "it", "exceeds", "the", "average", "?" ]
[ { "id": 6, "type": "column", "value": "quantityordered" }, { "id": 0, "type": "table", "value": "orderdetails" }, { "id": 1, "type": "column", "value": "productcode" }, { "id": 4, "type": "column", "value": "productline" }, { "id": 3, "type": "column", "value": "priceeach" }, { "id": 2, "type": "table", "value": "products" }, { "id": 5, "type": "value", "value": "Planes" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "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-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,751
book_1
bird:test.json:584
Return the number of orders received for Pride and Prejudice.
SELECT count(*) FROM Book AS T1 JOIN Books_Order AS T2 ON T1.isbn = T2.isbn WHERE T1.title = "Pride and Prejudice"
[ "Return", "the", "number", "of", "orders", "received", "for", "Pride", "and", "Prejudice", "." ]
[ { "id": 3, "type": "column", "value": "Pride and Prejudice" }, { "id": 1, "type": "table", "value": "books_order" }, { "id": 2, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "book" }, { "id": 4, "type": "column", "value": "isbn" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "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", "O", "B-TABLE", "I-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
14,752
superstore
bird:train.json:2396
List the products that were ordered by Anne McFarland from the Western store.
SELECT DISTINCT T3.`Product Name` FROM west_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T1.`Product ID` WHERE T2.`Customer Name` = 'Anne McFarland'
[ "List", "the", "products", "that", "were", "ordered", "by", "Anne", "McFarland", "from", "the", "Western", "store", "." ]
[ { "id": 4, "type": "table", "value": "west_superstore" }, { "id": 3, "type": "value", "value": "Anne McFarland" }, { "id": 2, "type": "column", "value": "Customer Name" }, { "id": 0, "type": "column", "value": "Product Name" }, { "id": 7, "type": "column", "value": "Customer ID" }, { "id": 6, "type": "column", "value": "Product ID" }, { "id": 1, "type": "table", "value": "product" }, { "id": 5, "type": "table", "value": "people" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7, 8 ] }, { "entity_id": 4, "token_idxs": [ 11, 12 ] }, { "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", "B-VALUE", "I-VALUE", "O", "O", "B-TABLE", "I-TABLE", "O" ]
14,753
dorm_1
spider:train_spider.json:5739
For each dorm, how many amenities does it have?
SELECT count(*) , T1.dormid FROM dorm AS T1 JOIN has_amenity AS T2 ON T1.dormid = T2.dormid WHERE T1.student_capacity > 100 GROUP BY T1.dormid
[ "For", "each", "dorm", ",", "how", "many", "amenities", "does", "it", "have", "?" ]
[ { "id": 3, "type": "column", "value": "student_capacity" }, { "id": 2, "type": "table", "value": "has_amenity" }, { "id": 0, "type": "column", "value": "dormid" }, { "id": 1, "type": "table", "value": "dorm" }, { "id": 4, "type": "value", "value": "100" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "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", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
14,754
music_1
spider:train_spider.json:3597
What are the average rating and resolution of songs that are in Bangla?
SELECT avg(rating) , avg(resolution) FROM song WHERE languages = "bangla"
[ "What", "are", "the", "average", "rating", "and", "resolution", "of", "songs", "that", "are", "in", "Bangla", "?" ]
[ { "id": 4, "type": "column", "value": "resolution" }, { "id": 1, "type": "column", "value": "languages" }, { "id": 2, "type": "column", "value": "bangla" }, { "id": 3, "type": "column", "value": "rating" }, { "id": 0, "type": "table", "value": "song" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "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", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
14,755
california_schools
bird:dev.json:88
What is the administrator's email address for the school with the highest number of test takers who received SAT scores of at least 1500?Provide the name of the school.
SELECT T2.AdmEmail1, T2.School FROM satscores AS T1 INNER JOIN schools AS T2 ON T1.cds = T2.CDSCode ORDER BY T1.NumGE1500 DESC LIMIT 1
[ "What", "is", "the", "administrator", "'s", "email", "address", "for", "the", "school", "with", "the", "highest", "number", "of", "test", "takers", "who", "received", "SAT", "scores", "of", "at", "least", "1500?Provide", "the", "name", "of", "the", "school", "." ]
[ { "id": 0, "type": "column", "value": "admemail1" }, { "id": 2, "type": "table", "value": "satscores" }, { "id": 4, "type": "column", "value": "numge1500" }, { "id": 3, "type": "table", "value": "schools" }, { "id": 6, "type": "column", "value": "cdscode" }, { "id": 1, "type": "column", "value": "school" }, { "id": 5, "type": "column", "value": "cds" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 29 ] }, { "entity_id": 2, "token_idxs": [ 19 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 20 ] }, { "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", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,756
beer_factory
bird:train.json:5233
How many breweries are located in North America?
SELECT COUNT(BrandID) FROM rootbeerbrand WHERE Country = 'United States'
[ "How", "many", "breweries", "are", "located", "in", "North", "America", "?" ]
[ { "id": 0, "type": "table", "value": "rootbeerbrand" }, { "id": 2, "type": "value", "value": "United States" }, { "id": 1, "type": "column", "value": "country" }, { "id": 3, "type": "column", "value": "brandid" } ]
[ { "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" ]
14,757
aan_1
bird:test.json:1052
What are the names of authors who have not published a paper in ACL?
SELECT name FROM Author WHERE author_id NOT IN (SELECT T1.author_id FROM Author_list AS T1 JOIN Paper AS T2 ON T1.paper_id = T2.paper_id WHERE T2.venue = "ACL")
[ "What", "are", "the", "names", "of", "authors", "who", "have", "not", "published", "a", "paper", "in", "ACL", "?" ]
[ { "id": 3, "type": "table", "value": "author_list" }, { "id": 2, "type": "column", "value": "author_id" }, { "id": 7, "type": "column", "value": "paper_id" }, { "id": 0, "type": "table", "value": "author" }, { "id": 4, "type": "table", "value": "paper" }, { "id": 5, "type": "column", "value": "venue" }, { "id": 1, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "ACL" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 13 ] }, { "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-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O" ]
14,758
human_resources
bird:train.json:8987
Write down the full name, performance status and located city of the employee who's social security number is "767-74-7373".
SELECT T1.firstname, T1.lastname, T2.state, T2.locationcity FROM employee AS T1 INNER JOIN location AS T2 ON T1.locationID = T2.locationID WHERE T1.ssn = '767-74-7373'
[ "Write", "down", "the", "full", "name", ",", "performance", "status", "and", "located", "city", "of", "the", "employee", "who", "'s", "social", "security", "number", "is", "\"", "767", "-", "74", "-", "7373", "\"", "." ]
[ { "id": 3, "type": "column", "value": "locationcity" }, { "id": 7, "type": "value", "value": "767-74-7373" }, { "id": 8, "type": "column", "value": "locationid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 4, "type": "table", "value": "employee" }, { "id": 5, "type": "table", "value": "location" }, { "id": 2, "type": "column", "value": "state" }, { "id": 6, "type": "column", "value": "ssn" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 21, 22, 23, 24, 25 ] }, { "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", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
14,759
shakespeare
bird:train.json:3020
What is the title which has character named "Froth"?
SELECT DISTINCT T1.title FROM works AS T1 INNER JOIN chapters AS T2 ON T1.id = T2.work_id INNER JOIN paragraphs AS T3 ON T2.id = T3.chapter_id INNER JOIN characters AS T4 ON T3.character_id = T4.id WHERE T4.CharName = 'Froth'
[ "What", "is", "the", "title", "which", "has", "character", "named", "\"", "Froth", "\"", "?" ]
[ { "id": 5, "type": "column", "value": "character_id" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 4, "type": "table", "value": "paragraphs" }, { "id": 9, "type": "column", "value": "chapter_id" }, { "id": 2, "type": "column", "value": "charname" }, { "id": 8, "type": "table", "value": "chapters" }, { "id": 10, "type": "column", "value": "work_id" }, { "id": 0, "type": "column", "value": "title" }, { "id": 3, "type": "value", "value": "Froth" }, { "id": 7, "type": "table", "value": "works" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O" ]
14,760
card_games
bird:dev.json:475
How many cards in the set Coldsnap have a black border color?
SELECT SUM(CASE WHEN T1.borderColor = 'black' THEN 1 ELSE 0 END) FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE T2.name = 'Coldsnap'
[ "How", "many", "cards", "in", "the", "set", "Coldsnap", "have", "a", "black", "border", "color", "?" ]
[ { "id": 8, "type": "column", "value": "bordercolor" }, { "id": 3, "type": "value", "value": "Coldsnap" }, { "id": 5, "type": "column", "value": "setcode" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 9, "type": "value", "value": "black" }, { "id": 1, "type": "table", "value": "sets" }, { "id": 2, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "code" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "B-COLUMN", "B-COLUMN", "O" ]
14,761
mondial_geo
bird:train.json:8228
Provide the country with republic government which has the highest population growth?
SELECT T2.Country FROM population AS T1 INNER JOIN politics AS T2 ON T1.Country = T2.Country WHERE T2.Government = 'republic' ORDER BY T1.Population_Growth DESC LIMIT 1
[ "Provide", "the", "country", "with", "republic", "government", "which", "has", "the", "highest", "population", "growth", "?" ]
[ { "id": 5, "type": "column", "value": "population_growth" }, { "id": 1, "type": "table", "value": "population" }, { "id": 3, "type": "column", "value": "government" }, { "id": 2, "type": "table", "value": "politics" }, { "id": 4, "type": "value", "value": "republic" }, { "id": 0, "type": "column", "value": "country" } ]
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[ "O", "O", "B-COLUMN", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
14,762
movie_3
bird:train.json:9105
Please list the titles of the films that are released in 2006 and have a rental rate of $2.99.
SELECT title FROM film WHERE release_year = 2006 AND rental_rate = 2.99
[ "Please", "list", "the", "titles", "of", "the", "films", "that", "are", "released", "in", "2006", "and", "have", "a", "rental", "rate", "of", "$", "2.99", "." ]
[ { "id": 2, "type": "column", "value": "release_year" }, { "id": 4, "type": "column", "value": "rental_rate" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "film" }, { "id": 3, "type": "value", "value": "2006" }, { "id": 5, "type": "value", "value": "2.99" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
14,763
sakila_1
spider:train_spider.json:2951
What are the title, id, and description of the movie with the greatest number of actors?
SELECT T2.title , T2.film_id , T2.description FROM film_actor AS T1 JOIN film AS T2 ON T1.film_id = T2.film_id GROUP BY T2.film_id ORDER BY count(*) DESC LIMIT 1
[ "What", "are", "the", "title", ",", "i", "d", ",", "and", "description", "of", "the", "movie", "with", "the", "greatest", "number", "of", "actors", "?" ]
[ { "id": 2, "type": "column", "value": "description" }, { "id": 3, "type": "table", "value": "film_actor" }, { "id": 0, "type": "column", "value": "film_id" }, { "id": 1, "type": "column", "value": "title" }, { "id": 4, "type": "table", "value": "film" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
14,765
public_review_platform
bird:train.json:3972
Between 2006 and 2007, which year ID had the greater number in elite user?
SELECT year_id FROM Elite WHERE year_id IN (2006, 2007) GROUP BY year_id ORDER BY COUNT(user_id) DESC LIMIT 1
[ "Between", "2006", "and", "2007", ",", "which", "year", "ID", "had", "the", "greater", "number", "in", "elite", "user", "?" ]
[ { "id": 1, "type": "column", "value": "year_id" }, { "id": 4, "type": "column", "value": "user_id" }, { "id": 0, "type": "table", "value": "elite" }, { "id": 2, "type": "value", "value": "2006" }, { "id": 3, "type": "value", "value": "2007" } ]
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[ "O", "B-VALUE", "O", "B-VALUE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
14,766
baseball_1
spider:train_spider.json:3701
Which team had the least number of attendances in home games in 1980?
SELECT T2.name FROM home_game AS T1 JOIN team AS T2 ON T1.team_id = T2.team_id_br WHERE T1.year = 1980 ORDER BY T1.attendance ASC LIMIT 1;
[ "Which", "team", "had", "the", "least", "number", "of", "attendances", "in", "home", "games", "in", "1980", "?" ]
[ { "id": 5, "type": "column", "value": "attendance" }, { "id": 7, "type": "column", "value": "team_id_br" }, { "id": 1, "type": "table", "value": "home_game" }, { "id": 6, "type": "column", "value": "team_id" }, { "id": 0, "type": "column", "value": "name" }, { "id": 2, "type": "table", "value": "team" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "1980" } ]
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[ "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
14,767
public_review_platform
bird:train.json:4133
List the categories of active businesses in Glendale, AZ.
SELECT DISTINCT T3.category_name FROM Business_Categories AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id INNER JOIN Categories AS T3 ON T1.category_id = T3.category_id WHERE T2.active = 'true' AND T2.state = 'AZ' AND T2.city = 'Glendale'
[ "List", "the", "categories", "of", "active", "businesses", "in", "Glendale", ",", "AZ", "." ]
[ { "id": 2, "type": "table", "value": "business_categories" }, { "id": 0, "type": "column", "value": "category_name" }, { "id": 4, "type": "column", "value": "category_id" }, { "id": 11, "type": "column", "value": "business_id" }, { "id": 1, "type": "table", "value": "categories" }, { "id": 3, "type": "table", "value": "business" }, { "id": 10, "type": "value", "value": "Glendale" }, { "id": 5, "type": "column", "value": "active" }, { "id": 7, "type": "column", "value": "state" }, { "id": 6, "type": "value", "value": "true" }, { "id": 9, "type": "column", "value": "city" }, { "id": 8, "type": "value", "value": "AZ" } ]
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[ "B-COLUMN", "I-COLUMN", "B-TABLE", "O", "B-COLUMN", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
14,768
computer_student
bird:train.json:974
Name the advisors for students in Year 3 of the program.
SELECT T1.p_id FROM advisedBy AS T1 INNER JOIN person AS T2 ON T1.p_id = T2.p_id WHERE T2.yearsInProgram = 'Year_3'
[ "Name", "the", "advisors", "for", "students", "in", "Year", "3", "of", "the", "program", "." ]
[ { "id": 3, "type": "column", "value": "yearsinprogram" }, { "id": 1, "type": "table", "value": "advisedby" }, { "id": 2, "type": "table", "value": "person" }, { "id": 4, "type": "value", "value": "Year_3" }, { "id": 0, "type": "column", "value": "p_id" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "B-COLUMN", "O" ]
14,770
customers_campaigns_ecommerce
spider:train_spider.json:4623
Show each premise type and the number of premises in that type.
SELECT premises_type , count(*) FROM premises GROUP BY premises_type
[ "Show", "each", "premise", "type", "and", "the", "number", "of", "premises", "in", "that", "type", "." ]
[ { "id": 1, "type": "column", "value": "premises_type" }, { "id": 0, "type": "table", "value": "premises" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 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", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
14,771
flight_company
spider:train_spider.json:6376
What are the different pilot names who had piloted a flight in the country 'United States' or in the airport named 'Billund Airport'?
SELECT DISTINCT T2.pilot FROM airport AS T1 JOIN flight AS T2 ON T1.id = T2.airport_id WHERE T1.country = 'United States' OR T1.name = 'Billund Airport'
[ "What", "are", "the", "different", "pilot", "names", "who", "had", "piloted", "a", "flight", "in", "the", "country", "'", "United", "States", "'", "or", "in", "the", "airport", "named", "'", "Billund", "Airport", "'", "?" ]
[ { "id": 8, "type": "value", "value": "Billund Airport" }, { "id": 6, "type": "value", "value": "United States" }, { "id": 4, "type": "column", "value": "airport_id" }, { "id": 1, "type": "table", "value": "airport" }, { "id": 5, "type": "column", "value": "country" }, { "id": 2, "type": "table", "value": "flight" }, { "id": 0, "type": "column", "value": "pilot" }, { "id": 7, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "O" ]
14,772
toxicology
bird:dev.json:324
Find the percentage of atoms with single bond.
SELECT CAST(COUNT(CASE WHEN T.bond_type = '-' THEN T.bond_id ELSE NULL END) AS REAL) * 100 / COUNT(T.bond_id) FROM bond t
[ "Find", "the", "percentage", "of", "atoms", "with", "single", "bond", "." ]
[ { "id": 3, "type": "column", "value": "bond_type" }, { "id": 2, "type": "column", "value": "bond_id" }, { "id": 0, "type": "table", "value": "bond" }, { "id": 1, "type": "value", "value": "100" }, { "id": 4, "type": "value", "value": "-" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,773
news_report
spider:train_spider.json:2812
Show the names of journalists and the dates of the events they reported.
SELECT T3.Name , T2.Date FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID
[ "Show", "the", "names", "of", "journalists", "and", "the", "dates", "of", "the", "events", "they", "reported", "." ]
[ { "id": 5, "type": "column", "value": "journalist_id" }, { "id": 3, "type": "table", "value": "news_report" }, { "id": 2, "type": "table", "value": "journalist" }, { "id": 6, "type": "column", "value": "event_id" }, { "id": 4, "type": "table", "value": "event" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "column", "value": "date" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "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", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-TABLE", "O" ]
14,774
olympics
bird:train.json:5016
Which region has the most athletes?
SELECT T2.region_name FROM person_region AS T1 INNER JOIN noc_region AS T2 ON T1.region_id = T2.id GROUP BY T2.region_name ORDER BY COUNT(T1.person_id) DESC LIMIT 1
[ "Which", "region", "has", "the", "most", "athletes", "?" ]
[ { "id": 1, "type": "table", "value": "person_region" }, { "id": 0, "type": "column", "value": "region_name" }, { "id": 2, "type": "table", "value": "noc_region" }, { "id": 3, "type": "column", "value": "region_id" }, { "id": 5, "type": "column", "value": "person_id" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 1 ] }, { "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", "O" ]