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11,452
computer_student
bird:train.json:1003
List down all the person IDs who taught course ID of 18.
SELECT p_id FROM taughtBy WHERE course_id = 18
[ "List", "down", "all", "the", "person", "IDs", "who", "taught", "course", "ID", "of", "18", "." ]
[ { "id": 2, "type": "column", "value": "course_id" }, { "id": 0, "type": "table", "value": "taughtby" }, { "id": 1, "type": "column", "value": "p_id" }, { "id": 3, "type": "value", "value": "18" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "O" ]
11,453
film_rank
spider:train_spider.json:4124
How many markets have number of cities smaller than 300?
SELECT count(*) FROM market WHERE Number_cities < 300
[ "How", "many", "markets", "have", "number", "of", "cities", "smaller", "than", "300", "?" ]
[ { "id": 1, "type": "column", "value": "number_cities" }, { "id": 0, "type": "table", "value": "market" }, { "id": 2, "type": "value", "value": "300" } ]
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[ "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
11,454
hockey
bird:train.json:7658
Please list the awards the coaches who are born in Canada have won.
SELECT DISTINCT T2.award FROM Master AS T1 INNER JOIN AwardsCoaches AS T2 ON T1.coachID = T2.coachID WHERE T1.birthCountry = 'Canada'
[ "Please", "list", "the", "awards", "the", "coaches", "who", "are", "born", "in", "Canada", "have", "won", "." ]
[ { "id": 2, "type": "table", "value": "awardscoaches" }, { "id": 3, "type": "column", "value": "birthcountry" }, { "id": 5, "type": "column", "value": "coachid" }, { "id": 1, "type": "table", "value": "master" }, { "id": 4, "type": "value", ...
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[ "O", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
11,455
art_1
bird:test.json:1259
What is the id of the oldest painting?
SELECT paintingID FROM paintings ORDER BY YEAR LIMIT 1
[ "What", "is", "the", "i", "d", "of", "the", "oldest", "painting", "?" ]
[ { "id": 1, "type": "column", "value": "paintingid" }, { "id": 0, "type": "table", "value": "paintings" }, { "id": 2, "type": "column", "value": "year" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
11,456
city_record
spider:train_spider.json:6291
Which cities have lower temperature in March than in July and have been once host cities?
SELECT T1.city FROM city AS T1 JOIN temperature AS T2 ON T1.city_id = T2.city_id WHERE T2.Mar < T2.Jul INTERSECT SELECT T3.city FROM city AS T3 JOIN hosting_city AS T4 ON T3.city_id = T4.host_city
[ "Which", "cities", "have", "lower", "temperature", "in", "March", "than", "in", "July", "and", "have", "been", "once", "host", "cities", "?" ]
[ { "id": 5, "type": "table", "value": "hosting_city" }, { "id": 2, "type": "table", "value": "temperature" }, { "id": 7, "type": "column", "value": "host_city" }, { "id": 6, "type": "column", "value": "city_id" }, { "id": 0, "type": "column", ...
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11,457
image_and_language
bird:train.json:7566
Calculate the average of object samples for the image.
SELECT CAST(COUNT(OBJ_SAMPLE_ID) AS REAL) / COUNT(DISTINCT IMG_ID) FROM IMG_OBJ
[ "Calculate", "the", "average", "of", "object", "samples", "for", "the", "image", "." ]
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[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
11,458
bike_1
spider:train_spider.json:164
What is the id of the trip that started from the station with the highest dock count?
SELECT T1.id FROM trip AS T1 JOIN station AS T2 ON T1.start_station_id = T2.id ORDER BY T2.dock_count DESC LIMIT 1
[ "What", "is", "the", "i", "d", "of", "the", "trip", "that", "started", "from", "the", "station", "with", "the", "highest", "dock", "count", "?" ]
[ { "id": 4, "type": "column", "value": "start_station_id" }, { "id": 3, "type": "column", "value": "dock_count" }, { "id": 2, "type": "table", "value": "station" }, { "id": 1, "type": "table", "value": "trip" }, { "id": 0, "type": "column", ...
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
11,459
wrestler
spider:train_spider.json:1881
How many different teams have had eliminated wrestlers?
SELECT COUNT (DISTINCT team) FROM elimination
[ "How", "many", "different", "teams", "have", "had", "eliminated", "wrestlers", "?" ]
[ { "id": 0, "type": "table", "value": "elimination" }, { "id": 1, "type": "column", "value": "team" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O" ]
11,460
program_share
spider:train_spider.json:3757
What is the list of program origins ordered alphabetically?
SELECT origin FROM program ORDER BY origin
[ "What", "is", "the", "list", "of", "program", "origins", "ordered", "alphabetically", "?" ]
[ { "id": 0, "type": "table", "value": "program" }, { "id": 1, "type": "column", "value": "origin" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O" ]
11,461
bike_1
spider:train_spider.json:180
What are the ids and names of all start stations that were the beginning of at least 200 trips?
SELECT start_station_id , start_station_name FROM trip GROUP BY start_station_name HAVING COUNT(*) >= 200
[ "What", "are", "the", "ids", "and", "names", "of", "all", "start", "stations", "that", "were", "the", "beginning", "of", "at", "least", "200", "trips", "?" ]
[ { "id": 1, "type": "column", "value": "start_station_name" }, { "id": 2, "type": "column", "value": "start_station_id" }, { "id": 0, "type": "table", "value": "trip" }, { "id": 3, "type": "value", "value": "200" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
11,462
sports_competition
spider:train_spider.json:3386
What are the countries that participated in both friendly and tournament type competitions?
SELECT country FROM competition WHERE competition_type = 'Friendly' INTERSECT SELECT country FROM competition WHERE competition_type = 'Tournament'
[ "What", "are", "the", "countries", "that", "participated", "in", "both", "friendly", "and", "tournament", "type", "competitions", "?" ]
[ { "id": 2, "type": "column", "value": "competition_type" }, { "id": 0, "type": "table", "value": "competition" }, { "id": 4, "type": "value", "value": "Tournament" }, { "id": 3, "type": "value", "value": "Friendly" }, { "id": 1, "type": "column...
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "B-TABLE", "O" ]
11,463
toxicology
bird:dev.json:249
What are the elements of the atoms of TR144_8_19?
SELECT T2.element FROM connected AS T1 INNER JOIN atom AS T2 ON T1.atom_id = T2.atom_id WHERE T1.bond_id = 'TR144_8_19'
[ "What", "are", "the", "elements", "of", "the", "atoms", "of", "TR144_8_19", "?" ]
[ { "id": 4, "type": "value", "value": "TR144_8_19" }, { "id": 1, "type": "table", "value": "connected" }, { "id": 0, "type": "column", "value": "element" }, { "id": 3, "type": "column", "value": "bond_id" }, { "id": 5, "type": "column", "val...
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
11,464
real_estate_rentals
bird:test.json:1407
What is the lowest room count across all the properties?
SELECT min(room_count) FROM Properties;
[ "What", "is", "the", "lowest", "room", "count", "across", "all", "the", "properties", "?" ]
[ { "id": 0, "type": "table", "value": "properties" }, { "id": 1, "type": "column", "value": "room_count" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
11,465
sales
bird:train.json:5368
List down product names of free gifts.
SELECT Name FROM Products WHERE Price = 0
[ "List", "down", "product", "names", "of", "free", "gifts", "." ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O" ]
11,466
ice_hockey_draft
bird:train.json:6928
What is the average height in centimeters of all the players in the position of defense?
SELECT CAST(SUM(T2.height_in_cm) AS REAL) / COUNT(T1.ELITEID) FROM PlayerInfo AS T1 INNER JOIN height_info AS T2 ON T1.height = T2.height_id WHERE T1.position_info = 'D'
[ "What", "is", "the", "average", "height", "in", "centimeters", "of", "all", "the", "players", "in", "the", "position", "of", "defense", "?" ]
[ { "id": 2, "type": "column", "value": "position_info" }, { "id": 7, "type": "column", "value": "height_in_cm" }, { "id": 1, "type": "table", "value": "height_info" }, { "id": 0, "type": "table", "value": "playerinfo" }, { "id": 5, "type": "colu...
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11,467
financial
bird:dev.json:175
How many accounts have an owner disposition and request for a statement to be generated upon a transaction?
SELECT COUNT(T1.account_id) FROM account AS T1 INNER JOIN disp AS T2 ON T1.account_id = T2.account_id WHERE T2.type = 'OWNER' AND T1.frequency = 'POPLATEK PO OBRATU'
[ "How", "many", "accounts", "have", "an", "owner", "disposition", "and", "request", "for", "a", "statement", "to", "be", "generated", "upon", "a", "transaction", "?" ]
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11,468
coinmarketcap
bird:train.json:6289
When did Peercoin rank fifth?
SELECT T2.date FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'Peercoin' AND T2.cmc_rank = 5
[ "When", "did", "Peercoin", "rank", "fifth", "?" ]
[ { "id": 2, "type": "table", "value": "historical" }, { "id": 6, "type": "value", "value": "Peercoin" }, { "id": 7, "type": "column", "value": "cmc_rank" }, { "id": 4, "type": "column", "value": "coin_id" }, { "id": 1, "type": "table", "valu...
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[ "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O" ]
11,469
party_people
spider:train_spider.json:2079
find the event names that have more than 2 records.
SELECT event_name FROM party_events GROUP BY event_name HAVING count(*) > 2
[ "find", "the", "event", "names", "that", "have", "more", "than", "2", "records", "." ]
[ { "id": 0, "type": "table", "value": "party_events" }, { "id": 1, "type": "column", "value": "event_name" }, { "id": 2, "type": "value", "value": "2" } ]
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11,470
election
spider:train_spider.json:2797
Which parties did not have any delegates in elections?
SELECT Party FROM party WHERE Party_ID NOT IN (SELECT Party FROM election)
[ "Which", "parties", "did", "not", "have", "any", "delegates", "in", "elections", "?" ]
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[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
11,471
voter_2
spider:train_spider.json:5483
What are the first and last names of all the female students who have president votes?
SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.President_VOTE WHERE T1.sex = "F"
[ "What", "are", "the", "first", "and", "last", "names", "of", "all", "the", "female", "students", "who", "have", "president", "votes", "?" ]
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11,472
cookbook
bird:train.json:8901
Among the recipes whose source is the National Potato Board, which recipe has the highest calories?
SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.source = 'National Potato Board' ORDER BY T2.calories DESC LIMIT 1
[ "Among", "the", "recipes", "whose", "source", "is", "the", "National", "Potato", "Board", ",", "which", "recipe", "has", "the", "highest", "calories", "?" ]
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11,473
shop_membership
spider:train_spider.json:5439
What are the total purchases for members rated at level 6?
SELECT count(*) FROM purchase AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T2.level = 6
[ "What", "are", "the", "total", "purchases", "for", "members", "rated", "at", "level", "6", "?" ]
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11,474
chinook_1
spider:train_spider.json:833
Show the album names, ids and the number of tracks for each album.
SELECT T1.Title , T2.AlbumID , COUNT(*) FROM ALBUM AS T1 JOIN TRACK AS T2 ON T1.AlbumId = T2.AlbumId GROUP BY T2.AlbumID
[ "Show", "the", "album", "names", ",", "ids", "and", "the", "number", "of", "tracks", "for", "each", "album", "." ]
[ { "id": 0, "type": "column", "value": "albumid" }, { "id": 1, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "album" }, { "id": 3, "type": "table", "value": "track" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs"...
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
11,475
computer_student
bird:train.json:985
Which course has more teachers, course no.16 or course no.18?
SELECT course_id FROM taughtBy WHERE course_id = 11 OR course_id = 18 GROUP BY course_id ORDER BY COUNT(course_id) DESC LIMIT 1
[ "Which", "course", "has", "more", "teachers", ",", "course", "no.16", "or", "course", "no.18", "?" ]
[ { "id": 1, "type": "column", "value": "course_id" }, { "id": 0, "type": "table", "value": "taughtby" }, { "id": 2, "type": "value", "value": "11" }, { "id": 3, "type": "value", "value": "18" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
11,476
product_catalog
spider:train_spider.json:306
Find the attribute data type for the attribute named "Green".
SELECT attribute_data_type FROM Attribute_Definitions WHERE attribute_name = "Green"
[ "Find", "the", "attribute", "data", "type", "for", "the", "attribute", "named", "\"", "Green", "\"", "." ]
[ { "id": 0, "type": "table", "value": "attribute_definitions" }, { "id": 1, "type": "column", "value": "attribute_data_type" }, { "id": 2, "type": "column", "value": "attribute_name" }, { "id": 3, "type": "column", "value": "Green" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 7, 8 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, ...
[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O" ]
11,477
music_platform_2
bird:train.json:7982
How many reviews are created for the podcast "Scaling Global" under?
SELECT COUNT(T2.content) FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T1.title = 'Scaling Global'
[ "How", "many", "reviews", "are", "created", "for", "the", "podcast", "\"", "Scaling", "Global", "\"", "under", "?" ]
[ { "id": 3, "type": "value", "value": "Scaling Global" }, { "id": 5, "type": "column", "value": "podcast_id" }, { "id": 0, "type": "table", "value": "podcasts" }, { "id": 1, "type": "table", "value": "reviews" }, { "id": 4, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id"...
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O", "O" ]
11,478
food_inspection_2
bird:train.json:6169
What is the inspection ID of the inspection with critical point level, $500 fine, and inspector comment "CDI ON 5-17-10"?
SELECT T2.inspection_id FROM inspection_point AS T1 INNER JOIN violation AS T2 ON T1.point_id = T2.point_id WHERE T2.fine = 500 AND T1.point_level = 'Critical' AND T2.inspector_comment = 'CDI ON 5-17-10'
[ "What", "is", "the", "inspection", "ID", "of", "the", "inspection", "with", "critical", "point", "level", ",", "$", "500", "fine", ",", "and", "inspector", "comment", "\"", "CDI", "ON", "5", "-", "17", "-", "10", "\"", "?" ]
[ { "id": 8, "type": "column", "value": "inspector_comment" }, { "id": 1, "type": "table", "value": "inspection_point" }, { "id": 9, "type": "value", "value": "CDI ON 5-17-10" }, { "id": 0, "type": "column", "value": "inspection_id" }, { "id": 6, ...
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { ...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "B-COLUMN", "B-COLUMN", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ...
11,479
books
bird:train.json:6049
Provide the full address of Ursola Purdy.
SELECT T3.street_number, T3.street_name, T3.city FROM customer AS T1 INNER JOIN customer_address AS T2 ON T1.customer_id = T2.customer_id INNER JOIN address AS T3 ON T3.address_id = T2.address_id INNER JOIN country AS T4 ON T4.country_id = T3.country_id WHERE T1.first_name = 'Ursola' AND T1.last_name = 'Purdy'
[ "Provide", "the", "full", "address", "of", "Ursola", "Purdy", "." ]
[ { "id": 11, "type": "table", "value": "customer_address" }, { "id": 0, "type": "column", "value": "street_number" }, { "id": 1, "type": "column", "value": "street_name" }, { "id": 13, "type": "column", "value": "customer_id" }, { "id": 5, "type...
[ { "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": [ 3 ] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "O", "B-TABLE", "O", "B-VALUE", "B-VALUE", "O" ]
11,480
works_cycles
bird:train.json:7384
Which department has the most number of night shifts?
SELECT T3.Name FROM Shift AS T1 INNER JOIN EmployeeDepartmentHistory AS T2 ON T1.ShiftId = T2.ShiftId INNER JOIN Department AS T3 ON T2.DepartmentID = T3.DepartmentID GROUP BY T2.DepartmentID ORDER BY COUNT(T1.Name = 'Night') DESC LIMIT 1
[ "Which", "department", "has", "the", "most", "number", "of", "night", "shifts", "?" ]
[ { "id": 4, "type": "table", "value": "employeedepartmenthistory" }, { "id": 0, "type": "column", "value": "departmentid" }, { "id": 2, "type": "table", "value": "department" }, { "id": 5, "type": "column", "value": "shiftid" }, { "id": 3, "type...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 1 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_...
[ "O", "B-TABLE", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "O" ]
11,481
soccer_3
bird:test.json:0
How many clubs are there?
SELECT count(*) FROM club
[ "How", "many", "clubs", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "club" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "B-TABLE", "O", "O", "O" ]
11,482
art_1
bird:test.json:1291
Find the average height and width of paintings grouped by painters and ordered by name
SELECT avg(height_mm) , avg(width_mm) , painterID FROM paintings GROUP BY painterID ORDER BY title
[ "Find", "the", "average", "height", "and", "width", "of", "paintings", "grouped", "by", "painters", "and", "ordered", "by", "name" ]
[ { "id": 0, "type": "table", "value": "paintings" }, { "id": 1, "type": "column", "value": "painterid" }, { "id": 3, "type": "column", "value": "height_mm" }, { "id": 4, "type": "column", "value": "width_mm" }, { "id": 2, "type": "column", "...
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity...
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
11,483
hospital_1
spider:train_spider.json:3943
Which physicians prescribe a medication of brand X? Tell me the name and position of those physicians.
SELECT DISTINCT T1.name , T1.position FROM physician AS T1 JOIN prescribes AS T2 ON T1.employeeid = T2.physician JOIN medication AS T3 ON T3.code = T2.medication WHERE T3.Brand = "X"
[ "Which", "physicians", "prescribe", "a", "medication", "of", "brand", "X", "?", "Tell", "me", "the", "name", "and", "position", "of", "those", "physicians", "." ]
[ { "id": 2, "type": "table", "value": "medication" }, { "id": 6, "type": "table", "value": "prescribes" }, { "id": 8, "type": "column", "value": "medication" }, { "id": 9, "type": "column", "value": "employeeid" }, { "id": 5, "type": "table", ...
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entit...
[ "O", "B-COLUMN", "B-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O" ]
11,484
driving_school
spider:train_spider.json:6711
What are the last names that are used by customers and staff?
SELECT last_name FROM Customers INTERSECT SELECT last_name FROM Staff
[ "What", "are", "the", "last", "names", "that", "are", "used", "by", "customers", "and", "staff", "?" ]
[ { "id": 0, "type": "table", "value": "customers" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 1, "type": "table", "value": "staff" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id"...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O" ]
11,485
college_2
spider:train_spider.json:1331
What is the department name and corresponding building for the department with the greatest budget?
SELECT dept_name , building FROM department ORDER BY budget DESC LIMIT 1
[ "What", "is", "the", "department", "name", "and", "corresponding", "building", "for", "the", "department", "with", "the", "greatest", "budget", "?" ]
[ { "id": 0, "type": "table", "value": "department" }, { "id": 1, "type": "column", "value": "dept_name" }, { "id": 2, "type": "column", "value": "building" }, { "id": 3, "type": "column", "value": "budget" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { ...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
11,486
sing_contest
bird:test.json:747
What are the names and original artists of the song whose English translation is 'All the streets of love'?
SELECT name , original_artist FROM songs WHERE english_translation = 'All the streets of love'
[ "What", "are", "the", "names", "and", "original", "artists", "of", "the", "song", "whose", "English", "translation", "is", "'", "All", "the", "streets", "of", "love", "'", "?" ]
[ { "id": 4, "type": "value", "value": "All the streets of love" }, { "id": 3, "type": "column", "value": "english_translation" }, { "id": 2, "type": "column", "value": "original_artist" }, { "id": 0, "type": "table", "value": "songs" }, { "id": 1, ...
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 11, 12 ] }, { "entity_id": 4, "token_idxs": [ ...
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
11,487
debit_card_specializing
bird:dev.json:1486
Is it true that more SMEs pay in Czech koruna than in euros? If so, how many more?
SELECT SUM(Currency = 'CZK') - SUM(Currency = 'EUR') FROM customers WHERE Segment = 'SME'
[ "Is", "it", "true", "that", "more", "SMEs", "pay", "in", "Czech", "koruna", "than", "in", "euros", "?", "If", "so", ",", "how", "many", "more", "?" ]
[ { "id": 0, "type": "table", "value": "customers" }, { "id": 3, "type": "column", "value": "currency" }, { "id": 1, "type": "column", "value": "segment" }, { "id": 2, "type": "value", "value": "SME" }, { "id": 4, "type": "value", "value": "C...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 12 ...
[ "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,488
bakery_1
bird:test.json:1542
Order the distinct good ids.
SELECT DISTINCT id FROM goods ORDER BY id
[ "Order", "the", "distinct", "good", "ids", "." ]
[ { "id": 0, "type": "table", "value": "goods" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": ...
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
11,491
customers_and_addresses
spider:train_spider.json:6058
Return the total number of distinct customers.
SELECT count(*) FROM customers
[ "Return", "the", "total", "number", "of", "distinct", "customers", "." ]
[ { "id": 0, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "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": [] }, { ...
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
11,492
retail_complains
bird:train.json:268
For the client who made the complaint call "CR0217298", what was his/her birthday?
SELECT T1.month, T1.day FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Complaint ID` = 'CR0217298'
[ "For", "the", "client", "who", "made", "the", "complaint", "call", "\"", "CR0217298", "\"", ",", "what", "was", "his", "/", "her", "birthday", "?" ]
[ { "id": 4, "type": "column", "value": "Complaint ID" }, { "id": 5, "type": "value", "value": "CR0217298" }, { "id": 6, "type": "column", "value": "client_id" }, { "id": 2, "type": "table", "value": "client" }, { "id": 3, "type": "table", "v...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": ...
[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,493
music_platform_2
bird:train.json:7962
What is the category and itune url of the title "Scaling Global"?
SELECT T1.category, T2.itunes_url FROM categories AS T1 INNER JOIN podcasts AS T2 ON T2.podcast_id = T1.podcast_id WHERE T2.title = 'Scaling Global'
[ "What", "is", "the", "category", "and", "itune", "url", "of", "the", "title", "\"", "Scaling", "Global", "\"", "?" ]
[ { "id": 5, "type": "value", "value": "Scaling Global" }, { "id": 1, "type": "column", "value": "itunes_url" }, { "id": 2, "type": "table", "value": "categories" }, { "id": 6, "type": "column", "value": "podcast_id" }, { "id": 0, "type": "column...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id":...
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O" ]
11,494
authors
bird:train.json:3580
What is the full name of the journals that are published in the database papers whose topic is Sustainability?
SELECT T2.FullName FROM Paper AS T1 INNER JOIN Journal AS T2 ON T1.JournalId = T2.Id WHERE T1.Keyword = 'Sustainability'
[ "What", "is", "the", "full", "name", "of", "the", "journals", "that", "are", "published", "in", "the", "database", "papers", "whose", "topic", "is", "Sustainability", "?" ]
[ { "id": 4, "type": "value", "value": "Sustainability" }, { "id": 5, "type": "column", "value": "journalid" }, { "id": 0, "type": "column", "value": "fullname" }, { "id": 2, "type": "table", "value": "journal" }, { "id": 3, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 18 ] }, { ...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
11,495
phone_market
spider:train_spider.json:1980
What are the memories and carriers of phones?
SELECT Memory_in_G , Carrier FROM phone
[ "What", "are", "the", "memories", "and", "carriers", "of", "phones", "?" ]
[ { "id": 1, "type": "column", "value": "memory_in_g" }, { "id": 2, "type": "column", "value": "carrier" }, { "id": 0, "type": "table", "value": "phone" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "...
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
11,496
customers_card_transactions
spider:train_spider.json:746
What are the different account ids that have made financial transactions, as well as how many transactions correspond to each?
SELECT account_id , count(*) FROM Financial_transactions GROUP BY account_id
[ "What", "are", "the", "different", "account", "ids", "that", "have", "made", "financial", "transactions", ",", "as", "well", "as", "how", "many", "transactions", "correspond", "to", "each", "?" ]
[ { "id": 0, "type": "table", "value": "financial_transactions" }, { "id": 1, "type": "column", "value": "account_id" } ]
[ { "entity_id": 0, "token_idxs": [ 9, 10 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5,...
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,497
movie_platform
bird:train.json:71
What's the url of user 39115684's rating on the movie 'When Will I Be Loved'?
SELECT T1.rating_url FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_title = 'A Way of Life' AND T1.user_id = 39115684
[ "What", "'s", "the", "url", "of", "user", "39115684", "'s", "rating", "on", "the", "movie", "'", "When", "Will", "I", "Be", "Loved", "'", "?" ]
[ { "id": 5, "type": "value", "value": "A Way of Life" }, { "id": 4, "type": "column", "value": "movie_title" }, { "id": 0, "type": "column", "value": "rating_url" }, { "id": 3, "type": "column", "value": "movie_id" }, { "id": 7, "type": "value",...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs":...
[ "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,499
online_exams
bird:test.json:208
Sort the student answer texts in descending order of their frequency of occurrence.
SELECT Student_Answer_Text FROM Student_Answers GROUP BY Student_Answer_Text ORDER BY COUNT(*) DESC
[ "Sort", "the", "student", "answer", "texts", "in", "descending", "order", "of", "their", "frequency", "of", "occurrence", "." ]
[ { "id": 1, "type": "column", "value": "student_answer_text" }, { "id": 0, "type": "table", "value": "student_answers" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "toke...
[ "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,500
retail_world
bird:train.json:6509
How many orders were from Hanna Moos company in 1999?
SELECT COUNT(T2.OrderID) FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE STRFTIME('%Y', T2.OrderDate) = '1999' AND T1.CompanyName = 'Hanna Moos'
[ "How", "many", "orders", "were", "from", "Hanna", "Moos", "company", "in", "1999", "?" ]
[ { "id": 5, "type": "column", "value": "companyname" }, { "id": 3, "type": "column", "value": "customerid" }, { "id": 6, "type": "value", "value": "Hanna Moos" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 8, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": ...
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]
11,501
college_2
spider:train_spider.json:1488
Find names of instructors with salary greater than that of some (at least one) instructor in the Biology department.
SELECT name FROM instructor WHERE salary > (SELECT min(salary) FROM instructor WHERE dept_name = 'Biology')
[ "Find", "names", "of", "instructors", "with", "salary", "greater", "than", "that", "of", "some", "(", "at", "least", "one", ")", "instructor", "in", "the", "Biology", "department", "." ]
[ { "id": 0, "type": "table", "value": "instructor" }, { "id": 3, "type": "column", "value": "dept_name" }, { "id": 4, "type": "value", "value": "Biology" }, { "id": 2, "type": "column", "value": "salary" }, { "id": 1, "type": "column", "valu...
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[ "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
11,502
professional_basketball
bird:train.json:2821
Please list the name of the coach who has served more than 2 NBA teams.
SELECT coachID FROM coaches GROUP BY coachID HAVING COUNT(DISTINCT tmID) > 2
[ "Please", "list", "the", "name", "of", "the", "coach", "who", "has", "served", "more", "than", "2", "NBA", "teams", "." ]
[ { "id": 0, "type": "table", "value": "coaches" }, { "id": 1, "type": "column", "value": "coachid" }, { "id": 3, "type": "column", "value": "tmid" }, { "id": 2, "type": "value", "value": "2" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
11,503
student_loan
bird:train.json:4524
State name of students who have been absent for 5 months from school and do not have payment due.
SELECT T1.name FROM longest_absense_from_school AS T1 INNER JOIN no_payment_due AS T2 ON T1.name = T2.name WHERE T1.month = 5 AND T2.bool = 'neg'
[ "State", "name", "of", "students", "who", "have", "been", "absent", "for", "5", "months", "from", "school", "and", "do", "not", "have", "payment", "due", "." ]
[ { "id": 1, "type": "table", "value": "longest_absense_from_school" }, { "id": 2, "type": "table", "value": "no_payment_due" }, { "id": 3, "type": "column", "value": "month" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "...
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 17, 18 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 9 ...
[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
11,504
codebase_comments
bird:train.json:589
Which method has the summary "Write a command to the log"?
SELECT Name FROM Method WHERE Summary = 'Write a command to the log'
[ "Which", "method", "has", "the", "summary", "\"", "Write", "a", "command", "to", "the", "log", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "Write a command to the log" }, { "id": 2, "type": "column", "value": "summary" }, { "id": 0, "type": "table", "value": "method" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 6, 7, 8, 9, 10, 11 ] }, { "entity_id": 4, "tok...
[ "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
11,505
mental_health_survey
bird:train.json:4591
According to 2016's survey, what is the number of users with a mental health disorder in the past?
SELECT COUNT(T2.UserID) FROM Question AS T1 INNER JOIN Answer AS T2 ON T1.questionid = T2.QuestionID WHERE T2.SurveyID = 2016 AND T1.questiontext LIKE 'Have you had a mental health disorder in the past?' AND T2.AnswerText = 'Yes'
[ "According", "to", "2016", "'s", "survey", ",", "what", "is", "the", "number", "of", "users", "with", "a", "mental", "health", "disorder", "in", "the", "past", "?" ]
[ { "id": 7, "type": "value", "value": "Have you had a mental health disorder in the past?" }, { "id": 6, "type": "column", "value": "questiontext" }, { "id": 3, "type": "column", "value": "questionid" }, { "id": 8, "type": "column", "value": "answertext" ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs":...
[ "O", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE" ]
11,506
formula_1
spider:train_spider.json:2174
How many drivers did not race in 2009?
SELECT count(DISTINCT driverId) FROM results WHERE raceId NOT IN( SELECT raceId FROM races WHERE YEAR != 2009 )
[ "How", "many", "drivers", "did", "not", "race", "in", "2009", "?" ]
[ { "id": 1, "type": "column", "value": "driverid" }, { "id": 0, "type": "table", "value": "results" }, { "id": 2, "type": "column", "value": "raceid" }, { "id": 3, "type": "table", "value": "races" }, { "id": 4, "type": "column", "value": "y...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "toke...
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "B-VALUE", "O" ]
11,507
tracking_software_problems
spider:train_spider.json:5362
List the problem id and log id which are assigned to the staff named Rylan Homenick.
SELECT DISTINCT T2.problem_id , T2.problem_log_id FROM staff AS T1 JOIN problem_log AS T2 ON T1.staff_id = T2.assigned_to_staff_id WHERE T1.staff_first_name = "Rylan" AND T1.staff_last_name = "Homenick"
[ "List", "the", "problem", "i", "d", "and", "log", "i", "d", "which", "are", "assigned", "to", "the", "staff", "named", "Rylan", "Homenick", "." ]
[ { "id": 5, "type": "column", "value": "assigned_to_staff_id" }, { "id": 6, "type": "column", "value": "staff_first_name" }, { "id": 8, "type": "column", "value": "staff_last_name" }, { "id": 1, "type": "column", "value": "problem_log_id" }, { "id":...
[ { "entity_id": 0, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5,...
[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-TABLE", "B-COLUMN", "B-COLUMN", "B-COLUMN", "O" ]
11,508
food_inspection
bird:train.json:8848
Who is the owner of the business that has a high risk violation of 103109 and described as unclean or unsanitary food contact surfaces?
SELECT DISTINCT T2.owner_name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'High Risk' AND T1.violation_type_id = 103109 AND T1.description = 'Unclean or unsanitary food contact surfaces'
[ "Who", "is", "the", "owner", "of", "the", "business", "that", "has", "a", "high", "risk", "violation", "of", "103109", "and", "described", "as", "unclean", "or", "unsanitary", "food", "contact", "surfaces", "?" ]
[ { "id": 9, "type": "value", "value": "Unclean or unsanitary food contact surfaces" }, { "id": 6, "type": "column", "value": "violation_type_id" }, { "id": 4, "type": "column", "value": "risk_category" }, { "id": 3, "type": "column", "value": "business_id" ...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, ...
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "B-TABLE", "O", "B-VALUE", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
11,509
car_racing
bird:test.json:1628
Which make is associated with 3 or more drivers?
SELECT Make FROM driver GROUP BY Make HAVING COUNT(*) >= 3
[ "Which", "make", "is", "associated", "with", "3", "or", "more", "drivers", "?" ]
[ { "id": 0, "type": "table", "value": "driver" }, { "id": 1, "type": "column", "value": "make" }, { "id": 2, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "...
[ "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "B-TABLE", "O" ]
11,510
student_club
bird:dev.json:1413
Mention the zip code of member who incurred less than 50USD.
SELECT T1.zip FROM member AS T1 INNER JOIN expense AS T2 ON T1.member_id = T2.link_to_member WHERE T2.cost < 50
[ "Mention", "the", "zip", "code", "of", "member", "who", "incurred", "less", "than", "50USD", "." ]
[ { "id": 6, "type": "column", "value": "link_to_member" }, { "id": 5, "type": "column", "value": "member_id" }, { "id": 2, "type": "table", "value": "expense" }, { "id": 1, "type": "table", "value": "member" }, { "id": 3, "type": "column", "...
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "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": ...
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
11,511
superhero
bird:dev.json:801
Find the ratio between male superheroes and female superheroes.
SELECT CAST(COUNT(CASE WHEN T2.gender = 'Male' THEN T1.id ELSE NULL END) AS REAL) / COUNT(CASE WHEN T2.gender = 'Female' THEN T1.id ELSE NULL END) FROM superhero AS T1 INNER JOIN gender AS T2 ON T1.gender_id = T2.id
[ "Find", "the", "ratio", "between", "male", "superheroes", "and", "female", "superheroes", "." ]
[ { "id": 0, "type": "table", "value": "superhero" }, { "id": 2, "type": "column", "value": "gender_id" }, { "id": 1, "type": "table", "value": "gender" }, { "id": 4, "type": "column", "value": "gender" }, { "id": 5, "type": "value", "value":...
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 0 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": ...
[ "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "B-VALUE", "B-TABLE", "O" ]
11,512
disney
bird:train.json:4624
Please list the villains of all the movies directed by Wolfgang Reitherman.
SELECT T2.villian FROM director AS T1 INNER JOIN characters AS T2 ON T1.name = T2.movie_title WHERE T1.director = 'Wolfgang Reitherman' AND T2.villian IS NOT NULL
[ "Please", "list", "the", "villains", "of", "all", "the", "movies", "directed", "by", "Wolfgang", "Reitherman", "." ]
[ { "id": 6, "type": "value", "value": "Wolfgang Reitherman" }, { "id": 4, "type": "column", "value": "movie_title" }, { "id": 2, "type": "table", "value": "characters" }, { "id": 1, "type": "table", "value": "director" }, { "id": 5, "type": "col...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": ...
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
11,513
airline
bird:train.json:5904
List the flight date of flights with air carrier described as Profit Airlines Inc.: XBH which have an actual elapsed time below 100.
SELECT T2.FL_DATE FROM `Air Carriers` AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.OP_CARRIER_AIRLINE_ID WHERE T2.ACTUAL_ELAPSED_TIME < 100 AND T1.Description = 'Profit Airlines Inc.: XBH'
[ "List", "the", "flight", "date", "of", "flights", "with", "air", "carrier", "described", "as", "Profit", "Airlines", "Inc.", ":", "XBH", "which", "have", "an", "actual", "elapsed", "time", "below", "100", "." ]
[ { "id": 8, "type": "value", "value": "Profit Airlines Inc.: XBH" }, { "id": 4, "type": "column", "value": "op_carrier_airline_id" }, { "id": 5, "type": "column", "value": "actual_elapsed_time" }, { "id": 1, "type": "table", "value": "Air Carriers" }, {...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 7, 8 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id"...
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
11,514
public_review_platform
bird:train.json:3758
How many Yelp businesses are there in 'AZ' with less than "3" stars?
SELECT COUNT(business_id) FROM Business WHERE state LIKE 'AZ' AND stars < 3
[ "How", "many", "Yelp", "businesses", "are", "there", "in", "'", "AZ", "'", "with", "less", "than", "\"", "3", "\"", "stars", "?" ]
[ { "id": 1, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "business" }, { "id": 2, "type": "column", "value": "state" }, { "id": 4, "type": "column", "value": "stars" }, { "id": 3, "type": "value", "value":...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, ...
[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "O" ]
11,515
retails
bird:train.json:6845
List the phone numbers of customers whose order priority is urgent.
SELECT T2.c_phone FROM orders AS T1 INNER JOIN customer AS T2 ON T1.o_custkey = T2.c_custkey WHERE T1.o_orderpriority = '1-URGENT'
[ "List", "the", "phone", "numbers", "of", "customers", "whose", "order", "priority", "is", "urgent", "." ]
[ { "id": 3, "type": "column", "value": "o_orderpriority" }, { "id": 5, "type": "column", "value": "o_custkey" }, { "id": 6, "type": "column", "value": "c_custkey" }, { "id": 2, "type": "table", "value": "customer" }, { "id": 4, "type": "value", ...
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 10 ] }, ...
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
11,516
sports_competition
spider:train_spider.json:3381
find the number of players whose points are lower than 30 in each position.
SELECT count(*) , POSITION FROM player WHERE points < 30 GROUP BY POSITION
[ "find", "the", "number", "of", "players", "whose", "points", "are", "lower", "than", "30", "in", "each", "position", "." ]
[ { "id": 1, "type": "column", "value": "position" }, { "id": 0, "type": "table", "value": "player" }, { "id": 2, "type": "column", "value": "points" }, { "id": 3, "type": "value", "value": "30" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 13 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entit...
[ "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O" ]
11,517
manufactory_1
spider:train_spider.json:5346
Select the name and price of the cheapest product.
SELECT name , price FROM Products ORDER BY price ASC LIMIT 1
[ "Select", "the", "name", "and", "price", "of", "the", "cheapest", "product", "." ]
[ { "id": 0, "type": "table", "value": "products" }, { "id": 2, "type": "column", "value": "price" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "...
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
11,518
soccer_2016
bird:train.json:2028
How many matches did team Mumbai Indians win in 2008?
SELECT COUNT(T.Match_Id) FROM ( SELECT T2.Match_Id FROM Team AS T1 INNER JOIN Match AS T2 ON T1.team_id = T2.match_winner INNER JOIN Player_Match AS T3 ON T1.Team_Id = T3.Team_Id WHERE T1.Team_Name = 'Mumbai Indians' AND T2.Match_Date LIKE '2008%' GROUP BY T2.Match_Id ) T
[ "How", "many", "matches", "did", "team", "Mumbai", "Indians", "win", "in", "2008", "?" ]
[ { "id": 6, "type": "value", "value": "Mumbai Indians" }, { "id": 1, "type": "table", "value": "player_match" }, { "id": 9, "type": "column", "value": "match_winner" }, { "id": 7, "type": "column", "value": "match_date" }, { "id": 5, "type": "co...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_...
[ "O", "B-TABLE", "B-TABLE", "B-COLUMN", "B-TABLE", "B-VALUE", "I-VALUE", "O", "O", "B-VALUE", "O" ]
11,519
student_club
bird:dev.json:1422
State the category of events were held at MU 215.
SELECT DISTINCT T2.category FROM event AS T1 INNER JOIN budget AS T2 ON T1.event_id = T2.link_to_event WHERE T1.location = 'MU 215'
[ "State", "the", "category", "of", "events", "were", "held", "at", "MU", "215", "." ]
[ { "id": 6, "type": "column", "value": "link_to_event" }, { "id": 0, "type": "column", "value": "category" }, { "id": 3, "type": "column", "value": "location" }, { "id": 5, "type": "column", "value": "event_id" }, { "id": 2, "type": "table", ...
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 8, 9 ] }, { "entity_id":...
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
11,520
cookbook
bird:train.json:8869
Is the ingredient "graham cracker crumbs" optional in the recipe "Raspberry Chiffon Pie"?
SELECT T2.optional FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id WHERE T1.title = 'Raspberry Chiffon Pie' AND T3.name = 'graham cracker crumbs'
[ "Is", "the", "ingredient", "\"", "graham", "cracker", "crumbs", "\"", "optional", "in", "the", "recipe", "\"", "Raspberry", "Chiffon", "Pie", "\"", "?" ]
[ { "id": 6, "type": "value", "value": "Raspberry Chiffon Pie" }, { "id": 8, "type": "value", "value": "graham cracker crumbs" }, { "id": 4, "type": "column", "value": "ingredient_id" }, { "id": 1, "type": "table", "value": "ingredient" }, { "id": 9,...
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, ...
[ "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
11,521
customer_complaints
spider:train_spider.json:5770
Find the emails and phone numbers of all the customers, ordered by email address and phone number.
SELECT email_address , phone_number FROM customers ORDER BY email_address , phone_number
[ "Find", "the", "emails", "and", "phone", "numbers", "of", "all", "the", "customers", ",", "ordered", "by", "email", "address", "and", "phone", "number", "." ]
[ { "id": 1, "type": "column", "value": "email_address" }, { "id": 2, "type": "column", "value": "phone_number" }, { "id": 0, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 13, 14 ] }, { "entity_id": 2, "token_idxs": [ 16, 17 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { ...
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
11,522
movie_3
bird:train.json:9424
Please give the full name of the customer who had made the biggest amount of payment in one single film rental.
SELECT T2.first_name, T2.last_name FROM payment AS T1 INNER JOIN customer AS T2 ON T1.customer_id = T2.customer_id ORDER BY T1.amount DESC LIMIT 1
[ "Please", "give", "the", "full", "name", "of", "the", "customer", "who", "had", "made", "the", "biggest", "amount", "of", "payment", "in", "one", "single", "film", "rental", "." ]
[ { "id": 5, "type": "column", "value": "customer_id" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 3, "type": "table", "value": "customer" }, { "id": 2, "type": "table", ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entit...
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
11,523
sales
bird:train.json:5454
What are the full names of the top 3 employees who handled the highest number of sales?
SELECT T1.FirstName, T1.MiddleInitial, T1.LastName FROM Employees AS T1 INNER JOIN Sales AS T2 ON T1.EmployeeID = T2.SalesPersonID GROUP BY T2.SalesPersonID, T1.FirstName, T1.MiddleInitial, T1.LastName ORDER BY COUNT(T2.SalesID) DESC LIMIT 3
[ "What", "are", "the", "full", "names", "of", "the", "top", "3", "employees", "who", "handled", "the", "highest", "number", "of", "sales", "?" ]
[ { "id": 0, "type": "column", "value": "salespersonid" }, { "id": 2, "type": "column", "value": "middleinitial" }, { "id": 6, "type": "column", "value": "employeeid" }, { "id": 1, "type": "column", "value": "firstname" }, { "id": 4, "type": "tab...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": ...
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
11,524
student_loan
bird:train.json:4500
How many students are enrolled in smc during month 1?
SELECT COUNT(name) FROM enrolled WHERE school = 'smc' AND month = 1
[ "How", "many", "students", "are", "enrolled", "in", "smc", "during", "month", "1", "?" ]
[ { "id": 0, "type": "table", "value": "enrolled" }, { "id": 2, "type": "column", "value": "school" }, { "id": 4, "type": "column", "value": "month" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "smc"...
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "...
[ "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "B-COLUMN", "B-VALUE", "O" ]
11,525
synthea
bird:train.json:1449
How many patients with 'allergy to eggs' have been immunized with 'Td (adult) preservative free'?
SELECT COUNT(DISTINCT T2.patient) FROM allergies AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient INNER JOIN immunizations AS T3 ON T2.patient = T3.PATIENT WHERE T1.DESCRIPTION = 'Allergy to eggs' AND T3.DESCRIPTION = 'Td (adult) preservative free'
[ "How", "many", "patients", "with", "'", "allergy", "to", "eggs", "'", "have", "been", "immunized", "with", "'", "Td", "(", "adult", ")", "preservative", "free", "'", "?" ]
[ { "id": 6, "type": "value", "value": "Td (adult) preservative free" }, { "id": 5, "type": "value", "value": "Allergy to eggs" }, { "id": 0, "type": "table", "value": "immunizations" }, { "id": 4, "type": "column", "value": "description" }, { "id": ...
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, ...
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
11,527
allergy_1
spider:train_spider.json:492
What is the largest major?
SELECT major FROM Student GROUP BY major ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "largest", "major", "?" ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "major" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "O", "O", "B-COLUMN", "O" ]
11,528
pilot_record
spider:train_spider.json:2086
List the distinct positions of pilots older than 30.
SELECT DISTINCT POSITION FROM pilot WHERE Age > 30
[ "List", "the", "distinct", "positions", "of", "pilots", "older", "than", "30", "." ]
[ { "id": 1, "type": "column", "value": "position" }, { "id": 0, "type": "table", "value": "pilot" }, { "id": 2, "type": "column", "value": "age" }, { "id": 3, "type": "value", "value": "30" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "...
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
11,529
public_review_platform
bird:train.json:3904
Find out which business is opened for 24/7 and list out what is the business attribute.
SELECT T5.attribute_name FROM Business_Hours AS T1 INNER JOIN Days AS T2 ON T1.day_id = T2.day_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id INNER JOIN Business_Attributes AS T4 ON T3.business_id = T4.business_id INNER JOIN Attributes AS T5 ON T4.attribute_id = T5.attribute_id WHERE T2.day_id LIKE '1'...
[ "Find", "out", "which", "business", "is", "opened", "for", "24/7", "and", "list", "out", "what", "is", "the", "business", "attribute", "." ]
[ { "id": 8, "type": "table", "value": "business_attributes" }, { "id": 0, "type": "column", "value": "attribute_name" }, { "id": 16, "type": "table", "value": "business_hours" }, { "id": 9, "type": "column", "value": "attribute_id" }, { "id": 12, ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 15 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O" ]
11,530
superstore
bird:train.json:2432
Who was the customer in the South Region superstore who bought the most “Hon Multipurpose Stacking Arm Chairs"?
SELECT T2.`Customer Name` FROM south_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 T3.`Product Name` = 'Hon Multipurpose Stacking Arm Chairs' GROUP BY T2.`Customer Name` ORDER BY COUNT(T2.`Customer Name`) DESC LIMIT 1
[ "Who", "was", "the", "customer", "in", "the", "South", "Region", "superstore", "who", "bought", "the", "most", "“", "Hon", "Multipurpose", "Stacking", "Arm", "Chairs", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "Hon Multipurpose Stacking Arm Chairs" }, { "id": 4, "type": "table", "value": "south_superstore" }, { "id": 0, "type": "column", "value": "Customer Name" }, { "id": 2, "type": "column", "value": "Product Name" }, {...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 14, 15, 16, 17, 18 ] }, { "entity_id": 4, "token_idxs": [ 6, 7, ...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
11,531
ship_1
spider:train_spider.json:6249
What are the different ship flags, and how many ships have each?
SELECT count(*) , flag FROM ship GROUP BY flag
[ "What", "are", "the", "different", "ship", "flags", ",", "and", "how", "many", "ships", "have", "each", "?" ]
[ { "id": 0, "type": "table", "value": "ship" }, { "id": 1, "type": "column", "value": "flag" } ]
[ { "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": ...
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,532
card_games
bird:dev.json:400
Lists the set code of all cards translated into Spanish.
SELECT setCode FROM set_translations WHERE language = 'Spanish'
[ "Lists", "the", "set", "code", "of", "all", "cards", "translated", "into", "Spanish", "." ]
[ { "id": 0, "type": "table", "value": "set_translations" }, { "id": 2, "type": "column", "value": "language" }, { "id": 1, "type": "column", "value": "setcode" }, { "id": 3, "type": "value", "value": "Spanish" } ]
[ { "entity_id": 0, "token_idxs": [ 7, 8 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "en...
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "B-VALUE", "O" ]
11,533
disney
bird:train.json:4647
Who is the hero character of the adventure movie which was released on 2016/3/4?
SELECT T1.hero FROM characters AS T1 INNER JOIN movies_total_gross AS T2 ON T2.movie_title = T1.movie_title WHERE T2.genre = 'Adventure' AND T1.release_date = '4-Mar-16'
[ "Who", "is", "the", "hero", "character", "of", "the", "adventure", "movie", "which", "was", "released", "on", "2016/3/4", "?" ]
[ { "id": 2, "type": "table", "value": "movies_total_gross" }, { "id": 6, "type": "column", "value": "release_date" }, { "id": 3, "type": "column", "value": "movie_title" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 5, "type": ...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "...
[ "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O" ]
11,534
mondial_geo
bird:train.json:8469
Among the country member of 'IOC' organization, which country has the most population?
SELECT T2.Name FROM isMember AS T1 INNER JOIN country AS T2 ON T1.Country = T2.Code WHERE T1.Organization = 'IOC' ORDER BY T2.Population DESC LIMIT 1
[ "Among", "the", "country", "member", "of", "'", "IOC", "'", "organization", ",", "which", "country", "has", "the", "most", "population", "?" ]
[ { "id": 3, "type": "column", "value": "organization" }, { "id": 5, "type": "column", "value": "population" }, { "id": 1, "type": "table", "value": "ismember" }, { "id": 2, "type": "table", "value": "country" }, { "id": 6, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "...
[ "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
11,535
soccer_2
spider:train_spider.json:5033
What are the names of the schools with some players in the mid position but no goalies?
SELECT cName FROM tryout WHERE pPos = 'mid' EXCEPT SELECT cName FROM tryout WHERE pPos = 'goalie'
[ "What", "are", "the", "names", "of", "the", "schools", "with", "some", "players", "in", "the", "mid", "position", "but", "no", "goalies", "?" ]
[ { "id": 0, "type": "table", "value": "tryout" }, { "id": 4, "type": "value", "value": "goalie" }, { "id": 1, "type": "column", "value": "cname" }, { "id": 2, "type": "column", "value": "ppos" }, { "id": 3, "type": "value", "value": "mid" ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, ...
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O" ]
11,536
cs_semester
bird:train.json:896
Among the easiest courses, what is the name of the course where most students got an A?
SELECT T2.name FROM registration AS T1 INNER JOIN course AS T2 ON T1.course_id = T2.course_id WHERE T1.grade = 'A' AND T2.diff = 1 GROUP BY T2.name ORDER BY COUNT(T1.student_id) DESC LIMIT 1
[ "Among", "the", "easiest", "courses", ",", "what", "is", "the", "name", "of", "the", "course", "where", "most", "students", "got", "an", "A", "?" ]
[ { "id": 1, "type": "table", "value": "registration" }, { "id": 8, "type": "column", "value": "student_id" }, { "id": 3, "type": "column", "value": "course_id" }, { "id": 2, "type": "table", "value": "course" }, { "id": 4, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "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":...
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
11,537
card_games
bird:dev.json:375
List down all the card IDs with converted mana cost of 0.
SELECT id FROM cards WHERE convertedManaCost = 0
[ "List", "down", "all", "the", "card", "IDs", "with", "converted", "mana", "cost", "of", "0", "." ]
[ { "id": 2, "type": "column", "value": "convertedmanacost" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 1, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 7, 8, 9 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] ...
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
11,538
works_cycles
bird:train.json:7000
For all the products, list the product name and its corresponding start date for the current standard cost.
SELECT T1.Name, T2.StartDate FROM Product AS T1 INNER JOIN ProductCostHistory AS T2 ON T1.ProductID = T2.ProductID WHERE T2.EndDate IS NULL
[ "For", "all", "the", "products", ",", "list", "the", "product", "name", "and", "its", "corresponding", "start", "date", "for", "the", "current", "standard", "cost", "." ]
[ { "id": 3, "type": "table", "value": "productcosthistory" }, { "id": 1, "type": "column", "value": "startdate" }, { "id": 5, "type": "column", "value": "productid" }, { "id": 2, "type": "table", "value": "product" }, { "id": 4, "type": "column"...
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 4, "token_idxs": [ ...
[ "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
11,539
car_retails
bird:train.json:1587
From 2003 to 2004, how many customers have paid more than three times?
SELECT COUNT(customernumber) FROM ( SELECT customernumber FROM payments WHERE STRFTIME('%Y', paymentDate) >= '2003' AND STRFTIME('%Y', paymentDate) <= '2004' GROUP BY customernumber HAVING COUNT(customernumber) > 3 ) T
[ "From", "2003", "to", "2004", ",", "how", "many", "customers", "have", "paid", "more", "than", "three", "times", "?" ]
[ { "id": 0, "type": "column", "value": "customernumber" }, { "id": 6, "type": "column", "value": "paymentdate" }, { "id": 1, "type": "table", "value": "payments" }, { "id": 3, "type": "value", "value": "2003" }, { "id": 4, "type": "value", "...
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 1 ] }, { "entity_id": 4, "token_idxs": [ 3 ] }, { "entity_id": 5, "...
[ "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
11,540
retails
bird:train.json:6686
Among the orders made by customers in Germany, which one of them has the highest priority in delivery? Please give its order key.
SELECT T3.o_orderkey FROM nation AS T1 INNER JOIN customer AS T2 ON T1.n_nationkey = T2.c_nationkey INNER JOIN orders AS T3 ON T2.c_custkey = T3.o_custkey WHERE T1.n_name = 'GERMANY' ORDER BY T3.o_orderdate LIMIT 1
[ "Among", "the", "orders", "made", "by", "customers", "in", "Germany", ",", "which", "one", "of", "them", "has", "the", "highest", "priority", "in", "delivery", "?", "Please", "give", "its", "order", "key", "." ]
[ { "id": 4, "type": "column", "value": "o_orderdate" }, { "id": 9, "type": "column", "value": "n_nationkey" }, { "id": 10, "type": "column", "value": "c_nationkey" }, { "id": 0, "type": "column", "value": "o_orderkey" }, { "id": 7, "type": "colu...
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
11,541
inn_1
spider:train_spider.json:2596
What is the average base price of different bed type? List bed type and average base price.
SELECT bedType , avg(basePrice) FROM Rooms GROUP BY bedType;
[ "What", "is", "the", "average", "base", "price", "of", "different", "bed", "type", "?", "List", "bed", "type", "and", "average", "base", "price", "." ]
[ { "id": 2, "type": "column", "value": "baseprice" }, { "id": 1, "type": "column", "value": "bedtype" }, { "id": 0, "type": "table", "value": "rooms" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8, 9 ] }, { "entity_id": 2, "token_idxs": [ 4, 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, ...
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,542
gas_company
spider:train_spider.json:1999
Show all company names and headquarters in the descending order of market value.
SELECT company , headquarters FROM company ORDER BY market_value DESC
[ "Show", "all", "company", "names", "and", "headquarters", "in", "the", "descending", "order", "of", "market", "value", "." ]
[ { "id": 2, "type": "column", "value": "headquarters" }, { "id": 3, "type": "column", "value": "market_value" }, { "id": 0, "type": "table", "value": "company" }, { "id": 1, "type": "column", "value": "company" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
11,544
books
bird:train.json:6100
What is the title of the book in the order ID 931?
SELECT T1.title FROM book AS T1 INNER JOIN order_line AS T2 ON T1.book_id = T2.book_id WHERE T2.order_id = 931
[ "What", "is", "the", "title", "of", "the", "book", "in", "the", "order", "ID", "931", "?" ]
[ { "id": 2, "type": "table", "value": "order_line" }, { "id": 3, "type": "column", "value": "order_id" }, { "id": 5, "type": "column", "value": "book_id" }, { "id": 0, "type": "column", "value": "title" }, { "id": 1, "type": "table", "value"...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { ...
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
11,545
student_1
spider:train_spider.json:4071
How many students are taught by teacher TARRING LEIA?
SELECT count(*) FROM list AS T1 JOIN teachers AS T2 ON T1.classroom = T2.classroom WHERE T2.firstname = "TARRING" AND T2.lastname = "LEIA"
[ "How", "many", "students", "are", "taught", "by", "teacher", "TARRING", "LEIA", "?" ]
[ { "id": 2, "type": "column", "value": "classroom" }, { "id": 3, "type": "column", "value": "firstname" }, { "id": 1, "type": "table", "value": "teachers" }, { "id": 5, "type": "column", "value": "lastname" }, { "id": 4, "type": "column", "v...
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O" ]
11,546
public_review_platform
bird:train.json:3806
Please provide the attribute values ​​of the bussinesses with fashion in Scottsdale.
SELECT T2.attribute_value FROM Business AS T1 INNER JOIN Business_Attributes AS T2 ON T1.business_id = T2.business_id INNER JOIN Business_Categories AS T3 ON T1.business_id = T3.business_id INNER JOIN Categories AS T4 ON T3.category_id = T4.category_id WHERE T4.category_name LIKE 'Fashion' AND T1.city LIKE 'Scottsdale'
[ "Please", "provide", "the", "attribute", "values", "​​of", "the", "bussinesses", "with", "fashion", "in", "Scottsdale", "." ]
[ { "id": 2, "type": "table", "value": "business_categories" }, { "id": 9, "type": "table", "value": "business_attributes" }, { "id": 0, "type": "column", "value": "attribute_value" }, { "id": 4, "type": "column", "value": "category_name" }, { "id": ...
[ { "entity_id": 0, "token_idxs": [ 3, 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": [ ...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
11,547
food_inspection
bird:train.json:8806
How many eateries applied in 2012?
SELECT COUNT(business_id) FROM businesses WHERE STRFTIME('%Y', application_date) = '2012'
[ "How", "many", "eateries", "applied", "in", "2012", "?" ]
[ { "id": 4, "type": "column", "value": "application_date" }, { "id": 2, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "businesses" }, { "id": 1, "type": "value", "value": "2012" }, { "id": 3, "type": "value", ...
[ { "entity_id": 0, "token_idxs": [] }, { "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": [] }, { ...
[ "O", "O", "O", "O", "O", "B-VALUE", "O" ]
11,548
genes
bird:train.json:2504
What kind of expression correlation occurs in physical type interacting gene pairs and what percentage of these are negatively correlated?
SELECT Expression_Corr FROM Interactions WHERE Type = 'Physical' UNION ALL SELECT CAST(SUM(Expression_Corr < 0) AS REAL) * 100 / COUNT(*) FROM Interactions WHERE Type = 'Physical'
[ "What", "kind", "of", "expression", "correlation", "occurs", "in", "physical", "type", "interacting", "gene", "pairs", "and", "what", "percentage", "of", "these", "are", "negatively", "correlated", "?" ]
[ { "id": 1, "type": "column", "value": "expression_corr" }, { "id": 0, "type": "table", "value": "interactions" }, { "id": 3, "type": "value", "value": "Physical" }, { "id": 2, "type": "column", "value": "type" }, { "id": 4, "type": "value", ...
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_...
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,549
cinema
spider:train_spider.json:1931
Show all the locations where some cinemas were opened in both year 2010 and year 2011.
SELECT LOCATION FROM cinema WHERE openning_year = 2010 INTERSECT SELECT LOCATION FROM cinema WHERE openning_year = 2011
[ "Show", "all", "the", "locations", "where", "some", "cinemas", "were", "opened", "in", "both", "year", "2010", "and", "year", "2011", "." ]
[ { "id": 2, "type": "column", "value": "openning_year" }, { "id": 1, "type": "column", "value": "location" }, { "id": 0, "type": "table", "value": "cinema" }, { "id": 3, "type": "value", "value": "2010" }, { "id": 4, "type": "value", "value"...
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 8, 9, 10, 11 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_i...
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O", "O", "B-VALUE", "O" ]
11,550
public_review_platform
bird:train.json:3961
For the Yelp businesses which received a "5" star review with "uber" number of votes for funny, which one is located in "Phoenix"? Give the business ID.
SELECT T1.business_id FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Phoenix' AND T2.review_stars = 5 AND T2.review_votes_funny = 'Uber'
[ "For", "the", "Yelp", "businesses", "which", "received", "a", "\"", "5", "\"", "star", "review", "with", "\"", "uber", "\"", "number", "of", "votes", "for", "funny", ",", "which", "one", "is", "located", "in", "\"", "Phoenix", "\"", "?", "Give", "the",...
[ { "id": 7, "type": "column", "value": "review_votes_funny" }, { "id": 5, "type": "column", "value": "review_stars" }, { "id": 0, "type": "column", "value": "business_id" }, { "id": 1, "type": "table", "value": "business" }, { "id": 2, "type": "...
[ { "entity_id": 0, "token_idxs": [ 34 ] }, { "entity_id": 1, "token_idxs": [ 33 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 28 ] }, { "ent...
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
11,551
cookbook
bird:train.json:8923
List the names of recipes that can lead to constipation.
SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T2.iron > 20
[ "List", "the", "names", "of", "recipes", "that", "can", "lead", "to", "constipation", "." ]
[ { "id": 2, "type": "table", "value": "nutrition" }, { "id": 5, "type": "column", "value": "recipe_id" }, { "id": 1, "type": "table", "value": "recipe" }, { "id": 0, "type": "column", "value": "title" }, { "id": 3, "type": "column", "value":...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": ...
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O" ]
11,552
culture_company
spider:train_spider.json:6981
Which publishers did not publish a book in 1989?
SELECT publisher FROM book_club EXCEPT SELECT publisher FROM book_club WHERE YEAR = 1989
[ "Which", "publishers", "did", "not", "publish", "a", "book", "in", "1989", "?" ]
[ { "id": 0, "type": "table", "value": "book_club" }, { "id": 1, "type": "column", "value": "publisher" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "1989" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
11,553
works_cycles
bird:train.json:7036
Who is the Vice President of Engineering and when did he join the company? Indicate his/her full name.
SELECT T2.FirstName, T2.MiddleName, T2.LastName, T1.HireDate FROM Employee AS T1 INNER JOIN Person AS T2 USING (BusinessEntityID) WHERE T1.JobTitle = 'Vice President of Engineering'
[ "Who", "is", "the", "Vice", "President", "of", "Engineering", "and", "when", "did", "he", "join", "the", "company", "?", "Indicate", "his", "/", "her", "full", "name", "." ]
[ { "id": 7, "type": "value", "value": "Vice President of Engineering" }, { "id": 1, "type": "column", "value": "middlename" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 3, "t...
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11,554
election
spider:train_spider.json:2794
Show the people that have been comptroller the most times and the corresponding number of times.
SELECT Comptroller , COUNT(*) FROM party GROUP BY Comptroller ORDER BY COUNT(*) DESC LIMIT 1
[ "Show", "the", "people", "that", "have", "been", "comptroller", "the", "most", "times", "and", "the", "corresponding", "number", "of", "times", "." ]
[ { "id": 1, "type": "column", "value": "comptroller" }, { "id": 0, "type": "table", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
11,555
entrepreneur
spider:train_spider.json:2285
What are the weights of entrepreneurs in descending order of money requested?
SELECT T2.Weight FROM entrepreneur AS T1 JOIN people AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Money_Requested DESC
[ "What", "are", "the", "weights", "of", "entrepreneurs", "in", "descending", "order", "of", "money", "requested", "?" ]
[ { "id": 3, "type": "column", "value": "money_requested" }, { "id": 1, "type": "table", "value": "entrepreneur" }, { "id": 4, "type": "column", "value": "people_id" }, { "id": 0, "type": "column", "value": "weight" }, { "id": 2, "type": "table",...
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
11,556
books
bird:train.json:6078
The book name "The Season: A Candid Look at Broadway" was published by which publisher?
SELECT T2.publisher_name FROM book AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.publisher_id WHERE T1.title = 'The Season: A Candid Look at Broadway'
[ "The", "book", "name", "\"", "The", "Season", ":", "A", "Candid", "Look", "at", "Broadway", "\"", "was", "published", "by", "which", "publisher", "?" ]
[ { "id": 4, "type": "value", "value": "The Season: A Candid Look at Broadway" }, { "id": 0, "type": "column", "value": "publisher_name" }, { "id": 5, "type": "column", "value": "publisher_id" }, { "id": 2, "type": "table", "value": "publisher" }, { ...
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[ "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]