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12,631
cs_semester
bird:train.json:869
Which professor advised Willie Rechert to work as a research assistant? Please give his or her full name.
SELECT T1.first_name, T1.last_name FROM prof AS T1 INNER JOIN RA AS T2 ON T1.prof_id = T2.prof_id INNER JOIN student AS T3 ON T2.student_id = T3.student_id WHERE T3.f_name = 'Willie' AND T3.l_name = 'Rechert'
[ "Which", "professor", "advised", "Willie", "Rechert", "to", "work", "as", "a", "research", "assistant", "?", "Please", "give", "his", "or", "her", "full", "name", "." ]
[ { "id": 0, "type": "column", "value": "first_name" }, { "id": 5, "type": "column", "value": "student_id" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 2, "type": "table", "value": "student" }, { "id": 9, "type": "value", "value": "Rechert" }, { "id": 10, "type": "column", "value": "prof_id" }, { "id": 6, "type": "column", "value": "f_name" }, { "id": 7, "type": "value", "value": "Willie" }, { "id": 8, "type": "column", "value": "l_name" }, { "id": 3, "type": "table", "value": "prof" }, { "id": 4, "type": "table", "value": "ra" } ]
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12,632
soccer_2016
bird:train.json:1993
How many times did K Goel played as a player only?
SELECT COUNT(T1.Match_Id) FROM Player_Match AS T1 INNER JOIN Player AS T2 ON T1.Player_Id = T2.Player_Id INNER JOIN Rolee AS T3 ON T1.Role_Id = T3.Role_Id WHERE T2.Player_Name = 'K Goel' AND T3.Role_Id = 3
[ "How", "many", "times", "did", "K", "Goel", "played", "as", "a", "player", "only", "?" ]
[ { "id": 2, "type": "table", "value": "player_match" }, { "id": 5, "type": "column", "value": "player_name" }, { "id": 8, "type": "column", "value": "player_id" }, { "id": 1, "type": "column", "value": "match_id" }, { "id": 4, "type": "column", "value": "role_id" }, { "id": 3, "type": "table", "value": "player" }, { "id": 6, "type": "value", "value": "K Goel" }, { "id": 0, "type": "table", "value": "rolee" }, { "id": 7, "type": "value", "value": "3" } ]
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[ "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "B-TABLE", "O", "O" ]
12,633
thrombosis_prediction
bird:dev.json:1198
How many female patients were given an APS diagnosis?
SELECT COUNT(ID) FROM Patient WHERE SEX = 'F' AND Diagnosis = 'APS'
[ "How", "many", "female", "patients", "were", "given", "an", "APS", "diagnosis", "?" ]
[ { "id": 4, "type": "column", "value": "diagnosis" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 2, "type": "column", "value": "sex" }, { "id": 5, "type": "value", "value": "APS" }, { "id": 1, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
12,635
insurance_policies
spider:train_spider.json:3877
Tell me the the claim date and settlement date for each settlement case.
SELECT Date_Claim_Made , Date_Claim_Settled FROM Settlements
[ "Tell", "me", "the", "the", "claim", "date", "and", "settlement", "date", "for", "each", "settlement", "case", "." ]
[ { "id": 2, "type": "column", "value": "date_claim_settled" }, { "id": 1, "type": "column", "value": "date_claim_made" }, { "id": 0, "type": "table", "value": "settlements" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O" ]
12,636
hospital_1
spider:train_spider.json:3962
List the names of departments where some physicians are primarily affiliated with.
SELECT DISTINCT T2.name FROM affiliated_with AS T1 JOIN department AS T2 ON T1.department = T2.departmentid WHERE PrimaryAffiliation = 1
[ "List", "the", "names", "of", "departments", "where", "some", "physicians", "are", "primarily", "affiliated", "with", "." ]
[ { "id": 3, "type": "column", "value": "primaryaffiliation" }, { "id": 1, "type": "table", "value": "affiliated_with" }, { "id": 6, "type": "column", "value": "departmentid" }, { "id": 2, "type": "table", "value": "department" }, { "id": 5, "type": "column", "value": "department" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "O" ]
12,637
european_football_2
bird:dev.json:1130
What are the short name of team who played safe while creating chance of passing?
SELECT DISTINCT t1.team_short_name FROM Team AS t1 INNER JOIN Team_Attributes AS t2 ON t1.team_api_id = t2.team_api_id WHERE t2.chanceCreationPassingClass = 'Safe'
[ "What", "are", "the", "short", "name", "of", "team", "who", "played", "safe", "while", "creating", "chance", "of", "passing", "?" ]
[ { "id": 3, "type": "column", "value": "chancecreationpassingclass" }, { "id": 0, "type": "column", "value": "team_short_name" }, { "id": 2, "type": "table", "value": "team_attributes" }, { "id": 5, "type": "column", "value": "team_api_id" }, { "id": 1, "type": "table", "value": "team" }, { "id": 4, "type": "value", "value": "Safe" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
12,638
image_and_language
bird:train.json:7610
How many 'blue' attribute classes are there on image ID 2355735?
SELECT COUNT(T1.ATT_CLASS) FROM ATT_CLASSES AS T1 INNER JOIN IMG_OBJ_ATT AS T2 ON T1.ATT_CLASS_ID = T2.ATT_CLASS_ID WHERE T2.IMG_ID = 2355735 AND T1.ATT_CLASS = 'blue'
[ "How", "many", "'", "blue", "'", "attribute", "classes", "are", "there", "on", "image", "ID", "2355735", "?" ]
[ { "id": 3, "type": "column", "value": "att_class_id" }, { "id": 0, "type": "table", "value": "att_classes" }, { "id": 1, "type": "table", "value": "img_obj_att" }, { "id": 2, "type": "column", "value": "att_class" }, { "id": 5, "type": "value", "value": "2355735" }, { "id": 4, "type": "column", "value": "img_id" }, { "id": 6, "type": "value", "value": "blue" } ]
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[ "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
12,639
beer_factory
bird:train.json:5283
What are the brands of the root beers that received 5-star ratings from no less than 5 customers?
SELECT T1.BrandName FROM rootbeerbrand AS T1 INNER JOIN rootbeerreview AS T2 ON T1.BrandID = T2.BrandID WHERE T2.StarRating = 5 GROUP BY T2.BrandID HAVING COUNT(T2.StarRating) >= 5
[ "What", "are", "the", "brands", "of", "the", "root", "beers", "that", "received", "5", "-", "star", "ratings", "from", "no", "less", "than", "5", "customers", "?" ]
[ { "id": 3, "type": "table", "value": "rootbeerreview" }, { "id": 2, "type": "table", "value": "rootbeerbrand" }, { "id": 4, "type": "column", "value": "starrating" }, { "id": 1, "type": "column", "value": "brandname" }, { "id": 0, "type": "column", "value": "brandid" }, { "id": 5, "type": "value", "value": "5" } ]
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12,640
student_loan
bird:train.json:4370
How many students belong to the navy department?
SELECT COUNT(name) FROM enlist WHERE organ = 'navy'
[ "How", "many", "students", "belong", "to", "the", "navy", "department", "?" ]
[ { "id": 0, "type": "table", "value": "enlist" }, { "id": 1, "type": "column", "value": "organ" }, { "id": 2, "type": "value", "value": "navy" }, { "id": 3, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
12,641
synthea
bird:train.json:1361
During all the observations of Elly Koss, what was the highest Systolic Blood Pressure observed?
SELECT T2.value, T2.units FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND T1.last = 'Koss' AND T2.description = 'Systolic Blood Pressure' ORDER BY T2.VALUE DESC LIMIT 1
[ "During", "all", "the", "observations", "of", "Elly", "Koss", ",", "what", "was", "the", "highest", "Systolic", "Blood", "Pressure", "observed", "?" ]
[ { "id": 10, "type": "value", "value": "Systolic Blood Pressure" }, { "id": 3, "type": "table", "value": "observations" }, { "id": 9, "type": "column", "value": "description" }, { "id": 2, "type": "table", "value": "patients" }, { "id": 4, "type": "column", "value": "patient" }, { "id": 0, "type": "column", "value": "value" }, { "id": 1, "type": "column", "value": "units" }, { "id": 5, "type": "column", "value": "first" }, { "id": 6, "type": "value", "value": "Elly" }, { "id": 7, "type": "column", "value": "last" }, { "id": 8, "type": "value", "value": "Koss" } ]
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12,642
car_retails
bird:train.json:1629
Please list the phone numbers of the top 3 customers that have the highest credit limit and have Leslie Jennings as their sales representitive.
SELECT t1.phone FROM customers AS t1 INNER JOIN employees AS t2 ON t1.salesRepEmployeeNumber = t2.employeeNumber WHERE t2.firstName = 'Leslie' AND t2.lastName = 'Jennings' ORDER BY t1.creditLimit DESC LIMIT 3
[ "Please", "list", "the", "phone", "numbers", "of", "the", "top", "3", "customers", "that", "have", "the", "highest", "credit", "limit", "and", "have", "Leslie", "Jennings", "as", "their", "sales", "representitive", "." ]
[ { "id": 4, "type": "column", "value": "salesrepemployeenumber" }, { "id": 5, "type": "column", "value": "employeenumber" }, { "id": 3, "type": "column", "value": "creditlimit" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "employees" }, { "id": 6, "type": "column", "value": "firstname" }, { "id": 8, "type": "column", "value": "lastname" }, { "id": 9, "type": "value", "value": "Jennings" }, { "id": 7, "type": "value", "value": "Leslie" }, { "id": 0, "type": "column", "value": "phone" } ]
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12,643
theme_gallery
spider:train_spider.json:1663
How many exhibition are there in year 2005 or after?
SELECT count(*) FROM exhibition WHERE YEAR >= 2005
[ "How", "many", "exhibition", "are", "there", "in", "year", "2005", "or", "after", "?" ]
[ { "id": 0, "type": "table", "value": "exhibition" }, { "id": 1, "type": "column", "value": "year" }, { "id": 2, "type": "value", "value": "2005" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "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-TABLE", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O" ]
12,644
car_retails
bird:train.json:1551
Which countries do the top 5 highest paying customers in a single payment come from? Indicate their entire address.
SELECT DISTINCT T2.country, T2.addressLine1, T2.addressLine2 FROM payments AS T1 INNER JOIN customers AS T2 ON T1.customerNumber = T2.customerNumber ORDER BY T1.amount DESC LIMIT 5
[ "Which", "countries", "do", "the", "top", "5", "highest", "paying", "customers", "in", "a", "single", "payment", "come", "from", "?", "Indicate", "their", "entire", "address", "." ]
[ { "id": 6, "type": "column", "value": "customernumber" }, { "id": 1, "type": "column", "value": "addressline1" }, { "id": 2, "type": "column", "value": "addressline2" }, { "id": 4, "type": "table", "value": "customers" }, { "id": 3, "type": "table", "value": "payments" }, { "id": 0, "type": "column", "value": "country" }, { "id": 5, "type": "column", "value": "amount" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
12,645
mondial_geo
bird:train.json:8252
The lake with the highest altitude is located in which city?
SELECT T2.City FROM lake AS T1 LEFT JOIN located AS T2 ON T2.Lake = T1.Name ORDER BY T1.Altitude DESC LIMIT 1
[ "The", "lake", "with", "the", "highest", "altitude", "is", "located", "in", "which", "city", "?" ]
[ { "id": 3, "type": "column", "value": "altitude" }, { "id": 2, "type": "table", "value": "located" }, { "id": 0, "type": "column", "value": "city" }, { "id": 1, "type": "table", "value": "lake" }, { "id": 4, "type": "column", "value": "lake" }, { "id": 5, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 1 ] }, { "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-TABLE", "O", "O", "B-COLUMN", "O" ]
12,646
formula_1
bird:dev.json:1014
Please list the lap records for the circuits in Italy.
WITH fastest_lap_times AS (SELECT T1.raceId, T1.FastestLapTime, (CAST(SUBSTR(T1.FastestLapTime, 1, INSTR(T1.FastestLapTime, ':') - 1) AS REAL) * 60) + (CAST(SUBSTR(T1.FastestLapTime, INSTR(T1.FastestLapTime, ':') + 1, INSTR(T1.FastestLapTime, '.') - INSTR(T1.FastestLapTime, ':') - 1) AS REAL)) + (CAST(SUBSTR(T1.FastestLapTime, INSTR(T1.FastestLapTime, '.') + 1) AS REAL) / 1000) as time_in_seconds FROM results AS T1 WHERE T1.FastestLapTime IS NOT NULL ) SELECT T1.FastestLapTime as lap_record FROM results AS T1 INNER JOIN races AS T2 on T1.raceId = T2.raceId INNER JOIN circuits AS T3 on T2.circuitId = T3.circuitId INNER JOIN (SELECT MIN(fastest_lap_times.time_in_seconds) as min_time_in_seconds FROM fastest_lap_times INNER JOIN races AS T2 on fastest_lap_times.raceId = T2.raceId INNER JOIN circuits AS T3 on T2.circuitId = T3.circuitId WHERE T3.country = 'Italy' ) AS T4 ON (CAST(SUBSTR(T1.FastestLapTime, 1, INSTR(T1.FastestLapTime, ':') - 1) AS REAL) * 60) + (CAST(SUBSTR(T1.FastestLapTime, INSTR(T1.FastestLapTime, ':') + 1, INSTR(T1.FastestLapTime, '.') - INSTR(T1.FastestLapTime, ':') - 1) AS REAL)) + (CAST(SUBSTR(T1.FastestLapTime, INSTR(T1.FastestLapTime, '.') + 1) AS REAL) / 1000) = T4.min_time_in_seconds LIMIT 1
[ "Please", "list", "the", "lap", "records", "for", "the", "circuits", "in", "Italy", "." ]
[ { "id": 2, "type": "column", "value": "min_time_in_seconds" }, { "id": 11, "type": "table", "value": "fastest_lap_times" }, { "id": 10, "type": "column", "value": "time_in_seconds" }, { "id": 0, "type": "column", "value": "fastestlaptime" }, { "id": 5, "type": "column", "value": "circuitid" }, { "id": 1, "type": "table", "value": "circuits" }, { "id": 3, "type": "table", "value": "results" }, { "id": 7, "type": "column", "value": "country" }, { "id": 6, "type": "column", "value": "raceid" }, { "id": 4, "type": "table", "value": "races" }, { "id": 8, "type": "value", "value": "Italy" }, { "id": 9, "type": "value", "value": "1000" }, { "id": 12, "type": "value", "value": "60" }, { "id": 13, "type": "value", "value": "1" }, { "id": 14, "type": "value", "value": ":" }, { "id": 15, "type": "value", "value": "." } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "B-VALUE" ]
12,647
baseball_1
spider:train_spider.json:3669
What are the name and id of the team with the most victories in 2008 postseason?
SELECT T2.name , T1.team_id_winner FROM postseason AS T1 JOIN team AS T2 ON T1.team_id_winner = T2.team_id_br WHERE T1.year = 2008 GROUP BY T1.team_id_winner ORDER BY count(*) DESC LIMIT 1;
[ "What", "are", "the", "name", "and", "i", "d", "of", "the", "team", "with", "the", "most", "victories", "in", "2008", "postseason", "?" ]
[ { "id": 0, "type": "column", "value": "team_id_winner" }, { "id": 2, "type": "table", "value": "postseason" }, { "id": 6, "type": "column", "value": "team_id_br" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "table", "value": "team" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "2008" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
12,648
olympics
bird:train.json:5039
How many people who are below 30 and participated in the summer season?
SELECT COUNT(T2.person_id) FROM games AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.games_id WHERE T1.season = 'Summer' AND T2.age < 30
[ "How", "many", "people", "who", "are", "below", "30", "and", "participated", "in", "the", "summer", "season", "?" ]
[ { "id": 1, "type": "table", "value": "games_competitor" }, { "id": 2, "type": "column", "value": "person_id" }, { "id": 4, "type": "column", "value": "games_id" }, { "id": 5, "type": "column", "value": "season" }, { "id": 6, "type": "value", "value": "Summer" }, { "id": 0, "type": "table", "value": "games" }, { "id": 7, "type": "column", "value": "age" }, { "id": 3, "type": "column", "value": "id" }, { "id": 8, "type": "value", "value": "30" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
12,649
real_estate_rentals
bird:test.json:1467
What search strings were entered by users who do not own any properties?
SELECT search_string FROM User_Searches EXCEPT SELECT T1.search_string FROM User_Searches AS T1 JOIN Properties AS T2 ON T1.user_id = T2.owner_user_id;
[ "What", "search", "strings", "were", "entered", "by", "users", "who", "do", "not", "own", "any", "properties", "?" ]
[ { "id": 0, "type": "table", "value": "user_searches" }, { "id": 1, "type": "column", "value": "search_string" }, { "id": 4, "type": "column", "value": "owner_user_id" }, { "id": 2, "type": "table", "value": "properties" }, { "id": 3, "type": "column", "value": "user_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1, 2 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "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", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
12,650
language_corpus
bird:train.json:5694
Calculate the average number of the word occurrences in which ‘system’ appeared as the first word in the pair.
SELECT AVG(T2.occurrences) FROM words AS T1 INNER JOIN biwords AS T2 ON T1.wid = T2.w1st WHERE T2.w1st = ( SELECT wid FROM words WHERE word = 'sistema' )
[ "Calculate", "the", "average", "number", "of", "the", "word", "occurrences", "in", "which", "‘", "system", "’", "appeared", "as", "the", "first", "word", "in", "the", "pair", "." ]
[ { "id": 3, "type": "column", "value": "occurrences" }, { "id": 1, "type": "table", "value": "biwords" }, { "id": 6, "type": "value", "value": "sistema" }, { "id": 0, "type": "table", "value": "words" }, { "id": 2, "type": "column", "value": "w1st" }, { "id": 5, "type": "column", "value": "word" }, { "id": 4, "type": "column", "value": "wid" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
12,651
address
bird:train.json:5119
Give the name and the position of the cbsa officer from the area with the zip code 45503.
SELECT T1.CBSA_name, T2.latitude, T2.longitude FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T2.zip_code = 45503 GROUP BY T1.CBSA_name, T2.latitude, T2.longitude
[ "Give", "the", "name", "and", "the", "position", "of", "the", "cbsa", "officer", "from", "the", "area", "with", "the", "zip", "code", "45503", "." ]
[ { "id": 0, "type": "column", "value": "cbsa_name" }, { "id": 2, "type": "column", "value": "longitude" }, { "id": 1, "type": "column", "value": "latitude" }, { "id": 4, "type": "table", "value": "zip_data" }, { "id": 5, "type": "column", "value": "zip_code" }, { "id": 6, "type": "value", "value": "45503" }, { "id": 3, "type": "table", "value": "cbsa" }, { "id": 7, "type": "column", "value": "cbsa" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
12,652
talkingdata
bird:train.json:1134
How many times is the number of active apps in the event that happened at 7:50:28 on 2016/5/2 than in the event that happened at 7:41:03 on 2016/5/2?
SELECT SUM(IIF(timestamp = '2016-05-02 7:50:28', 1, 0)) / SUM(IIF(timestamp = '2016-05-02 7:41:03', 1, 0)) AS num FROM events AS T1 INNER JOIN app_events AS T2 ON T1.event_id = T2.event_id WHERE T2.is_active = '1'
[ "How", "many", "times", "is", "the", "number", "of", "active", "apps", "in", "the", "event", "that", "happened", "at", "7:50:28", "on", "2016/5/2", "than", "in", "the", "event", "that", "happened", "at", "7:41:03", "on", "2016/5/2", "?" ]
[ { "id": 7, "type": "value", "value": "2016-05-02 7:50:28" }, { "id": 8, "type": "value", "value": "2016-05-02 7:41:03" }, { "id": 1, "type": "table", "value": "app_events" }, { "id": 2, "type": "column", "value": "is_active" }, { "id": 6, "type": "column", "value": "timestamp" }, { "id": 4, "type": "column", "value": "event_id" }, { "id": 0, "type": "table", "value": "events" }, { "id": 3, "type": "value", "value": "1" }, { "id": 5, "type": "value", "value": "0" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
12,653
farm
spider:train_spider.json:34
Show the years and the official names of the host cities of competitions.
SELECT T2.Year , T1.Official_Name FROM city AS T1 JOIN farm_competition AS T2 ON T1.City_ID = T2.Host_city_ID
[ "Show", "the", "years", "and", "the", "official", "names", "of", "the", "host", "cities", "of", "competitions", "." ]
[ { "id": 3, "type": "table", "value": "farm_competition" }, { "id": 1, "type": "column", "value": "official_name" }, { "id": 5, "type": "column", "value": "host_city_id" }, { "id": 4, "type": "column", "value": "city_id" }, { "id": 0, "type": "column", "value": "year" }, { "id": 2, "type": "table", "value": "city" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "B-TABLE", "O", "B-TABLE", "O" ]
12,654
formula_1
bird:dev.json:850
Please give the name of the race held on the circuits in Germany.
SELECT DISTINCT T2.name FROM circuits AS T1 INNER JOIN races AS T2 ON T2.circuitID = T1.circuitId WHERE T1.country = 'Germany'
[ "Please", "give", "the", "name", "of", "the", "race", "held", "on", "the", "circuits", "in", "Germany", "." ]
[ { "id": 5, "type": "column", "value": "circuitid" }, { "id": 1, "type": "table", "value": "circuits" }, { "id": 3, "type": "column", "value": "country" }, { "id": 4, "type": "value", "value": "Germany" }, { "id": 2, "type": "table", "value": "races" }, { "id": 0, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
12,655
european_football_2
bird:dev.json:1023
Among the players with an overall rating between 60 to 65, how many players whose going to be in all of your attack moves instead of defensing?
SELECT COUNT(id) FROM Player_Attributes WHERE overall_rating BETWEEN 60 AND 65 AND defensive_work_rate = 'low'
[ "Among", "the", "players", "with", "an", "overall", "rating", "between", "60", "to", "65", ",", "how", "many", "players", "whose", "going", "to", "be", "in", "all", "of", "your", "attack", "moves", "instead", "of", "defensing", "?" ]
[ { "id": 5, "type": "column", "value": "defensive_work_rate" }, { "id": 0, "type": "table", "value": "player_attributes" }, { "id": 2, "type": "column", "value": "overall_rating" }, { "id": 6, "type": "value", "value": "low" }, { "id": 1, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "60" }, { "id": 4, "type": "value", "value": "65" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
12,656
public_review_platform
bird:train.json:4017
Mention the number of businesses that have no any attribute.
SELECT COUNT(business_id) FROM Business_Attributes WHERE attribute_value IN ('none', 'no', 'false')
[ "Mention", "the", "number", "of", "businesses", "that", "have", "no", "any", "attribute", "." ]
[ { "id": 0, "type": "table", "value": "business_attributes" }, { "id": 1, "type": "column", "value": "attribute_value" }, { "id": 5, "type": "column", "value": "business_id" }, { "id": 4, "type": "value", "value": "false" }, { "id": 2, "type": "value", "value": "none" }, { "id": 3, "type": "value", "value": "no" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-COLUMN", "O" ]
12,657
formula_1
bird:dev.json:981
On what year did the youngest driver had his first qualifying race? Also state the name, date and time of the race.
SELECT T3.year, T3.name, T3.date, T3.time FROM qualifying AS T1 INNER JOIN drivers AS T2 on T1.driverId = T2.driverId INNER JOIN races AS T3 on T1.raceId = T3.raceId WHERE T1.driverId = ( SELECT driverId FROM drivers ORDER BY dob DESC LIMIT 1 ) ORDER BY T3.date ASC LIMIT 1
[ "On", "what", "year", "did", "the", "youngest", "driver", "had", "his", "first", "qualifying", "race", "?", "Also", "state", "the", "name", ",", "date", "and", "time", "of", "the", "race", "." ]
[ { "id": 6, "type": "table", "value": "qualifying" }, { "id": 5, "type": "column", "value": "driverid" }, { "id": 7, "type": "table", "value": "drivers" }, { "id": 8, "type": "column", "value": "raceid" }, { "id": 4, "type": "table", "value": "races" }, { "id": 0, "type": "column", "value": "year" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "date" }, { "id": 3, "type": "column", "value": "time" }, { "id": 9, "type": "column", "value": "dob" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O" ]
12,658
superstore
bird:train.json:2424
How many orders of O'Sullivan Plantations 2-Door Library in Landvery Oak in central superstore were shipped through the shipping mode with the fastest delivery speed?
SELECT COUNT(DISTINCT T1.`Order ID`) FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.`Product Name` = 'O''Sullivan Plantations 2-Door Library in Landvery Oak' AND T2.Region = 'Central' AND T1.`Ship Mode` = 'First Class'
[ "How", "many", "orders", "of", "O'Sullivan", "Plantations", "2", "-", "Door", "Library", "in", "Landvery", "Oak", "in", "central", "superstore", "were", "shipped", "through", "the", "shipping", "mode", "with", "the", "fastest", "delivery", "speed", "?" ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O" ]
12,659
public_review_platform
bird:train.json:4138
List the closing time and day of week of active businesses in Goodyear with stars greater than the 80% of average age of star rating.
SELECT DISTINCT T2.closing_time, T3.day_of_week FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T1.active = 'true' AND T1.city = 'Goodyear' AND T1.stars > ( SELECT AVG(stars) * 0.8 FROM Business WHERE active = 'true' AND city = 'Goodyear' )
[ "List", "the", "closing", "time", "and", "day", "of", "week", "of", "active", "businesses", "in", "Goodyear", "with", "stars", "greater", "than", "the", "80", "%", "of", "average", "age", "of", "star", "rating", "." ]
[ { "id": 4, "type": "table", "value": "business_hours" }, { "id": 0, "type": "column", "value": "closing_time" }, { "id": 1, "type": "column", "value": "day_of_week" }, { "id": 11, "type": "column", "value": "business_id" }, { "id": 3, "type": "table", "value": "business" }, { "id": 9, "type": "value", "value": "Goodyear" }, { "id": 5, "type": "column", "value": "day_id" }, { "id": 6, "type": "column", "value": "active" }, { "id": 10, "type": "column", "value": "stars" }, { "id": 2, "type": "table", "value": "days" }, { "id": 7, "type": "value", "value": "true" }, { "id": 8, "type": "column", "value": "city" }, { "id": 12, "type": "value", "value": "0.8" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "B-TABLE", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
12,660
match_season
spider:train_spider.json:1086
How many distinct colleges are associated with players from the team with name "Columbus Crew".
SELECT count(DISTINCT T1.College) FROM match_season AS T1 JOIN team AS T2 ON T1.Team = T2.Team_id WHERE T2.Name = "Columbus Crew"
[ "How", "many", "distinct", "colleges", "are", "associated", "with", "players", "from", "the", "team", "with", "name", "\"", "Columbus", "Crew", "\"", "." ]
[ { "id": 3, "type": "column", "value": "Columbus Crew" }, { "id": 0, "type": "table", "value": "match_season" }, { "id": 4, "type": "column", "value": "college" }, { "id": 6, "type": "column", "value": "team_id" }, { "id": 1, "type": "table", "value": "team" }, { "id": 2, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "team" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
12,661
cs_semester
bird:train.json:859
How many research assistants does Sauveur Skyme have?
SELECT COUNT(T1.student_id) FROM RA AS T1 INNER JOIN prof AS T2 ON T1.prof_id = T2.prof_id WHERE T2.first_name = 'Sauveur' AND T2.last_name = 'Skyme'
[ "How", "many", "research", "assistants", "does", "Sauveur", "Skyme", "have", "?" ]
[ { "id": 2, "type": "column", "value": "student_id" }, { "id": 4, "type": "column", "value": "first_name" }, { "id": 6, "type": "column", "value": "last_name" }, { "id": 3, "type": "column", "value": "prof_id" }, { "id": 5, "type": "value", "value": "Sauveur" }, { "id": 7, "type": "value", "value": "Skyme" }, { "id": 1, "type": "table", "value": "prof" }, { "id": 0, "type": "table", "value": "ra" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "B-VALUE", "O", "O" ]
12,662
shakespeare
bird:train.json:2962
Please list the IDs of the paragraphs in which the character "son to Tamora" appears.
SELECT T1.id FROM paragraphs AS T1 INNER JOIN characters AS T2 ON T1.character_id = T2.id WHERE T2.Description = 'son to Tamora'
[ "Please", "list", "the", "IDs", "of", "the", "paragraphs", "in", "which", "the", "character", "\"", "son", "to", "Tamora", "\"", "appears", "." ]
[ { "id": 4, "type": "value", "value": "son to Tamora" }, { "id": 5, "type": "column", "value": "character_id" }, { "id": 3, "type": "column", "value": "description" }, { "id": 1, "type": "table", "value": "paragraphs" }, { "id": 2, "type": "table", "value": "characters" }, { "id": 0, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O" ]
12,663
superstore
bird:train.json:2426
Among the orders with sales value of no less than 5,000 in west superstore, how many were bought by the customers in California?
SELECT COUNT(DISTINCT T1.`Order ID`) FROM west_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` INNER JOIN people AS T3 ON T3.`Customer ID` = T1.`Customer ID` WHERE T1.Sales > 5000 AND T3.State = 'California' AND T2.Region = 'West'
[ "Among", "the", "orders", "with", "sales", "value", "of", "no", "less", "than", "5,000", "in", "west", "superstore", ",", "how", "many", "were", "bought", "by", "the", "customers", "in", "California", "?" ]
[ { "id": 2, "type": "table", "value": "west_superstore" }, { "id": 4, "type": "column", "value": "Customer ID" }, { "id": 8, "type": "value", "value": "California" }, { "id": 11, "type": "column", "value": "Product ID" }, { "id": 1, "type": "column", "value": "Order ID" }, { "id": 3, "type": "table", "value": "product" }, { "id": 0, "type": "table", "value": "people" }, { "id": 9, "type": "column", "value": "region" }, { "id": 5, "type": "column", "value": "sales" }, { "id": 7, "type": "column", "value": "state" }, { "id": 6, "type": "value", "value": "5000" }, { "id": 10, "type": "value", "value": "West" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 21, 22 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [ 4 ] }, { "entity_id": 8, "token_idxs": [ 23 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 12 ] }, { "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", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
12,664
cre_Doc_and_collections
bird:test.json:700
What are the collection subset ids, names, and number of collections for each subset?
SELECT T2.Collection_Subset_ID , T1.Collection_Subset_Name , count(*) FROM Collection_Subsets AS T1 JOIN Collection_Subset_Members AS T2 ON T1.Collection_Subset_ID = T2.Collection_Subset_ID GROUP BY T2.Collection_Subset_ID;
[ "What", "are", "the", "collection", "subset", "ids", ",", "names", ",", "and", "number", "of", "collections", "for", "each", "subset", "?" ]
[ { "id": 3, "type": "table", "value": "collection_subset_members" }, { "id": 1, "type": "column", "value": "collection_subset_name" }, { "id": 0, "type": "column", "value": "collection_subset_id" }, { "id": 2, "type": "table", "value": "collection_subsets" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
12,666
art_1
bird:test.json:1309
List the year, location, and name of all paintings that are taller than 1000 in alphabetical order.
SELECT title , LOCATION , YEAR FROM paintings WHERE height_mm > 1000 ORDER BY title
[ "List", "the", "year", ",", "location", ",", "and", "name", "of", "all", "paintings", "that", "are", "taller", "than", "1000", "in", "alphabetical", "order", "." ]
[ { "id": 0, "type": "table", "value": "paintings" }, { "id": 4, "type": "column", "value": "height_mm" }, { "id": 2, "type": "column", "value": "location" }, { "id": 1, "type": "column", "value": "title" }, { "id": 3, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "1000" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "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", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
12,667
olympics
bird:train.json:4937
Show the name of the competitor id 90991.
SELECT T1.full_name FROM person AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.person_id WHERE T2.id = 90991
[ "Show", "the", "name", "of", "the", "competitor", "i", "d", "90991", "." ]
[ { "id": 2, "type": "table", "value": "games_competitor" }, { "id": 0, "type": "column", "value": "full_name" }, { "id": 5, "type": "column", "value": "person_id" }, { "id": 1, "type": "table", "value": "person" }, { "id": 4, "type": "value", "value": "90991" }, { "id": 3, "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": [ 6, 7 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "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", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
12,668
student_club
bird:dev.json:1468
Where is the hometown of Garrett Gerke?
SELECT T2.city FROM member AS T1 INNER JOIN zip_code AS T2 ON T2.zip_code = T1.zip WHERE T1.first_name = 'Garrett' AND T1.last_name = 'Gerke'
[ "Where", "is", "the", "hometown", "of", "Garrett", "Gerke", "?" ]
[ { "id": 5, "type": "column", "value": "first_name" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 2, "type": "table", "value": "zip_code" }, { "id": 3, "type": "column", "value": "zip_code" }, { "id": 6, "type": "value", "value": "Garrett" }, { "id": 1, "type": "table", "value": "member" }, { "id": 8, "type": "value", "value": "Gerke" }, { "id": 0, "type": "column", "value": "city" }, { "id": 4, "type": "column", "value": "zip" } ]
[ { "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": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 6 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-VALUE", "B-VALUE", "O" ]
12,669
beer_factory
bird:train.json:5285
Which brand of root beer has the lowest unit profit available to wholesalers? Indicate the ID of the customer that has the highest number of purchases of the said brand.
SELECT T3.BrandName, T2.CustomerID FROM rootbeer AS T1 INNER JOIN `transaction` AS T2 ON T1.RootBeerID = T2.RootBeerID INNER JOIN rootbeerbrand AS T3 ON T1.BrandID = T3.BrandID GROUP BY T3.BrandID ORDER BY T3.CurrentRetailPrice - T3.WholesaleCost, COUNT(T1.BrandID) DESC LIMIT 1
[ "Which", "brand", "of", "root", "beer", "has", "the", "lowest", "unit", "profit", "available", "to", "wholesalers", "?", "Indicate", "the", "ID", "of", "the", "customer", "that", "has", "the", "highest", "number", "of", "purchases", "of", "the", "said", "brand", "." ]
[ { "id": 6, "type": "column", "value": "currentretailprice" }, { "id": 3, "type": "table", "value": "rootbeerbrand" }, { "id": 7, "type": "column", "value": "wholesalecost" }, { "id": 5, "type": "table", "value": "transaction" }, { "id": 2, "type": "column", "value": "customerid" }, { "id": 8, "type": "column", "value": "rootbeerid" }, { "id": 1, "type": "column", "value": "brandname" }, { "id": 4, "type": "table", "value": "rootbeer" }, { "id": 0, "type": "column", "value": "brandid" } ]
[ { "entity_id": 0, "token_idxs": [ 30 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 19 ] }, { "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": [ 12 ] }, { "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", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
12,671
cinema
spider:train_spider.json:1943
Show all the locations with at least two cinemas with capacity above 300.
SELECT LOCATION FROM cinema WHERE capacity > 300 GROUP BY LOCATION HAVING count(*) >= 2
[ "Show", "all", "the", "locations", "with", "at", "least", "two", "cinemas", "with", "capacity", "above", "300", "." ]
[ { "id": 1, "type": "column", "value": "location" }, { "id": 2, "type": "column", "value": "capacity" }, { "id": 0, "type": "table", "value": "cinema" }, { "id": 3, "type": "value", "value": "300" }, { "id": 4, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
12,672
world_development_indicators
bird:train.json:2093
Please list the countries in Latin America & Caribbean with a note on the series code SM.POP.TOTL.
SELECT T1.SHORTNAME, T2.Description FROM Country AS T1 INNER JOIN CountryNotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T1.Region = 'Latin America & Caribbean' AND T2.Seriescode = 'SM.POP.TOTL'
[ "Please", "list", "the", "countries", "in", "Latin", "America", "&", "Caribbean", "with", "a", "note", "on", "the", "series", "code", "SM.POP.TOTL", "." ]
[ { "id": 6, "type": "value", "value": "Latin America & Caribbean" }, { "id": 3, "type": "table", "value": "countrynotes" }, { "id": 1, "type": "column", "value": "description" }, { "id": 4, "type": "column", "value": "countrycode" }, { "id": 8, "type": "value", "value": "SM.POP.TOTL" }, { "id": 7, "type": "column", "value": "seriescode" }, { "id": 0, "type": "column", "value": "shortname" }, { "id": 2, "type": "table", "value": "country" }, { "id": 5, "type": "column", "value": "region" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 5, 6, 7, 8 ] }, { "entity_id": 7, "token_idxs": [ 14, 15 ] }, { "entity_id": 8, "token_idxs": [ 16 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
12,673
book_1
bird:test.json:559
What is the maximum and the minimum sale price?
SELECT max(saleprice) , min(saleprice) FROM Book
[ "What", "is", "the", "maximum", "and", "the", "minimum", "sale", "price", "?" ]
[ { "id": 1, "type": "column", "value": "saleprice" }, { "id": 0, "type": "table", "value": "book" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7, 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
12,674
flight_1
spider:train_spider.json:374
What is the id and name of the employee with the highest salary?
SELECT eid , name FROM Employee ORDER BY salary DESC LIMIT 1
[ "What", "is", "the", "i", "d", "and", "name", "of", "the", "employee", "with", "the", "highest", "salary", "?" ]
[ { "id": 0, "type": "table", "value": "employee" }, { "id": 3, "type": "column", "value": "salary" }, { "id": 2, "type": "column", "value": "name" }, { "id": 1, "type": "column", "value": "eid" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 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", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
12,675
customers_card_transactions
spider:train_spider.json:721
What is the card type code with most number of cards?
SELECT card_type_code FROM Customers_cards GROUP BY card_type_code ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "card", "type", "code", "with", "most", "number", "of", "cards", "?" ]
[ { "id": 0, "type": "table", "value": "customers_cards" }, { "id": 1, "type": "column", "value": "card_type_code" } ]
[ { "entity_id": 0, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 1, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O" ]
12,676
hockey
bird:train.json:7817
Which team has the highest winning rate in year 2000? State the team ID and list down the birth country of it's players.
SELECT DISTINCT T3.tmID, T1.birthCountry FROM Master AS T1 INNER JOIN Scoring AS T2 ON T1.playerID = T2.playerID INNER JOIN ( SELECT year, tmID FROM Teams WHERE year = 2000 ORDER BY W / (W + L) DESC LIMIT 1 ) AS T3 ON T2.tmID = T3.tmID AND T2.year = T3.year
[ "Which", "team", "has", "the", "highest", "winning", "rate", "in", "year", "2000", "?", "State", "the", "team", "ID", "and", "list", "down", "the", "birth", "country", "of", "it", "'s", "players", "." ]
[ { "id": 1, "type": "column", "value": "birthcountry" }, { "id": 4, "type": "column", "value": "playerid" }, { "id": 3, "type": "table", "value": "scoring" }, { "id": 2, "type": "table", "value": "master" }, { "id": 5, "type": "table", "value": "teams" }, { "id": 0, "type": "column", "value": "tmid" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "2000" }, { "id": 8, "type": "column", "value": "w" }, { "id": 9, "type": "column", "value": "l" } ]
[ { "entity_id": 0, "token_idxs": [ 13, 14 ] }, { "entity_id": 1, "token_idxs": [ 19, 20 ] }, { "entity_id": 2, "token_idxs": [ 2, 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 24 ] }, { "entity_id": 5, "token_idxs": [ 1 ] }, { "entity_id": 6, "token_idxs": [ 8 ] }, { "entity_id": 7, "token_idxs": [ 9 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O" ]
12,677
soccer_2016
bird:train.json:1920
How many players bat with their left hands?
SELECT SUM(CASE WHEN T2.Batting_hand = 'Left-hand bat' THEN 1 ELSE 0 END) FROM Player AS T1 INNER JOIN Batting_Style AS T2 ON T1.Batting_hand = T2.Batting_Id
[ "How", "many", "players", "bat", "with", "their", "left", "hands", "?" ]
[ { "id": 1, "type": "table", "value": "batting_style" }, { "id": 6, "type": "value", "value": "Left-hand bat" }, { "id": 2, "type": "column", "value": "batting_hand" }, { "id": 3, "type": "column", "value": "batting_id" }, { "id": 0, "type": "table", "value": "player" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
12,678
movie_platform
bird:train.json:82
What's the percentage of the users who have rated "1" on the movie "When Will I Be Loved"?
SELECT CAST(SUM(CASE WHEN T1.rating_score = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_title = 'When Will I Be Loved'
[ "What", "'s", "the", "percentage", "of", "the", "users", "who", "have", "rated", "\"", "1", "\"", "on", "the", "movie", "\"", "When", "Will", "I", "Be", "Loved", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "When Will I Be Loved" }, { "id": 8, "type": "column", "value": "rating_score" }, { "id": 2, "type": "column", "value": "movie_title" }, { "id": 4, "type": "column", "value": "movie_id" }, { "id": 0, "type": "table", "value": "ratings" }, { "id": 1, "type": "table", "value": "movies" }, { "id": 5, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
12,679
csu_1
spider:train_spider.json:2356
report the total number of degrees granted between 1998 and 2002.
SELECT T1.campus , sum(T2.degrees) FROM campuses AS T1 JOIN degrees AS T2 ON T1.id = T2.campus WHERE T2.year >= 1998 AND T2.year <= 2002 GROUP BY T1.campus
[ "report", "the", "total", "number", "of", "degrees", "granted", "between", "1998", "and", "2002", "." ]
[ { "id": 1, "type": "table", "value": "campuses" }, { "id": 2, "type": "table", "value": "degrees" }, { "id": 3, "type": "column", "value": "degrees" }, { "id": 0, "type": "column", "value": "campus" }, { "id": 5, "type": "column", "value": "year" }, { "id": 6, "type": "value", "value": "1998" }, { "id": 7, "type": "value", "value": "2002" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
12,680
activity_1
spider:train_spider.json:6790
What are the ids of the students who are under 20 years old and are involved in at least one activity.
SELECT StuID FROM Participates_in INTERSECT SELECT StuID FROM Student WHERE age < 20
[ "What", "are", "the", "ids", "of", "the", "students", "who", "are", "under", "20", "years", "old", "and", "are", "involved", "in", "at", "least", "one", "activity", "." ]
[ { "id": 0, "type": "table", "value": "participates_in" }, { "id": 1, "type": "table", "value": "student" }, { "id": 2, "type": "column", "value": "stuid" }, { "id": 3, "type": "column", "value": "age" }, { "id": 4, "type": "value", "value": "20" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
12,681
student_loan
bird:train.json:4396
Which students that filed for bankruptcy are also in the foreign legion?
SELECT T2.name FROM enlist AS T1 INNER JOIN filed_for_bankrupcy AS T2 ON T1.`name` = T2.`name` WHERE T1.organ = 'foreign_legion'
[ "Which", "students", "that", "filed", "for", "bankruptcy", "are", "also", "in", "the", "foreign", "legion", "?" ]
[ { "id": 2, "type": "table", "value": "filed_for_bankrupcy" }, { "id": 4, "type": "value", "value": "foreign_legion" }, { "id": 1, "type": "table", "value": "enlist" }, { "id": 3, "type": "column", "value": "organ" }, { "id": 0, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
12,682
mondial_geo
bird:train.json:8475
Name the organizations with the most members.
SELECT T1.Name FROM organization AS T1 INNER JOIN isMember AS T2 ON T2.Country = T1.Country INNER JOIN country AS T3 ON T2.Country = T3.Code GROUP BY T1.Name ORDER BY COUNT(T3.Name) DESC LIMIT 1
[ "Name", "the", "organizations", "with", "the", "most", "members", "." ]
[ { "id": 2, "type": "table", "value": "organization" }, { "id": 3, "type": "table", "value": "ismember" }, { "id": 1, "type": "table", "value": "country" }, { "id": 4, "type": "column", "value": "country" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [ 0 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "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": [] } ]
[ "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
12,683
soccer_2016
bird:train.json:1813
What is the nationality of the 7th season Purple Cap winner?
SELECT T3.Country_Name FROM Season AS T1 INNER JOIN Player AS T2 ON T1.Man_of_the_Series = T2.Player_Id INNER JOIN Country AS T3 ON T2.Country_Name = T3.Country_Id WHERE T1.Season_Id = 7 AND T1.Purple_Cap IS NOT NULL
[ "What", "is", "the", "nationality", "of", "the", "7th", "season", "Purple", "Cap", "winner", "?" ]
[ { "id": 8, "type": "column", "value": "man_of_the_series" }, { "id": 0, "type": "column", "value": "country_name" }, { "id": 4, "type": "column", "value": "country_id" }, { "id": 7, "type": "column", "value": "purple_cap" }, { "id": 5, "type": "column", "value": "season_id" }, { "id": 9, "type": "column", "value": "player_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 2, "type": "table", "value": "season" }, { "id": 3, "type": "table", "value": "player" }, { "id": 6, "type": "value", "value": "7" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O" ]
12,684
law_episode
bird:train.json:1271
What are the names of the person that were not credited at the end of episode tt0629391?
SELECT T2.name FROM Credit AS T1 INNER JOIN Person AS T2 ON T2.person_id = T1.person_id WHERE T1.credited = 'false' AND T1.episode_id = 'tt0629391'
[ "What", "are", "the", "names", "of", "the", "person", "that", "were", "not", "credited", "at", "the", "end", "of", "episode", "tt0629391", "?" ]
[ { "id": 6, "type": "column", "value": "episode_id" }, { "id": 3, "type": "column", "value": "person_id" }, { "id": 7, "type": "value", "value": "tt0629391" }, { "id": 4, "type": "column", "value": "credited" }, { "id": 1, "type": "table", "value": "credit" }, { "id": 2, "type": "table", "value": "person" }, { "id": 5, "type": "value", "value": "false" }, { "id": 0, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
12,685
club_1
spider:train_spider.json:4264
Find the number of members of club "Pen and Paper Gaming".
SELECT count(*) FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t1.clubname = "Pen and Paper Gaming"
[ "Find", "the", "number", "of", "members", "of", "club", "\"", "Pen", "and", "Paper", "Gaming", "\"", "." ]
[ { "id": 2, "type": "column", "value": "Pen and Paper Gaming" }, { "id": 4, "type": "table", "value": "member_of_club" }, { "id": 1, "type": "column", "value": "clubname" }, { "id": 0, "type": "table", "value": "student" }, { "id": 6, "type": "column", "value": "clubid" }, { "id": 5, "type": "column", "value": "stuid" }, { "id": 3, "type": "table", "value": "club" } ]
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[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
12,686
shakespeare
bird:train.json:2994
In "Twelfth Night, Or What You Will", what is the description of the chapter in 2nd scene, Act 2?
SELECT T2.Description FROM works AS T1 INNER JOIN chapters AS T2 ON T1.id = T2.work_id WHERE T1.LongTitle = 'Twelfth Night, Or What You Will' AND T2.Scene = 2 AND T2.Act = 2
[ "In", "\"", "Twelfth", "Night", ",", "Or", "What", "You", "Will", "\"", ",", "what", "is", "the", "description", "of", "the", "chapter", "in", "2nd", "scene", ",", "Act", "2", "?" ]
[ { "id": 6, "type": "value", "value": "Twelfth Night, Or What You Will" }, { "id": 0, "type": "column", "value": "description" }, { "id": 5, "type": "column", "value": "longtitle" }, { "id": 2, "type": "table", "value": "chapters" }, { "id": 4, "type": "column", "value": "work_id" }, { "id": 1, "type": "table", "value": "works" }, { "id": 7, "type": "column", "value": "scene" }, { "id": 9, "type": "column", "value": "act" }, { "id": 3, "type": "column", "value": "id" }, { "id": 8, "type": "value", "value": "2" } ]
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[ "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-VALUE", "O" ]
12,687
pilot_1
bird:test.json:1139
How many pilots who are older than 40 or younger than 30?
SELECT count(pilot_name) FROM pilotskills ORDER BY age > 40 OR age < 30
[ "How", "many", "pilots", "who", "are", "older", "than", "40", "or", "younger", "than", "30", "?" ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "pilot_name" }, { "id": 2, "type": "column", "value": "age" }, { "id": 3, "type": "value", "value": "40" }, { "id": 4, "type": "value", "value": "30" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O" ]
12,688
department_store
spider:train_spider.json:4712
Give the id and product type of the product with the lowest price.
SELECT product_id , product_type_code FROM products ORDER BY product_price LIMIT 1
[ "Give", "the", "i", "d", "and", "product", "type", "of", "the", "product", "with", "the", "lowest", "price", "." ]
[ { "id": 2, "type": "column", "value": "product_type_code" }, { "id": 3, "type": "column", "value": "product_price" }, { "id": 1, "type": "column", "value": "product_id" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "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", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
12,689
network_2
spider:train_spider.json:4476
Who is the person that has no friend?
SELECT name FROM person EXCEPT SELECT name FROM PersonFriend
[ "Who", "is", "the", "person", "that", "has", "no", "friend", "?" ]
[ { "id": 1, "type": "table", "value": "personfriend" }, { "id": 0, "type": "table", "value": "person" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "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": [] }, { "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" ]
12,690
book_1
bird:test.json:542
What is the title and purchase price of the book that has the highest total order amount?
SELECT T2.title , T2.PurchasePrice FROM Books_Order AS T1 JOIN BOOk AS T2 ON T1.isbn = T2.isbn GROUP BY T1.isbn ORDER BY sum(amount) DESC LIMIT 1
[ "What", "is", "the", "title", "and", "purchase", "price", "of", "the", "book", "that", "has", "the", "highest", "total", "order", "amount", "?" ]
[ { "id": 2, "type": "column", "value": "purchaseprice" }, { "id": 3, "type": "table", "value": "books_order" }, { "id": 5, "type": "column", "value": "amount" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "column", "value": "isbn" }, { "id": 4, "type": "table", "value": "book" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "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", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
12,691
activity_1
spider:train_spider.json:6791
What is the first and last name of the student participating in the most activities?
SELECT T1.fname , T1.lname FROM Student AS T1 JOIN Participates_in AS T2 ON T1.StuID = T2.StuID GROUP BY T1.StuID ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "first", "and", "last", "name", "of", "the", "student", "participating", "in", "the", "most", "activities", "?" ]
[ { "id": 4, "type": "table", "value": "participates_in" }, { "id": 3, "type": "table", "value": "student" }, { "id": 0, "type": "column", "value": "stuid" }, { "id": 1, "type": "column", "value": "fname" }, { "id": 2, "type": "column", "value": "lname" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O" ]
12,692
regional_sales
bird:train.json:2642
Please list the customer names whose order quantity was more than 5 on 6/1/2018.
SELECT T FROM ( SELECT DISTINCT CASE WHEN SUM(T1.`Order Quantity`) > 5 THEN T2.`Customer Names` END AS T FROM `Sales Orders` T1 INNER JOIN Customers T2 ON T2.CustomerID = T1._CustomerID WHERE T1.OrderDate = '6/1/18' GROUP BY T1._CustomerID ) WHERE T IS NOT NULL
[ "Please", "list", "the", "customer", "names", "whose", "order", "quantity", "was", "more", "than", "5", "on", "6/1/2018", "." ]
[ { "id": 7, "type": "column", "value": "Customer Names" }, { "id": 9, "type": "column", "value": "Order Quantity" }, { "id": 2, "type": "table", "value": "Sales Orders" }, { "id": 1, "type": "column", "value": "_customerid" }, { "id": 6, "type": "column", "value": "customerid" }, { "id": 3, "type": "table", "value": "customers" }, { "id": 4, "type": "column", "value": "orderdate" }, { "id": 5, "type": "value", "value": "6/1/18" }, { "id": 0, "type": "column", "value": "t" }, { "id": 8, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 4 ] }, { "entity_id": 8, "token_idxs": [ 11 ] }, { "entity_id": 9, "token_idxs": [ 7 ] }, { "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", "B-COLUMN", "B-TABLE", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
12,693
movie_3
bird:train.json:9280
What is the title of the animated films that have the shortest length?
SELECT T1.title FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T2.category_id = T3.category_id ORDER BY T1.length LIMIT 1
[ "What", "is", "the", "title", "of", "the", "animated", "films", "that", "have", "the", "shortest", "length", "?" ]
[ { "id": 4, "type": "table", "value": "film_category" }, { "id": 5, "type": "column", "value": "category_id" }, { "id": 1, "type": "table", "value": "category" }, { "id": 6, "type": "column", "value": "film_id" }, { "id": 2, "type": "column", "value": "length" }, { "id": 0, "type": "column", "value": "title" }, { "id": 3, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "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", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
12,694
tracking_share_transactions
spider:train_spider.json:5848
Show all date and share count of transactions.
SELECT date_of_transaction , share_count FROM TRANSACTIONS
[ "Show", "all", "date", "and", "share", "count", "of", "transactions", "." ]
[ { "id": 1, "type": "column", "value": "date_of_transaction" }, { "id": 0, "type": "table", "value": "transactions" }, { "id": 2, "type": "column", "value": "share_count" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 4, 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "B-TABLE", "O" ]
12,695
simpson_episodes
bird:train.json:4195
State the name of director for the 'Treehouse of Horror XIX' episode.
SELECT T2.person FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Treehouse of Horror XIX' AND T2.role = 'director';
[ "State", "the", "name", "of", "director", "for", "the", "'", "Treehouse", "of", "Horror", "XIX", "'", "episode", "." ]
[ { "id": 5, "type": "value", "value": "Treehouse of Horror XIX" }, { "id": 3, "type": "column", "value": "episode_id" }, { "id": 7, "type": "value", "value": "director" }, { "id": 1, "type": "table", "value": "episode" }, { "id": 0, "type": "column", "value": "person" }, { "id": 2, "type": "table", "value": "credit" }, { "id": 4, "type": "column", "value": "title" }, { "id": 6, "type": "column", "value": "role" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 13 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 0 ] }, { "entity_id": 5, "token_idxs": [ 8, 9, 10, 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 4 ] }, { "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-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
12,696
party_people
spider:train_spider.json:2070
Count the number of party events.
SELECT count(*) FROM party_events
[ "Count", "the", "number", "of", "party", "events", "." ]
[ { "id": 0, "type": "table", "value": "party_events" } ]
[ { "entity_id": 0, "token_idxs": [ 4, 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
12,697
small_bank_1
spider:train_spider.json:1806
Find the total saving balance for each account name.
SELECT sum(T2.balance) , T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid GROUP BY T1.name
[ "Find", "the", "total", "saving", "balance", "for", "each", "account", "name", "." ]
[ { "id": 1, "type": "table", "value": "accounts" }, { "id": 2, "type": "table", "value": "savings" }, { "id": 3, "type": "column", "value": "balance" }, { "id": 4, "type": "column", "value": "custid" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "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", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
12,698
college_2
spider:train_spider.json:1398
Find the total credits of courses provided by different department.
SELECT sum(credits) , dept_name FROM course GROUP BY dept_name
[ "Find", "the", "total", "credits", "of", "courses", "provided", "by", "different", "department", "." ]
[ { "id": 1, "type": "column", "value": "dept_name" }, { "id": 2, "type": "column", "value": "credits" }, { "id": 0, "type": "table", "value": "course" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
12,699
public_review_platform
bird:train.json:3849
How many users have joined Yelp since the year 2012?
SELECT COUNT(user_id) FROM Users WHERE user_yelping_since_year = 2012
[ "How", "many", "users", "have", "joined", "Yelp", "since", "the", "year", "2012", "?" ]
[ { "id": 1, "type": "column", "value": "user_yelping_since_year" }, { "id": 3, "type": "column", "value": "user_id" }, { "id": 0, "type": "table", "value": "users" }, { "id": 2, "type": "value", "value": "2012" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5, 6, 7, 8 ] }, { "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-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
12,700
book_press
bird:test.json:2004
What are the 3 best selling books? Show their titles, author names, and press names.
SELECT t1.name , t2.title , t3.name FROM author AS t1 JOIN book AS t2 ON t1.author_id = t2.author_id JOIN press AS t3 ON t2.press_id = t3.press_id ORDER BY t2.sale_amount DESC LIMIT 3
[ "What", "are", "the", "3", "best", "selling", "books", "?", "Show", "their", "titles", ",", "author", "names", ",", "and", "press", "names", "." ]
[ { "id": 3, "type": "column", "value": "sale_amount" }, { "id": 7, "type": "column", "value": "author_id" }, { "id": 6, "type": "column", "value": "press_id" }, { "id": 4, "type": "table", "value": "author" }, { "id": 1, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "press" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "table", "value": "book" } ]
[ { "entity_id": 0, "token_idxs": [ 17 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 16 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
12,702
music_2
spider:train_spider.json:5232
Find all the songs that do not have a lead vocal.
SELECT DISTINCT title FROM vocals AS t1 JOIN songs AS t2 ON t1.songid = t2.songid EXCEPT SELECT t2.title FROM vocals AS t1 JOIN songs AS t2 ON t1.songid = t2.songid WHERE TYPE = "lead"
[ "Find", "all", "the", "songs", "that", "do", "not", "have", "a", "lead", "vocal", "." ]
[ { "id": 1, "type": "table", "value": "vocals" }, { "id": 5, "type": "column", "value": "songid" }, { "id": 0, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "songs" }, { "id": 3, "type": "column", "value": "type" }, { "id": 4, "type": "column", "value": "lead" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "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", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O" ]
12,703
club_1
spider:train_spider.json:4291
Which clubs are located at "AKW"? Return the club names.
SELECT clubname FROM club WHERE clublocation = "AKW"
[ "Which", "clubs", "are", "located", "at", "\"", "AKW", "\"", "?", "Return", "the", "club", "names", "." ]
[ { "id": 2, "type": "column", "value": "clublocation" }, { "id": 1, "type": "column", "value": "clubname" }, { "id": 0, "type": "table", "value": "club" }, { "id": 3, "type": "column", "value": "AKW" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 1, 2, 3 ] }, { "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", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
12,704
music_2
spider:train_spider.json:5231
What are the types of vocals that the musician with the first name "Solveig" played in the song "A Bar in Amsterdam"?
SELECT TYPE FROM vocals AS T1 JOIN songs AS T2 ON T1.songid = T2.songid JOIN band AS T3 ON T1.bandmate = T3.id WHERE T3.firstname = "Solveig" AND T2.title = "A Bar In Amsterdam"
[ "What", "are", "the", "types", "of", "vocals", "that", "the", "musician", "with", "the", "first", "name", "\"", "Solveig", "\"", "played", "in", "the", "song", "\"", "A", "Bar", "in", "Amsterdam", "\"", "?" ]
[ { "id": 9, "type": "column", "value": "A Bar In Amsterdam" }, { "id": 6, "type": "column", "value": "firstname" }, { "id": 4, "type": "column", "value": "bandmate" }, { "id": 7, "type": "column", "value": "Solveig" }, { "id": 2, "type": "table", "value": "vocals" }, { "id": 10, "type": "column", "value": "songid" }, { "id": 3, "type": "table", "value": "songs" }, { "id": 8, "type": "column", "value": "title" }, { "id": 0, "type": "column", "value": "type" }, { "id": 1, "type": "table", "value": "band" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 22, 23 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 19 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 11, 12 ] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 21, 24 ] }, { "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-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O" ]
12,705
authors
bird:train.json:3554
Provide any four valid Journal ID along with short name and full name of the papers which were made in 2013.
SELECT DISTINCT T2.JournalId, T1.ShortName, T1.FullName FROM Journal AS T1 INNER JOIN Paper AS T2 ON T1.Id = T2.JournalId WHERE T2.Year = 2013 AND T2.JournalId != 0 AND T2.JournalId != -1 LIMIT 4
[ "Provide", "any", "four", "valid", "Journal", "ID", "along", "with", "short", "name", "and", "full", "name", "of", "the", "papers", "which", "were", "made", "in", "2013", "." ]
[ { "id": 0, "type": "column", "value": "journalid" }, { "id": 1, "type": "column", "value": "shortname" }, { "id": 2, "type": "column", "value": "fullname" }, { "id": 3, "type": "table", "value": "journal" }, { "id": 4, "type": "table", "value": "paper" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "2013" }, { "id": 5, "type": "column", "value": "id" }, { "id": 9, "type": "value", "value": "-1" }, { "id": 8, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8, 9 ] }, { "entity_id": 2, "token_idxs": [ 11, 12 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 20 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O" ]
12,706
entrepreneur
spider:train_spider.json:2275
What are the names of entrepreneurs whose investor is not "Rachel Elnaugh"?
SELECT T2.Name FROM entrepreneur AS T1 JOIN people AS T2 ON T1.People_ID = T2.People_ID WHERE T1.Investor != "Rachel Elnaugh"
[ "What", "are", "the", "names", "of", "entrepreneurs", "whose", "investor", "is", "not", "\"", "Rachel", "Elnaugh", "\"", "?" ]
[ { "id": 4, "type": "column", "value": "Rachel Elnaugh" }, { "id": 1, "type": "table", "value": "entrepreneur" }, { "id": 5, "type": "column", "value": "people_id" }, { "id": 3, "type": "column", "value": "investor" }, { "id": 2, "type": "table", "value": "people" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "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", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
12,707
regional_sales
bird:train.json:2600
List the store located cities with regions in no water area of California state.
SELECT DISTINCT T2.`City Name` FROM Regions AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StateCode = T1.StateCode WHERE T2.State = 'California' AND T2.`Water Area` = '0'
[ "List", "the", "store", "located", "cities", "with", "regions", "in", "no", "water", "area", "of", "California", "state", "." ]
[ { "id": 2, "type": "table", "value": "Store Locations" }, { "id": 5, "type": "value", "value": "California" }, { "id": 6, "type": "column", "value": "Water Area" }, { "id": 0, "type": "column", "value": "City Name" }, { "id": 3, "type": "column", "value": "statecode" }, { "id": 1, "type": "table", "value": "regions" }, { "id": 4, "type": "column", "value": "state" }, { "id": 7, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 2, 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entity_id": 5, "token_idxs": [ 12 ] }, { "entity_id": 6, "token_idxs": [ 9, 10 ] }, { "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", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "B-COLUMN", "O" ]
12,708
cre_Docs_and_Epenses
spider:train_spider.json:6404
What are the ids and names for each of the documents?
SELECT document_id , document_name FROM Documents
[ "What", "are", "the", "ids", "and", "names", "for", "each", "of", "the", "documents", "?" ]
[ { "id": 2, "type": "column", "value": "document_name" }, { "id": 1, "type": "column", "value": "document_id" }, { "id": 0, "type": "table", "value": "documents" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
12,709
synthea
bird:train.json:1518
Describe the condition of patient Wilmer Koepp.
SELECT T2.DESCRIPTION FROM patients AS T1 INNER JOIN conditions AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Wilmer' AND T1.last = 'Koepp'
[ "Describe", "the", "condition", "of", "patient", "Wilmer", "Koepp", "." ]
[ { "id": 0, "type": "column", "value": "description" }, { "id": 2, "type": "table", "value": "conditions" }, { "id": 1, "type": "table", "value": "patients" }, { "id": 3, "type": "column", "value": "patient" }, { "id": 5, "type": "value", "value": "Wilmer" }, { "id": 4, "type": "column", "value": "first" }, { "id": 7, "type": "value", "value": "Koepp" }, { "id": 6, "type": "column", "value": "last" } ]
[ { "entity_id": 0, "token_idxs": [ 0 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 6 ] }, { "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-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "B-VALUE", "B-VALUE", "O" ]
12,710
public_review_platform
bird:train.json:4117
What is the average number of stars for businesses in the Obstetricians & Gynecologists category?
SELECT CAST(SUM(T1.stars) AS REAL) / COUNT(T1.business_id) FROM Business AS T1 INNER JOIN Business_Categories AS T2 ON T1.business_id = T2.business_id INNER JOIN Categories AS T3 ON T2.category_id = T3.category_id WHERE T3.category_name = 'Obstetricians & Gynecologists'
[ "What", "is", "the", "average", "number", "of", "stars", "for", "businesses", "in", "the", "Obstetricians", "&", "Gynecologists", "category", "?" ]
[ { "id": 2, "type": "value", "value": "Obstetricians & Gynecologists" }, { "id": 4, "type": "table", "value": "business_categories" }, { "id": 1, "type": "column", "value": "category_name" }, { "id": 5, "type": "column", "value": "category_id" }, { "id": 6, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "categories" }, { "id": 3, "type": "table", "value": "business" }, { "id": 7, "type": "column", "value": "stars" } ]
[ { "entity_id": 0, "token_idxs": [ 14 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11, 12, 13 ] }, { "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": [ 6 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O" ]
12,711
student_club
bird:dev.json:1397
On average, how much did the Student_Club spend on food for the typical event in the past?
SELECT SUM(spent) / COUNT(spent) FROM budget WHERE category = 'Food' AND event_status = 'Closed'
[ "On", "average", ",", "how", "much", "did", "the", "Student_Club", "spend", "on", "food", "for", "the", "typical", "event", "in", "the", "past", "?" ]
[ { "id": 3, "type": "column", "value": "event_status" }, { "id": 1, "type": "column", "value": "category" }, { "id": 0, "type": "table", "value": "budget" }, { "id": 4, "type": "value", "value": "Closed" }, { "id": 5, "type": "column", "value": "spent" }, { "id": 2, "type": "value", "value": "Food" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 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", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
12,712
language_corpus
bird:train.json:5755
How many words has the appearance times greater than 10?
SELECT COUNT(w1st) AS countwords FROM biwords WHERE occurrences > 10
[ "How", "many", "words", "has", "the", "appearance", "times", "greater", "than", "10", "?" ]
[ { "id": 1, "type": "column", "value": "occurrences" }, { "id": 0, "type": "table", "value": "biwords" }, { "id": 3, "type": "column", "value": "w1st" }, { "id": 2, "type": "value", "value": "10" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "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", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
12,714
mondial_geo
bird:train.json:8399
What's the number of infant mortality in Switzerland in a year?
SELECT T2.Infant_Mortality * T1.Population * T2.Population_Growth FROM country AS T1 INNER JOIN population AS T2 ON T1.Code = T2.Country WHERE T1.Name = 'Switzerland'
[ "What", "'s", "the", "number", "of", "infant", "mortality", "in", "Switzerland", "in", "a", "year", "?" ]
[ { "id": 4, "type": "column", "value": "population_growth" }, { "id": 7, "type": "column", "value": "infant_mortality" }, { "id": 3, "type": "value", "value": "Switzerland" }, { "id": 1, "type": "table", "value": "population" }, { "id": 8, "type": "column", "value": "population" }, { "id": 0, "type": "table", "value": "country" }, { "id": 6, "type": "column", "value": "country" }, { "id": 2, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "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": [ 5, 6 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O", "O", "O" ]
12,715
customers_and_orders
bird:test.json:298
How many orders have each order status code?
SELECT order_status_code , count(*) FROM Customer_orders GROUP BY order_status_code
[ "How", "many", "orders", "have", "each", "order", "status", "code", "?" ]
[ { "id": 1, "type": "column", "value": "order_status_code" }, { "id": 0, "type": "table", "value": "customer_orders" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5, 6, 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
12,716
cre_Doc_Control_Systems
spider:train_spider.json:2103
What is the shipping agent code of shipping agent UPS?
SELECT shipping_agent_code FROM Ref_Shipping_Agents WHERE shipping_agent_name = "UPS";
[ "What", "is", "the", "shipping", "agent", "code", "of", "shipping", "agent", "UPS", "?" ]
[ { "id": 0, "type": "table", "value": "ref_shipping_agents" }, { "id": 1, "type": "column", "value": "shipping_agent_code" }, { "id": 2, "type": "column", "value": "shipping_agent_name" }, { "id": 3, "type": "column", "value": "UPS" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 2, "token_idxs": [ 7, 8 ] }, { "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-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
12,717
works_cycles
bird:train.json:7162
What's the profit for the Freewheel?
SELECT T1.LastReceiptCost - T1.StandardPrice FROM ProductVendor AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Name = 'Freewheel'
[ "What", "'s", "the", "profit", "for", "the", "Freewheel", "?" ]
[ { "id": 4, "type": "column", "value": "lastreceiptcost" }, { "id": 0, "type": "table", "value": "productvendor" }, { "id": 5, "type": "column", "value": "standardprice" }, { "id": 3, "type": "value", "value": "Freewheel" }, { "id": 6, "type": "column", "value": "productid" }, { "id": 1, "type": "table", "value": "product" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "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-TABLE", "O", "O", "B-VALUE", "O" ]
12,718
college_1
spider:train_spider.json:3294
What are the first names of all students taking accoutning and Computer Information Systems classes?
SELECT T1.stu_fname FROM student AS T1 JOIN enroll AS T2 ON T1.stu_num = T2.stu_num JOIN CLASS AS T3 ON T2.class_code = T3.class_code JOIN course AS T4 ON T3.crs_code = T4.crs_code JOIN department AS T5 ON T5.dept_code = T4.dept_code WHERE T5.dept_name = 'Accounting' INTERSECT SELECT T1.stu_fname FROM student AS T1 JOIN enroll AS T2 ON T1.stu_num = T2.stu_num JOIN CLASS AS T3 ON T2.class_code = T3.class_code JOIN course AS T4 ON T3.crs_code = T4.crs_code JOIN department AS T5 ON T5.dept_code = T4.dept_code WHERE T5.dept_name = 'Computer Info. Systems'
[ "What", "are", "the", "first", "names", "of", "all", "students", "taking", "accoutning", "and", "Computer", "Information", "Systems", "classes", "?" ]
[ { "id": 4, "type": "value", "value": "Computer Info. Systems" }, { "id": 1, "type": "table", "value": "department" }, { "id": 3, "type": "value", "value": "Accounting" }, { "id": 11, "type": "column", "value": "class_code" }, { "id": 0, "type": "column", "value": "stu_fname" }, { "id": 2, "type": "column", "value": "dept_name" }, { "id": 6, "type": "column", "value": "dept_code" }, { "id": 8, "type": "column", "value": "crs_code" }, { "id": 9, "type": "table", "value": "student" }, { "id": 12, "type": "column", "value": "stu_num" }, { "id": 5, "type": "table", "value": "course" }, { "id": 10, "type": "table", "value": "enroll" }, { "id": 7, "type": "table", "value": "class" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O" ]
12,719
race_track
spider:train_spider.json:775
Show all track names that have had no races.
SELECT name FROM track WHERE track_id NOT IN (SELECT track_id FROM race)
[ "Show", "all", "track", "names", "that", "have", "had", "no", "races", "." ]
[ { "id": 2, "type": "column", "value": "track_id" }, { "id": 0, "type": "table", "value": "track" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "table", "value": "race" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "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, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
12,720
network_2
spider:train_spider.json:4479
What is the name of the person who has the oldest average age for their friends, and what is that average age?
SELECT T2.name , avg(T1.age) FROM Person AS T1 JOIN PersonFriend AS T2 ON T1.name = T2.friend GROUP BY T2.name ORDER BY avg(T1.age) DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "person", "who", "has", "the", "oldest", "average", "age", "for", "their", "friends", ",", "and", "what", "is", "that", "average", "age", "?" ]
[ { "id": 2, "type": "table", "value": "personfriend" }, { "id": 1, "type": "table", "value": "person" }, { "id": 4, "type": "column", "value": "friend" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "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", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
12,721
soccer_2016
bird:train.json:1988
What are the teams that played in a match with the point of winning margin of 38 on April 30, 2009?
SELECT T1.Team_Name FROM Team AS T1 INNER JOIN Match AS T2 ON T1.Team_Id = T2.Team_1 WHERE T2.win_margin = 38 AND match_date = '2009-04-30'
[ "What", "are", "the", "teams", "that", "played", "in", "a", "match", "with", "the", "point", "of", "winning", "margin", "of", "38", "on", "April", "30", ",", "2009", "?" ]
[ { "id": 5, "type": "column", "value": "win_margin" }, { "id": 7, "type": "column", "value": "match_date" }, { "id": 8, "type": "value", "value": "2009-04-30" }, { "id": 0, "type": "column", "value": "team_name" }, { "id": 3, "type": "column", "value": "team_id" }, { "id": 4, "type": "column", "value": "team_1" }, { "id": 2, "type": "table", "value": "match" }, { "id": 1, "type": "table", "value": "team" }, { "id": 6, "type": "value", "value": "38" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O" ]
12,722
hockey
bird:train.json:7737
What are the awards won by the coach who coached the team with the most number of victories of all time? Indicate the choach ID.
SELECT DISTINCT T2.coachID, T1.award FROM AwardsCoaches AS T1 INNER JOIN Coaches AS T2 ON T1.coachID = T2.coachID GROUP BY T2.coachID, T1.award ORDER BY SUM(T2.w) DESC LIMIT 1
[ "What", "are", "the", "awards", "won", "by", "the", "coach", "who", "coached", "the", "team", "with", "the", "most", "number", "of", "victories", "of", "all", "time", "?", "Indicate", "the", "choach", "ID", "." ]
[ { "id": 2, "type": "table", "value": "awardscoaches" }, { "id": 0, "type": "column", "value": "coachid" }, { "id": 3, "type": "table", "value": "coaches" }, { "id": 1, "type": "column", "value": "award" }, { "id": 4, "type": "column", "value": "w" } ]
[ { "entity_id": 0, "token_idxs": [ 24, 25 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "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-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
12,723
european_football_2
bird:dev.json:1133
How many football players born after the 1990s have the first name "Aaron"?
SELECT COUNT(id) FROM Player WHERE birthday > '1990' AND player_name LIKE 'Aaron%'
[ "How", "many", "football", "players", "born", "after", "the", "1990s", "have", "the", "first", "name", "\"", "Aaron", "\"", "?" ]
[ { "id": 4, "type": "column", "value": "player_name" }, { "id": 2, "type": "column", "value": "birthday" }, { "id": 0, "type": "table", "value": "player" }, { "id": 5, "type": "value", "value": "Aaron%" }, { "id": 3, "type": "value", "value": "1990" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "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", "B-VALUE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
12,724
book_publishing_company
bird:train.json:201
What is the highest level of job to get to for the employee who got hired the earliest?
SELECT T2.max_lvl FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id ORDER BY T1.hire_date LIMIT 1
[ "What", "is", "the", "highest", "level", "of", "job", "to", "get", "to", "for", "the", "employee", "who", "got", "hired", "the", "earliest", "?" ]
[ { "id": 3, "type": "column", "value": "hire_date" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 0, "type": "column", "value": "max_lvl" }, { "id": 4, "type": "column", "value": "job_id" }, { "id": 2, "type": "table", "value": "jobs" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 15, 16 ] }, { "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", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
12,725
art_1
bird:test.json:1243
What are first names of the artists with oil paintings in gallery 241?
SELECT DISTINCT T1.fname FROM artists AS T1 JOIN paintings AS T2 ON T1.artistID = T2.painterID WHERE T2.medium = "oil" AND LOCATION = "Gallery 241"
[ "What", "are", "first", "names", "of", "the", "artists", "with", "oil", "paintings", "in", "gallery", "241", "?" ]
[ { "id": 8, "type": "column", "value": "Gallery 241" }, { "id": 2, "type": "table", "value": "paintings" }, { "id": 4, "type": "column", "value": "painterid" }, { "id": 3, "type": "column", "value": "artistid" }, { "id": 7, "type": "column", "value": "location" }, { "id": 1, "type": "table", "value": "artists" }, { "id": 5, "type": "column", "value": "medium" }, { "id": 0, "type": "column", "value": "fname" }, { "id": 6, "type": "column", "value": "oil" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 8 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 11, 12 ] }, { "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", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
12,726
cre_Doc_Tracking_DB
spider:train_spider.json:4204
Show all role codes and the number of employees in each role.
SELECT role_code , count(*) FROM Employees GROUP BY role_code
[ "Show", "all", "role", "codes", "and", "the", "number", "of", "employees", "in", "each", "role", "." ]
[ { "id": 0, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "role_code" } ]
[ { "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" ]
12,727
legislator
bird:train.json:4855
State all the district that Benjamin Contee has served before.
SELECT T2.district FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.first_name = 'Benjamin' AND T1.last_name = 'Contee'
[ "State", "all", "the", "district", "that", "Benjamin", "Contee", "has", "served", "before", "." ]
[ { "id": 2, "type": "table", "value": "historical-terms" }, { "id": 3, "type": "column", "value": "bioguide_id" }, { "id": 1, "type": "table", "value": "historical" }, { "id": 5, "type": "column", "value": "first_name" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 0, "type": "column", "value": "district" }, { "id": 4, "type": "column", "value": "bioguide" }, { "id": 6, "type": "value", "value": "Benjamin" }, { "id": 8, "type": "value", "value": "Contee" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-VALUE", "O", "O", "O", "O" ]
12,728
aan_1
bird:test.json:1013
How many papers does Mckeown , Kathleen cite ?
select count(*) from citation as t1 join author_list as t2 on t1.paper_id = t2.paper_id join author as t3 on t2.author_id = t3.author_id where t3.name = "mckeown , kathleen"
[ "How", "many", "papers", "does", "Mckeown", ",", "Kathleen", "cite", "?" ]
[ { "id": 2, "type": "column", "value": "mckeown , kathleen" }, { "id": 4, "type": "table", "value": "author_list" }, { "id": 5, "type": "column", "value": "author_id" }, { "id": 3, "type": "table", "value": "citation" }, { "id": 6, "type": "column", "value": "paper_id" }, { "id": 0, "type": "table", "value": "author" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 2 ] }, { "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", "I-COLUMN", "I-COLUMN", "O", "O" ]
12,729
toxicology
bird:dev.json:313
How many atoms belong to molecule id TR001?
SELECT COUNT(T.atom_id) FROM atom AS T WHERE T.molecule_id = 'TR001'
[ "How", "many", "atoms", "belong", "to", "molecule", "i", "d", "TR001", "?" ]
[ { "id": 1, "type": "column", "value": "molecule_id" }, { "id": 3, "type": "column", "value": "atom_id" }, { "id": 2, "type": "value", "value": "TR001" }, { "id": 0, "type": "table", "value": "atom" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5, 6, 7 ] }, { "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", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
12,730
insurance_and_eClaims
spider:train_spider.json:1540
Which customer have the most policies? Give me the customer details.
SELECT t2.customer_details FROM policies AS t1 JOIN customers AS t2 ON t1.customer_id = t2.customer_id GROUP BY t2.customer_details ORDER BY count(*) DESC LIMIT 1
[ "Which", "customer", "have", "the", "most", "policies", "?", "Give", "me", "the", "customer", "details", "." ]
[ { "id": 0, "type": "column", "value": "customer_details" }, { "id": 3, "type": "column", "value": "customer_id" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 1, "type": "table", "value": "policies" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "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", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
12,731
soccer_2
spider:train_spider.json:4988
What is minimum hours of the students playing in different position?
SELECT min(T2.HS) , T1.pPos FROM tryout AS T1 JOIN player AS T2 ON T1.pID = T2.pID GROUP BY T1.pPos
[ "What", "is", "minimum", "hours", "of", "the", "students", "playing", "in", "different", "position", "?" ]
[ { "id": 1, "type": "table", "value": "tryout" }, { "id": 2, "type": "table", "value": "player" }, { "id": 0, "type": "column", "value": "ppos" }, { "id": 4, "type": "column", "value": "pid" }, { "id": 3, "type": "column", "value": "hs" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "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-TABLE", "O", "O", "O", "O" ]
12,732
public_review_platform
bird:train.json:3765
How many more "buffets" than "gyms" in Yelp business?
SELECT SUM(CASE WHEN T1.category_name LIKE 'Buffets' THEN 1 ELSE 0 END) - SUM(CASE WHEN T1.category_name LIKE 'Gyms' THEN 1 ELSE 0 END) FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id
[ "How", "many", "more", "\"", "buffets", "\"", "than", "\"", "gyms", "\"", "in", "Yelp", "business", "?" ]
[ { "id": 1, "type": "table", "value": "business_categories" }, { "id": 5, "type": "column", "value": "category_name" }, { "id": 2, "type": "column", "value": "category_id" }, { "id": 0, "type": "table", "value": "categories" }, { "id": 6, "type": "value", "value": "Buffets" }, { "id": 7, "type": "value", "value": "Gyms" }, { "id": 3, "type": "value", "value": "0" }, { "id": 4, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "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": [ 4 ] }, { "entity_id": 7, "token_idxs": [ 8 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O" ]
12,733
bakery_1
bird:test.json:1497
For each type of food, tell me how many customers have ever bought it.
SELECT T1.food , count(DISTINCT T3.CustomerId) FROM goods AS T1 JOIN items AS T2 ON T1.Id = T2.Item JOIN receipts AS T3 ON T2.Receipt = T3.ReceiptNumber GROUP BY T1.food
[ "For", "each", "type", "of", "food", ",", "tell", "me", "how", "many", "customers", "have", "ever", "bought", "it", "." ]
[ { "id": 6, "type": "column", "value": "receiptnumber" }, { "id": 2, "type": "column", "value": "customerid" }, { "id": 1, "type": "table", "value": "receipts" }, { "id": 5, "type": "column", "value": "receipt" }, { "id": 3, "type": "table", "value": "goods" }, { "id": 4, "type": "table", "value": "items" }, { "id": 0, "type": "column", "value": "food" }, { "id": 8, "type": "column", "value": "item" }, { "id": 7, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "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": [ 14 ] }, { "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", "O", "O", "B-COLUMN", "O" ]
12,734
movie_1
spider:train_spider.json:2490
What are the names of the directors who made exactly one movie?
SELECT director FROM Movie GROUP BY director HAVING count(*) = 1
[ "What", "are", "the", "names", "of", "the", "directors", "who", "made", "exactly", "one", "movie", "?" ]
[ { "id": 1, "type": "column", "value": "director" }, { "id": 0, "type": "table", "value": "movie" }, { "id": 2, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
12,735
retail_world
bird:train.json:6432
What are the products that are supplied by Aux joyeux ecclsiastiques?
SELECT T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Aux joyeux ecclsiastiques'
[ "What", "are", "the", "products", "that", "are", "supplied", "by", "Aux", "joyeux", "ecclsiastiques", "?" ]
[ { "id": 4, "type": "value", "value": "Aux joyeux ecclsiastiques" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 3, "type": "column", "value": "companyname" }, { "id": 5, "type": "column", "value": "supplierid" }, { "id": 2, "type": "table", "value": "suppliers" }, { "id": 1, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]