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14,775
driving_school
spider:train_spider.json:6640
How many staff in total?
SELECT count(*) FROM Staff;
[ "How", "many", "staff", "in", "total", "?" ]
[ { "id": 0, "type": "table", "value": "staff" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O" ]
14,776
student_club
bird:dev.json:1446
Calculate the percentage of zip codes that are PO boxes.
SELECT CAST(SUM(CASE WHEN type = 'PO Box' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(zip_code) FROM zip_code
[ "Calculate", "the", "percentage", "of", "zip", "codes", "that", "are", "PO", "boxes", "." ]
[ { "id": 0, "type": "table", "value": "zip_code" }, { "id": 2, "type": "column", "value": "zip_code" }, { "id": 6, "type": "value", "value": "PO Box" }, { "id": 5, "type": "column", "value": "type" }, { "id": 1, "type": "value", "value": "100" }, { "id": 3, "type": "value", "value": "0" }, { "id": 4, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O" ]
14,777
entrepreneur
spider:train_spider.json:2277
What is the weight of the shortest person?
SELECT Weight FROM people ORDER BY Height ASC LIMIT 1
[ "What", "is", "the", "weight", "of", "the", "shortest", "person", "?" ]
[ { "id": 0, "type": "table", "value": "people" }, { "id": 1, "type": "column", "value": "weight" }, { "id": 2, "type": "column", "value": "height" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
14,778
e_commerce
bird:test.json:62
List the customers' first name, middle initial, last name and payment methods.
SELECT T1.customer_first_name , T1.customer_middle_initial , T1.customer_last_name , T2.Payment_method_code FROM Customers AS T1 JOIN Customer_Payment_Methods AS T2 ON T1.customer_id = T2.customer_id
[ "List", "the", "customers", "'", "first", "name", ",", "middle", "initial", ",", "last", "name", "and", "payment", "methods", "." ]
[ { "id": 5, "type": "table", "value": "customer_payment_methods" }, { "id": 1, "type": "column", "value": "customer_middle_initial" }, { "id": 0, "type": "column", "value": "customer_first_name" }, { "id": 3, "type": "column", "value": "payment_method_code" }, { "id": 2, "type": "column", "value": "customer_last_name" }, { "id": 6, "type": "column", "value": "customer_id" }, { "id": 4, "type": "table", "value": "customers" } ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,779
driving_school
spider:train_spider.json:6712
What is the first name of the staff who did not give any lesson?
SELECT first_name FROM Staff EXCEPT SELECT T2.first_name FROM Lessons AS T1 JOIN Staff AS T2 ON T1.staff_id = T2.staff_id
[ "What", "is", "the", "first", "name", "of", "the", "staff", "who", "did", "not", "give", "any", "lesson", "?" ]
[ { "id": 1, "type": "column", "value": "first_name" }, { "id": 3, "type": "column", "value": "staff_id" }, { "id": 2, "type": "table", "value": "lessons" }, { "id": 0, "type": "table", "value": "staff" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,780
insurance_fnol
spider:train_spider.json:911
What are all the policy types of the customer named "Dayana Robel"?
SELECT DISTINCT t3.policy_type_code FROM customers AS t1 JOIN customers_policies AS t2 ON t1.customer_id = t2.customer_id JOIN available_policies AS t3 ON t2.policy_id = t3.policy_id WHERE t1.customer_name = "Dayana Robel"
[ "What", "are", "all", "the", "policy", "types", "of", "the", "customer", "named", "\"", "Dayana", "Robel", "\"", "?" ]
[ { "id": 1, "type": "table", "value": "available_policies" }, { "id": 5, "type": "table", "value": "customers_policies" }, { "id": 0, "type": "column", "value": "policy_type_code" }, { "id": 2, "type": "column", "value": "customer_name" }, { "id": 3, "type": "column", "value": "Dayana Robel" }, { "id": 7, "type": "column", "value": "customer_id" }, { "id": 4, "type": "table", "value": "customers" }, { "id": 6, "type": "column", "value": "policy_id" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 11, 12 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 4 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
14,781
activity_1
spider:train_spider.json:6802
Which students participate in both Canoeing and Kayaking as their activities? Tell me their student ids.
SELECT T1.stuid FROM participates_in AS T1 JOIN activity AS T2 ON T2.actid = T2.actid WHERE T2.activity_name = 'Canoeing' INTERSECT SELECT T1.stuid FROM participates_in AS T1 JOIN activity AS T2 ON T2.actid = T2.actid WHERE T2.activity_name = 'Kayaking'
[ "Which", "students", "participate", "in", "both", "Canoeing", "and", "Kayaking", "as", "their", "activities", "?", "Tell", "me", "their", "student", "ids", "." ]
[ { "id": 1, "type": "table", "value": "participates_in" }, { "id": 3, "type": "column", "value": "activity_name" }, { "id": 2, "type": "table", "value": "activity" }, { "id": 4, "type": "value", "value": "Canoeing" }, { "id": 5, "type": "value", "value": "Kayaking" }, { "id": 0, "type": "column", "value": "stuid" }, { "id": 6, "type": "column", "value": "actid" } ]
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[ "O", "O", "B-TABLE", "I-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,783
disney
bird:train.json:4675
List the directors of movies that feature a song.
SELECT T2.director FROM characters AS T1 INNER JOIN director AS T2 ON T1.movie_title = T2.name WHERE T1.song IS NOT NULL GROUP BY T2.director
[ "List", "the", "directors", "of", "movies", "that", "feature", "a", "song", "." ]
[ { "id": 4, "type": "column", "value": "movie_title" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 0, "type": "column", "value": "director" }, { "id": 2, "type": "table", "value": "director" }, { "id": 3, "type": "column", "value": "song" }, { "id": 5, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 4, 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O" ]
14,784
superhero
bird:dev.json:794
Which hero was the fastest?
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN hero_attribute AS T2 ON T1.id = T2.hero_id INNER JOIN attribute AS T3 ON T2.attribute_id = T3.id WHERE T3.attribute_name = 'Speed' ORDER BY T2.attribute_value DESC LIMIT 1
[ "Which", "hero", "was", "the", "fastest", "?" ]
[ { "id": 4, "type": "column", "value": "attribute_value" }, { "id": 0, "type": "column", "value": "superhero_name" }, { "id": 2, "type": "column", "value": "attribute_name" }, { "id": 6, "type": "table", "value": "hero_attribute" }, { "id": 7, "type": "column", "value": "attribute_id" }, { "id": 1, "type": "table", "value": "attribute" }, { "id": 5, "type": "table", "value": "superhero" }, { "id": 9, "type": "column", "value": "hero_id" }, { "id": 3, "type": "value", "value": "Speed" }, { "id": 8, "type": "column", "value": "id" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "O" ]
14,786
works_cycles
bird:train.json:7287
Please list the reviewers who have given the highest rating for a medium class, women's product.
SELECT T1.ReviewerName FROM ProductReview AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Class = 'M' AND T2.Style = 'W' AND T1.Rating = 5
[ "Please", "list", "the", "reviewers", "who", "have", "given", "the", "highest", "rating", "for", "a", "medium", "class", ",", "women", "'s", "product", "." ]
[ { "id": 1, "type": "table", "value": "productreview" }, { "id": 0, "type": "column", "value": "reviewername" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 2, "type": "table", "value": "product" }, { "id": 8, "type": "column", "value": "rating" }, { "id": 4, "type": "column", "value": "class" }, { "id": 6, "type": "column", "value": "style" }, { "id": 5, "type": "value", "value": "M" }, { "id": 7, "type": "value", "value": "W" }, { "id": 9, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
14,787
world
bird:train.json:7906
List down the country names of countries that have a GNP lower than 1000 and have Dutch as their language.
SELECT T2.Name FROM CountryLanguage AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T2.GNP < 1000 AND T1.IsOfficial = 'T' AND T1.Language = 'Dutch'
[ "List", "down", "the", "country", "names", "of", "countries", "that", "have", "a", "GNP", "lower", "than", "1000", "and", "have", "Dutch", "as", "their", "language", "." ]
[ { "id": 1, "type": "table", "value": "countrylanguage" }, { "id": 3, "type": "column", "value": "countrycode" }, { "id": 7, "type": "column", "value": "isofficial" }, { "id": 9, "type": "column", "value": "language" }, { "id": 2, "type": "table", "value": "country" }, { "id": 10, "type": "value", "value": "Dutch" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "code" }, { "id": 6, "type": "value", "value": "1000" }, { "id": 5, "type": "column", "value": "gnp" }, { "id": 8, "type": "value", "value": "T" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O" ]
14,788
music_1
spider:train_spider.json:3589
What are the names of artists who are Male and are from UK?
SELECT artist_name FROM artist WHERE country = "UK" AND gender = "Male"
[ "What", "are", "the", "names", "of", "artists", "who", "are", "Male", "and", "are", "from", "UK", "?" ]
[ { "id": 1, "type": "column", "value": "artist_name" }, { "id": 2, "type": "column", "value": "country" }, { "id": 0, "type": "table", "value": "artist" }, { "id": 4, "type": "column", "value": "gender" }, { "id": 5, "type": "column", "value": "Male" }, { "id": 3, "type": "column", "value": "UK" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O" ]
14,789
hockey
bird:train.json:7657
Did the tallest player got in the Hall of Fame? If yes, please list the year when he got in the Hall of Fame.
SELECT CASE WHEN T1.hofID IS NULL THEN 'NO' ELSE T2.year END FROM Master AS T1 LEFT JOIN HOF AS T2 ON T1.hofID = T2.hofID WHERE T1.height = ( SELECT MAX(height) FROM Master )
[ "Did", "the", "tallest", "player", "got", "in", "the", "Hall", "of", "Fame", "?", "If", "yes", ",", "please", "list", "the", "year", "when", "he", "got", "in", "the", "Hall", "of", "Fame", "." ]
[ { "id": 0, "type": "table", "value": "master" }, { "id": 2, "type": "column", "value": "height" }, { "id": 4, "type": "column", "value": "hofid" }, { "id": 3, "type": "column", "value": "year" }, { "id": 1, "type": "table", "value": "hof" }, { "id": 5, "type": "value", "value": "NO" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 24 ] }, { "entity_id": 2, "token_idxs": [ 19, 20 ] }, { "entity_id": 3, "token_idxs": [ 17 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O" ]
14,790
codebase_community
bird:dev.json:678
Which post by Harvey Motulsky has the most views? Please give the id and title of this post.
SELECT T2.Id, T2.Title FROM users AS T1 INNER JOIN posts AS T2 ON T1.Id = T2.OwnerUserId WHERE T1.DisplayName = 'Harvey Motulsky' ORDER BY T2.ViewCount DESC LIMIT 1
[ "Which", "post", "by", "Harvey", "Motulsky", "has", "the", "most", "views", "?", "Please", "give", "the", "i", "d", "and", "title", "of", "this", "post", "." ]
[ { "id": 5, "type": "value", "value": "Harvey Motulsky" }, { "id": 4, "type": "column", "value": "displayname" }, { "id": 7, "type": "column", "value": "owneruserid" }, { "id": 6, "type": "column", "value": "viewcount" }, { "id": 1, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "users" }, { "id": 3, "type": "table", "value": "posts" }, { "id": 0, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 13, 14 ] }, { "entity_id": 1, "token_idxs": [ 16 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 19 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3, 4 ] }, { "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-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,792
flight_1
spider:train_spider.json:400
What are the numbers of the shortest flights?
SELECT flno FROM Flight ORDER BY distance ASC LIMIT 3
[ "What", "are", "the", "numbers", "of", "the", "shortest", "flights", "?" ]
[ { "id": 2, "type": "column", "value": "distance" }, { "id": 0, "type": "table", "value": "flight" }, { "id": 1, "type": "column", "value": "flno" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,793
icfp_1
spider:train_spider.json:2870
What is the name of the institution that "Matthias Blume" belongs to?
SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Matthias" AND t1.lname = "Blume"
[ "What", "is", "the", "name", "of", "the", "institution", "that", "\"", "Matthias", "Blume", "\"", "belongs", "to", "?" ]
[ { "id": 3, "type": "table", "value": "authorship" }, { "id": 6, "type": "column", "value": "Matthias" }, { "id": 2, "type": "table", "value": "authors" }, { "id": 4, "type": "column", "value": "instid" }, { "id": 9, "type": "column", "value": "authid" }, { "id": 5, "type": "column", "value": "fname" }, { "id": 7, "type": "column", "value": "lname" }, { "id": 8, "type": "column", "value": "Blume" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "table", "value": "inst" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 10 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O" ]
14,794
trains
bird:train.json:726
Among the trains running west, how many trains have three-wheeled, jagged roof cars?
SELECT SUM(CASE WHEN T2.direction = 'west' THEN 1 ELSE 0 END)as count FROM cars AS T1 INNER JOIN trains AS T2 ON T1.train_id = T2.id WHERE T1.wheels = 3 AND T1.roof = 'jagged'
[ "Among", "the", "trains", "running", "west", ",", "how", "many", "trains", "have", "three", "-", "wheeled", ",", "jagged", "roof", "cars", "?" ]
[ { "id": 10, "type": "column", "value": "direction" }, { "id": 2, "type": "column", "value": "train_id" }, { "id": 1, "type": "table", "value": "trains" }, { "id": 4, "type": "column", "value": "wheels" }, { "id": 7, "type": "value", "value": "jagged" }, { "id": 0, "type": "table", "value": "cars" }, { "id": 6, "type": "column", "value": "roof" }, { "id": 11, "type": "value", "value": "west" }, { "id": 3, "type": "column", "value": "id" }, { "id": 5, "type": "value", "value": "3" }, { "id": 8, "type": "value", "value": "0" }, { "id": 9, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-COLUMN", "B-TABLE", "O" ]
14,795
works_cycles
bird:train.json:7214
What is the name of the territory assigned to the sales person with business id "277"?
SELECT T2.Name FROM SalesPerson AS T1 INNER JOIN SalesTerritory AS T2 ON T1.TerritoryID = T2.TerritoryID WHERE T1.BusinessEntityID = 277
[ "What", "is", "the", "name", "of", "the", "territory", "assigned", "to", "the", "sales", "person", "with", "business", "i", "d", "\"", "277", "\"", "?" ]
[ { "id": 3, "type": "column", "value": "businessentityid" }, { "id": 2, "type": "table", "value": "salesterritory" }, { "id": 1, "type": "table", "value": "salesperson" }, { "id": 5, "type": "column", "value": "territoryid" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "277" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 10, 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 13, 14, 15 ] }, { "entity_id": 4, "token_idxs": [ 17 ] }, { "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", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O" ]
14,796
mondial_geo
bird:train.json:8245
Which country has the highest GDP?
SELECT T1.Name FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country ORDER BY T2.GDP DESC LIMIT 1
[ "Which", "country", "has", "the", "highest", "GDP", "?" ]
[ { "id": 1, "type": "table", "value": "country" }, { "id": 2, "type": "table", "value": "economy" }, { "id": 5, "type": "column", "value": "country" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "code" }, { "id": 3, "type": "column", "value": "gdp" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 1 ] }, { "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" ]
14,797
online_exams
bird:test.json:218
Find the valid answer text that appeared most frequently.
SELECT Valid_Answer_Text FROM Valid_Answers GROUP BY Valid_Answer_Text ORDER BY COUNT(*) DESC LIMIT 1
[ "Find", "the", "valid", "answer", "text", "that", "appeared", "most", "frequently", "." ]
[ { "id": 1, "type": "column", "value": "valid_answer_text" }, { "id": 0, "type": "table", "value": "valid_answers" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "O" ]
14,798
store_product
spider:train_spider.json:4914
Find all types of store and number of them.
SELECT TYPE , count(*) FROM store GROUP BY TYPE
[ "Find", "all", "types", "of", "store", "and", "number", "of", "them", "." ]
[ { "id": 0, "type": "table", "value": "store" }, { "id": 1, "type": "column", "value": "type" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
14,799
college_1
spider:train_spider.json:3237
Find the total credits of all classes offered by each department.
SELECT sum(T1.crs_credit) , T1.dept_code FROM course AS T1 JOIN CLASS AS T2 ON T1.crs_code = T2.crs_code GROUP BY T1.dept_code
[ "Find", "the", "total", "credits", "of", "all", "classes", "offered", "by", "each", "department", "." ]
[ { "id": 3, "type": "column", "value": "crs_credit" }, { "id": 0, "type": "column", "value": "dept_code" }, { "id": 4, "type": "column", "value": "crs_code" }, { "id": 1, "type": "table", "value": "course" }, { "id": 2, "type": "table", "value": "class" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
14,800
student_club
bird:dev.json:1317
Among the students from the Student_Club who attended the event "Women's Soccer", how many of them want a T-shirt that's in medium size?
SELECT COUNT(T1.event_id) FROM event AS T1 INNER JOIN attendance AS T2 ON T1.event_id = T2.link_to_event INNER JOIN member AS T3 ON T2.link_to_member = T3.member_id WHERE T1.event_name = 'Women''s Soccer' AND T3.t_shirt_size = 'Medium'
[ "Among", "the", "students", "from", "the", "Student_Club", "who", "attended", "the", "event", "\"", "Women", "'s", "Soccer", "\"", ",", "how", "many", "of", "them", "want", "a", "T", "-", "shirt", "that", "'s", "in", "medium", "size", "?" ]
[ { "id": 4, "type": "column", "value": "link_to_member" }, { "id": 7, "type": "value", "value": "Women's Soccer" }, { "id": 10, "type": "column", "value": "link_to_event" }, { "id": 8, "type": "column", "value": "t_shirt_size" }, { "id": 3, "type": "table", "value": "attendance" }, { "id": 6, "type": "column", "value": "event_name" }, { "id": 5, "type": "column", "value": "member_id" }, { "id": 1, "type": "column", "value": "event_id" }, { "id": 0, "type": "table", "value": "member" }, { "id": 9, "type": "value", "value": "Medium" }, { "id": 2, "type": "table", "value": "event" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "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": [ 11, 12, 13 ] }, { "entity_id": 8, "token_idxs": [ 22, 23, 24 ] }, { "entity_id": 9, "token_idxs": [ 28 ] }, { "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", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O", "O" ]
14,801
school_bus
spider:train_spider.json:6358
Show the types of schools that have two schools.
SELECT TYPE FROM school GROUP BY TYPE HAVING count(*) = 2
[ "Show", "the", "types", "of", "schools", "that", "have", "two", "schools", "." ]
[ { "id": 0, "type": "table", "value": "school" }, { "id": 1, "type": "column", "value": "type" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,802
cre_Doc_and_collections
bird:test.json:687
What is the description of collection named Best?
SELECT Collection_Description FROM Collections WHERE Collection_Name = "Best";
[ "What", "is", "the", "description", "of", "collection", "named", "Best", "?" ]
[ { "id": 1, "type": "column", "value": "collection_description" }, { "id": 2, "type": "column", "value": "collection_name" }, { "id": 0, "type": "table", "value": "collections" }, { "id": 3, "type": "column", "value": "Best" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O" ]
14,803
ship_1
spider:train_spider.json:6246
Find the name, type, and flag of the ship that is built in the most recent year.
SELECT name , TYPE , flag FROM ship ORDER BY built_year DESC LIMIT 1
[ "Find", "the", "name", ",", "type", ",", "and", "flag", "of", "the", "ship", "that", "is", "built", "in", "the", "most", "recent", "year", "." ]
[ { "id": 4, "type": "column", "value": "built_year" }, { "id": 0, "type": "table", "value": "ship" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "type" }, { "id": 3, "type": "column", "value": "flag" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
14,804
works_cycles
bird:train.json:7274
What is the average lead time of product ID 843? Calculate for its profit on net and indicate the full location to which the vendor is located.
SELECT T1.AverageLeadTime, T1.LastReceiptCost - T1.StandardPrice, T4.AddressLine1, T4.AddressLine2 , T4.City, T4.PostalCode FROM ProductVendor AS T1 INNER JOIN Vendor AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN BusinessEntityAddress AS T3 ON T1.BusinessEntityID = T3.BusinessEntityID INNER JOIN Address AS T4 ON T3.AddressID = T4.AddressID WHERE T1.ProductID = 843
[ "What", "is", "the", "average", "lead", "time", "of", "product", "ID", "843", "?", "Calculate", "for", "its", "profit", "on", "net", "and", "indicate", "the", "full", "location", "to", "which", "the", "vendor", "is", "located", "." ]
[ { "id": 10, "type": "table", "value": "businessentityaddress" }, { "id": 14, "type": "column", "value": "businessentityid" }, { "id": 0, "type": "column", "value": "averageleadtime" }, { "id": 8, "type": "column", "value": "lastreceiptcost" }, { "id": 9, "type": "column", "value": "standardprice" }, { "id": 12, "type": "table", "value": "productvendor" }, { "id": 1, "type": "column", "value": "addressline1" }, { "id": 2, "type": "column", "value": "addressline2" }, { "id": 4, "type": "column", "value": "postalcode" }, { "id": 6, "type": "column", "value": "productid" }, { "id": 11, "type": "column", "value": "addressid" }, { "id": 5, "type": "table", "value": "address" }, { "id": 13, "type": "table", "value": "vendor" }, { "id": 3, "type": "column", "value": "city" }, { "id": 7, "type": "value", "value": "843" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 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": [ 7, 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": [ 25 ] }, { "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-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
14,805
store_1
spider:train_spider.json:631
List the name of tracks belongs to genre Rock or media type is MPEG audio file.
SELECT T2.name FROM genres AS T1 JOIN tracks AS T2 ON T1.id = T2.genre_id JOIN media_types AS T3 ON T3.id = T2.media_type_id WHERE T1.name = "Rock" OR T3.name = "MPEG audio file";
[ "List", "the", "name", "of", "tracks", "belongs", "to", "genre", "Rock", "or", "media", "type", "is", "MPEG", "audio", "file", "." ]
[ { "id": 7, "type": "column", "value": "MPEG audio file" }, { "id": 5, "type": "column", "value": "media_type_id" }, { "id": 1, "type": "table", "value": "media_types" }, { "id": 8, "type": "column", "value": "genre_id" }, { "id": 2, "type": "table", "value": "genres" }, { "id": 3, "type": "table", "value": "tracks" }, { "id": 0, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "Rock" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 10, 11 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 8 ] }, { "entity_id": 7, "token_idxs": [ 13, 14, 15 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
14,806
synthea
bird:train.json:1389
How many patients are allergic to eggs?
SELECT COUNT(PATIENT) FROM allergies WHERE DESCRIPTION = 'Allergy to eggs'
[ "How", "many", "patients", "are", "allergic", "to", "eggs", "?" ]
[ { "id": 2, "type": "value", "value": "Allergy to eggs" }, { "id": 1, "type": "column", "value": "description" }, { "id": 0, "type": "table", "value": "allergies" }, { "id": 3, "type": "column", "value": "patient" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "B-VALUE", "I-VALUE", "O" ]
14,807
authors
bird:train.json:3564
How many authors have written paper "145 GROWTH HORMONE RECEPTORS AND THE ONSET OF HYPERINSULINEMIA IN THE OBESE ZUCKER RAT: "?
SELECT COUNT(DISTINCT T2.Name) FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Title = '145 GROWTH HORMONE RECEPTORS AND THE ONSET OF HYPERINSULINEMIA IN THE OBESE ZUCKER RAT: '
[ "How", "many", "authors", "have", "written", "paper", "\"", "145", "GROWTH", "HORMONE", "RECEPTORS", "AND", "THE", "ONSET", "OF", "HYPERINSULINEMIA", "IN", "THE", "OBESE", "ZUCKER", "RAT", ":", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "145 GROWTH HORMONE RECEPTORS AND THE ONSET OF HYPERINSULINEMIA IN THE OBESE ZUCKER RAT: " }, { "id": 1, "type": "table", "value": "paperauthor" }, { "id": 6, "type": "column", "value": "paperid" }, { "id": 0, "type": "table", "value": "paper" }, { "id": 2, "type": "column", "value": "title" }, { "id": 4, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,808
bike_share_1
bird:train.json:9076
What is the total number of bikes that can be hold in Redwood City before 2014.
SELECT SUM(CASE WHEN city = 'Redwood City' AND SUBSTR(installation_date, -4) < '2014' THEN dock_count ELSE 0 END) NUM FROM station
[ "What", "is", "the", "total", "number", "of", "bikes", "that", "can", "be", "hold", "in", "Redwood", "City", "before", "2014", "." ]
[ { "id": 6, "type": "column", "value": "installation_date" }, { "id": 4, "type": "value", "value": "Redwood City" }, { "id": 2, "type": "column", "value": "dock_count" }, { "id": 0, "type": "table", "value": "station" }, { "id": 3, "type": "column", "value": "city" }, { "id": 5, "type": "value", "value": "2014" }, { "id": 7, "type": "value", "value": "-4" }, { "id": 1, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 13 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "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", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]
14,810
cre_Doc_Workflow
bird:test.json:2033
What is the process name for the next process of the process with id 9?
SELECT process_name FROM Business_processes WHERE process_id = (SELECT next_process_id FROM Business_processes WHERE process_id = 9)
[ "What", "is", "the", "process", "name", "for", "the", "next", "process", "of", "the", "process", "with", "i", "d", "9", "?" ]
[ { "id": 0, "type": "table", "value": "business_processes" }, { "id": 3, "type": "column", "value": "next_process_id" }, { "id": 1, "type": "column", "value": "process_name" }, { "id": 2, "type": "column", "value": "process_id" }, { "id": 4, "type": "value", "value": "9" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "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", "I-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,811
music_2
spider:train_spider.json:5258
Find the first name of the band mate that has performed in most songs.
SELECT t2.firstname FROM Performance AS t1 JOIN Band AS t2 ON t1.bandmate = t2.id JOIN Songs AS T3 ON T3.SongId = T1.SongId GROUP BY firstname ORDER BY count(*) DESC LIMIT 1
[ "Find", "the", "first", "name", "of", "the", "band", "mate", "that", "has", "performed", "in", "most", "songs", "." ]
[ { "id": 2, "type": "table", "value": "performance" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 5, "type": "column", "value": "bandmate" }, { "id": 4, "type": "column", "value": "songid" }, { "id": 1, "type": "table", "value": "songs" }, { "id": 3, "type": "table", "value": "band" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 13 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [ 0 ] }, { "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-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
14,812
hospital_1
spider:train_spider.json:3937
Tell me the distinct block codes where some rooms are available.
SELECT DISTINCT blockcode FROM room WHERE unavailable = 0
[ "Tell", "me", "the", "distinct", "block", "codes", "where", "some", "rooms", "are", "available", "." ]
[ { "id": 2, "type": "column", "value": "unavailable" }, { "id": 1, "type": "column", "value": "blockcode" }, { "id": 0, "type": "table", "value": "room" }, { "id": 3, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "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": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "O" ]
14,813
company_office
spider:train_spider.json:4550
List the name and assets of each company in ascending order of company name.
SELECT name , Assets_billion FROM Companies ORDER BY name ASC
[ "List", "the", "name", "and", "assets", "of", "each", "company", "in", "ascending", "order", "of", "company", "name", "." ]
[ { "id": 2, "type": "column", "value": "assets_billion" }, { "id": 0, "type": "table", "value": "companies" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "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", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O" ]
14,814
music_1
spider:train_spider.json:3599
What are the maximum and minimum resolution of songs whose duration is 3 minutes?
SELECT max(T2.resolution) , min(T2.resolution) FROM files AS T1 JOIN song AS T2 ON T1.f_id = T2.f_id WHERE T1.duration LIKE "3:%"
[ "What", "are", "the", "maximum", "and", "minimum", "resolution", "of", "songs", "whose", "duration", "is", "3", "minutes", "?" ]
[ { "id": 4, "type": "column", "value": "resolution" }, { "id": 2, "type": "column", "value": "duration" }, { "id": 0, "type": "table", "value": "files" }, { "id": 1, "type": "table", "value": "song" }, { "id": 5, "type": "column", "value": "f_id" }, { "id": 3, "type": "column", "value": "3:%" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O" ]
14,815
soccer_2016
bird:train.json:1868
Provide the names and birthdates of players who have left-arm fast skills.
SELECT T1.Player_Name, T1.DOB FROM Player AS T1 INNER JOIN Bowling_Style AS T2 ON T2.Bowling_Id = T1.Bowling_skill WHERE T2.Bowling_skill = 'Left-arm fast'
[ "Provide", "the", "names", "and", "birthdates", "of", "players", "who", "have", "left", "-", "arm", "fast", "skills", "." ]
[ { "id": 3, "type": "table", "value": "bowling_style" }, { "id": 4, "type": "column", "value": "bowling_skill" }, { "id": 5, "type": "value", "value": "Left-arm fast" }, { "id": 0, "type": "column", "value": "player_name" }, { "id": 6, "type": "column", "value": "bowling_id" }, { "id": 2, "type": "table", "value": "player" }, { "id": 1, "type": "column", "value": "dob" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 9, 10, 11, 12 ] }, { "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", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
14,816
sales_in_weather
bird:train.json:8202
How many stations were able to sell item 5 on January 2014?
SELECT COUNT(DISTINCT T2.station_nbr) AS number FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr WHERE SUBSTR(`date`, 1, 7) = '2014-01' AND item_nbr = 5
[ "How", "many", "stations", "were", "able", "to", "sell", "item", "5", "on", "January", "2014", "?" ]
[ { "id": 0, "type": "table", "value": "sales_in_weather" }, { "id": 2, "type": "column", "value": "station_nbr" }, { "id": 3, "type": "column", "value": "store_nbr" }, { "id": 1, "type": "table", "value": "relation" }, { "id": 5, "type": "column", "value": "item_nbr" }, { "id": 4, "type": "value", "value": "2014-01" }, { "id": 7, "type": "column", "value": "date" }, { "id": 6, "type": "value", "value": "5" }, { "id": 8, "type": "value", "value": "1" }, { "id": 9, "type": "value", "value": "7" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [ 8 ] }, { "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", "B-COLUMN", "B-VALUE", "O", "O", "B-VALUE", "O" ]
14,817
social_media
bird:train.json:806
Give the name of the city of the user who tweeted `One of our favorite stories is @FINRA_News's move to the cloud with AWS Enterprise Support! https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a`.
SELECT T2.City FROM twitter AS T1 INNER JOIN location AS T2 ON T2.LocationID = T1.LocationID WHERE T1.text = 'One of our favorite stories is @FINRA_News''s move to the cloud with AWS Enterprise Support! https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a'
[ "Give", "the", "name", "of", "the", "city", "of", "the", "user", "who", "tweeted", "`", "One", "of", "our", "favorite", "stories", "is", "@FINRA_News", "'s", "move", "to", "the", "cloud", "with", "AWS", "Enterprise", "Support", "!", "https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a", "`", "." ]
[ { "id": 4, "type": "value", "value": "One of our favorite stories is @FINRA_News's move to the cloud with AWS Enterprise Support! https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a" }, { "id": 5, "type": "column", "value": "locationid" }, { "id": 2, "type": "table", "value": "location" }, { "id": 1, "type": "table", "value": "twitter" }, { "id": 0, "type": "column", "value": "city" }, { "id": 3, "type": "column", "value": "text" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
14,818
legislator
bird:train.json:4805
What is the birthday of Amy Klobuchar?
SELECT birthday_bio FROM current WHERE first_name = 'Amy' AND last_name = 'Klobuchar'
[ "What", "is", "the", "birthday", "of", "Amy", "Klobuchar", "?" ]
[ { "id": 1, "type": "column", "value": "birthday_bio" }, { "id": 2, "type": "column", "value": "first_name" }, { "id": 4, "type": "column", "value": "last_name" }, { "id": 5, "type": "value", "value": "Klobuchar" }, { "id": 0, "type": "table", "value": "current" }, { "id": 3, "type": "value", "value": "Amy" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-VALUE", "O" ]
14,819
aan_1
bird:test.json:984
What are the titles and paper ids co-authored by Mckeown, Kathleen and Rambow, Owen?
SELECT T1.title , T1.paper_id FROM Paper 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 LIKE "%Mckeown , Kathleen%" INTERSECT SELECT T1.title , T1.paper_id FROM Paper 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 LIKE "%Rambow , Owen%"
[ "What", "are", "the", "titles", "and", "paper", "ids", "co", "-", "authored", "by", "Mckeown", ",", "Kathleen", "and", "Rambow", ",", "Owen", "?" ]
[ { "id": 4, "type": "column", "value": "%Mckeown , Kathleen%" }, { "id": 5, "type": "column", "value": "%Rambow , Owen%" }, { "id": 7, "type": "table", "value": "author_list" }, { "id": 8, "type": "column", "value": "author_id" }, { "id": 1, "type": "column", "value": "paper_id" }, { "id": 2, "type": "table", "value": "author" }, { "id": 0, "type": "column", "value": "title" }, { "id": 6, "type": "table", "value": "paper" }, { "id": 3, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11, 12, 13 ] }, { "entity_id": 5, "token_idxs": [ 15, 16, 17 ] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "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", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
14,820
soccer_1
spider:train_spider.json:1298
What are the names of players who have the best dribbling?
SELECT DISTINCT T1.player_name FROM Player AS T1 JOIN Player_Attributes AS T2 ON T1.player_api_id = T2.player_api_id WHERE T2.dribbling = ( SELECT max(overall_rating) FROM Player_Attributes)
[ "What", "are", "the", "names", "of", "players", "who", "have", "the", "best", "dribbling", "?" ]
[ { "id": 2, "type": "table", "value": "player_attributes" }, { "id": 5, "type": "column", "value": "overall_rating" }, { "id": 4, "type": "column", "value": "player_api_id" }, { "id": 0, "type": "column", "value": "player_name" }, { "id": 3, "type": "column", "value": "dribbling" }, { "id": 1, "type": "table", "value": "player" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,821
car_road_race
bird:test.json:1314
How many races are there?
SELECT count(*) FROM race
[ "How", "many", "races", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "race" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O" ]
14,822
advertising_agencies
bird:test.json:2105
Show all invoice ids and statuses without a payment.
SELECT invoice_id , invoice_status FROM Invoices EXCEPT SELECT T1.invoice_id , T1.invoice_status FROM Invoices AS T1 JOIN Payments AS T2 ON T1.invoice_id = T2.invoice_id
[ "Show", "all", "invoice", "ids", "and", "statuses", "without", "a", "payment", "." ]
[ { "id": 2, "type": "column", "value": "invoice_status" }, { "id": 1, "type": "column", "value": "invoice_id" }, { "id": 0, "type": "table", "value": "invoices" }, { "id": 3, "type": "table", "value": "payments" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 4, 5 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "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", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O" ]
14,823
formula_1
bird:dev.json:998
In terms of number of points acquired, how many victories did the driver who ranked 91st acquired?
SELECT SUM(CASE WHEN points = 91 THEN wins ELSE 0 END) FROM driverStandings
[ "In", "terms", "of", "number", "of", "points", "acquired", ",", "how", "many", "victories", "did", "the", "driver", "who", "ranked", "91st", "acquired", "?" ]
[ { "id": 0, "type": "table", "value": "driverstandings" }, { "id": 3, "type": "column", "value": "points" }, { "id": 2, "type": "column", "value": "wins" }, { "id": 4, "type": "value", "value": "91" }, { "id": 1, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 0 ] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
14,825
cre_Doc_Tracking_DB
spider:train_spider.json:4190
List all role codes, role names, and role descriptions.
SELECT role_code , role_name , role_description FROM ROLES
[ "List", "all", "role", "codes", ",", "role", "names", ",", "and", "role", "descriptions", "." ]
[ { "id": 3, "type": "column", "value": "role_description" }, { "id": 1, "type": "column", "value": "role_code" }, { "id": 2, "type": "column", "value": "role_name" }, { "id": 0, "type": "table", "value": "roles" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,826
student_loan
bird:train.json:4494
Among the students who have been absent for four months, provide any five students' names and enlisted organizations.
SELECT T2.name, T2.organ FROM longest_absense_from_school AS T1 INNER JOIN enlist AS T2 ON T2.name = T1.name WHERE T1.month = 4 LIMIT 5
[ "Among", "the", "students", "who", "have", "been", "absent", "for", "four", "months", ",", "provide", "any", "five", "students", "'", "names", "and", "enlisted", "organizations", "." ]
[ { "id": 2, "type": "table", "value": "longest_absense_from_school" }, { "id": 3, "type": "table", "value": "enlist" }, { "id": 1, "type": "column", "value": "organ" }, { "id": 4, "type": "column", "value": "month" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "4" } ]
[ { "entity_id": 0, "token_idxs": [ 16 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 18 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O" ]
14,827
regional_sales
bird:train.json:2632
From 2018 to 2020, which year did the George Lewis group have the highest number of orders?
SELECT SUBSTR(T1.OrderDate, -2, 2) FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.`Sales Team` = 'George Lewis' GROUP BY SUBSTR(T1.OrderDate, -2, 2) ORDER BY COUNT(T1.OrderNumber) DESC LIMIT 1
[ "From", "2018", "to", "2020", ",", "which", "year", "did", "the", "George", "Lewis", "group", "have", "the", "highest", "number", "of", "orders", "?" ]
[ { "id": 0, "type": "table", "value": "Sales Orders" }, { "id": 3, "type": "value", "value": "George Lewis" }, { "id": 8, "type": "column", "value": "_salesteamid" }, { "id": 7, "type": "column", "value": "salesteamid" }, { "id": 9, "type": "column", "value": "ordernumber" }, { "id": 1, "type": "table", "value": "Sales Team" }, { "id": 2, "type": "column", "value": "Sales Team" }, { "id": 4, "type": "column", "value": "orderdate" }, { "id": 5, "type": "value", "value": "-2" }, { "id": 6, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [ 17 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 15 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
14,828
college_1
spider:train_spider.json:3324
What are the different first names and highest degree attained for professors teaching in the Computer Information Systems department?
SELECT DISTINCT T2.emp_fname , T3.prof_high_degree FROM CLASS AS T1 JOIN employee AS T2 ON T1.prof_num = T2.emp_num JOIN professor AS T3 ON T2.emp_num = T3.emp_num JOIN department AS T4 ON T4.dept_code = T3.dept_code WHERE T4.dept_name = 'Computer Info. Systems'
[ "What", "are", "the", "different", "first", "names", "and", "highest", "degree", "attained", "for", "professors", "teaching", "in", "the", "Computer", "Information", "Systems", "department", "?" ]
[ { "id": 4, "type": "value", "value": "Computer Info. Systems" }, { "id": 1, "type": "column", "value": "prof_high_degree" }, { "id": 2, "type": "table", "value": "department" }, { "id": 0, "type": "column", "value": "emp_fname" }, { "id": 3, "type": "column", "value": "dept_name" }, { "id": 5, "type": "table", "value": "professor" }, { "id": 6, "type": "column", "value": "dept_code" }, { "id": 8, "type": "table", "value": "employee" }, { "id": 10, "type": "column", "value": "prof_num" }, { "id": 9, "type": "column", "value": "emp_num" }, { "id": 7, "type": "table", "value": "class" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7, 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 18 ] }, { "entity_id": 4, "token_idxs": [ 15, 16, 17 ] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "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", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O" ]
14,829
world
bird:train.json:7832
Among the languages used in Baltic Countries, provide the languages which are used by over 80%.
SELECT T2.Language FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Region = 'Baltic Countries' AND T2.Percentage > 80
[ "Among", "the", "languages", "used", "in", "Baltic", "Countries", ",", "provide", "the", "languages", "which", "are", "used", "by", "over", "80", "%", "." ]
[ { "id": 6, "type": "value", "value": "Baltic Countries" }, { "id": 2, "type": "table", "value": "countrylanguage" }, { "id": 4, "type": "column", "value": "countrycode" }, { "id": 7, "type": "column", "value": "percentage" }, { "id": 0, "type": "column", "value": "language" }, { "id": 1, "type": "table", "value": "country" }, { "id": 5, "type": "column", "value": "region" }, { "id": 3, "type": "column", "value": "code" }, { "id": 8, "type": "value", "value": "80" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "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": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "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", "B-COLUMN", "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
14,830
college_1
spider:train_spider.json:3307
Find the first name and office of the professor who is in the history department and has a Ph.D. degree.
SELECT T1.emp_fname , T2.prof_office FROM employee AS T1 JOIN professor AS T2 ON T1.emp_num = T2.emp_num JOIN department AS T3 ON T3.dept_code = T2.dept_code WHERE T3.dept_name = 'History' AND T2.prof_high_degree = 'Ph.D.'
[ "Find", "the", "first", "name", "and", "office", "of", "the", "professor", "who", "is", "in", "the", "history", "department", "and", "has", "a", "Ph.D.", "degree", "." ]
[ { "id": 8, "type": "column", "value": "prof_high_degree" }, { "id": 1, "type": "column", "value": "prof_office" }, { "id": 2, "type": "table", "value": "department" }, { "id": 0, "type": "column", "value": "emp_fname" }, { "id": 4, "type": "table", "value": "professor" }, { "id": 5, "type": "column", "value": "dept_code" }, { "id": 6, "type": "column", "value": "dept_name" }, { "id": 3, "type": "table", "value": "employee" }, { "id": 7, "type": "value", "value": "History" }, { "id": 10, "type": "column", "value": "emp_num" }, { "id": 9, "type": "value", "value": "Ph.D." } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 14 ] }, { "entity_id": 7, "token_idxs": [ 13 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 18 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O" ]
14,831
movie_platform
bird:train.json:145
List all the titles created by user who was a subsriber when he created the list and have less than 50 movies in the list.
SELECT DISTINCT T2.list_title FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_movie_number < 50 AND T1.user_subscriber = 1
[ "List", "all", "the", "titles", "created", "by", "user", "who", "was", "a", "subsriber", "when", "he", "created", "the", "list", "and", "have", "less", "than", "50", "movies", "in", "the", "list", "." ]
[ { "id": 4, "type": "column", "value": "list_movie_number" }, { "id": 6, "type": "column", "value": "user_subscriber" }, { "id": 1, "type": "table", "value": "lists_users" }, { "id": 0, "type": "column", "value": "list_title" }, { "id": 3, "type": "column", "value": "list_id" }, { "id": 2, "type": "table", "value": "lists" }, { "id": 5, "type": "value", "value": "50" }, { "id": 7, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 0, 1, 2, 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 20 ] }, { "entity_id": 6, "token_idxs": [ 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": [] } ]
[ "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O" ]
14,832
soccer_2016
bird:train.json:2033
What is the average of Indian players that were born between 1975 and 1985 among all players?
SELECT CAST(SUM(CASE WHEN T2.Country_Name = 'India' THEN 1 ELSE 0 END) AS REAL) / COUNT(T1.Player_Id) FROM Player AS T1 INNER JOIN Country AS T2 ON T1.Country_Name = T2.Country_ID WHERE strftime('%Y', T1.DOB) BETWEEN '1975' AND '1985'
[ "What", "is", "the", "average", "of", "Indian", "players", "that", "were", "born", "between", "1975", "and", "1985", "among", "all", "players", "?" ]
[ { "id": 4, "type": "column", "value": "country_name" }, { "id": 5, "type": "column", "value": "country_id" }, { "id": 8, "type": "column", "value": "player_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 0, "type": "table", "value": "player" }, { "id": 11, "type": "value", "value": "India" }, { "id": 2, "type": "value", "value": "1975" }, { "id": 3, "type": "value", "value": "1985" }, { "id": 7, "type": "column", "value": "dob" }, { "id": 6, "type": "value", "value": "%Y" }, { "id": 9, "type": "value", "value": "0" }, { "id": 10, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 16 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "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": [ 5 ] }, { "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", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "B-TABLE", "O" ]
14,835
music_tracker
bird:train.json:2050
Name all the release titles of the "ep's" under the alternative tag.
SELECT T1.groupName FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T2.tag LIKE 'alternative' AND T1.releaseType = 'ep'
[ "Name", "all", "the", "release", "titles", "of", "the", "\"", "ep", "'s", "\"", "under", "the", "alternative", "tag", "." ]
[ { "id": 5, "type": "value", "value": "alternative" }, { "id": 6, "type": "column", "value": "releasetype" }, { "id": 0, "type": "column", "value": "groupname" }, { "id": 1, "type": "table", "value": "torrents" }, { "id": 2, "type": "table", "value": "tags" }, { "id": 4, "type": "column", "value": "tag" }, { "id": 3, "type": "column", "value": "id" }, { "id": 7, "type": "value", "value": "ep" } ]
[ { "entity_id": 0, "token_idxs": [ 0 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 14 ] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 3 ] }, { "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": [] } ]
[ "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,836
student_club
bird:dev.json:1388
Which students manage to generate the highest income. State his/her full name along with the income source.
SELECT T1.first_name, T1.last_name, T2.source FROM member AS T1 INNER JOIN income AS T2 ON T1.member_id = T2.link_to_member GROUP BY T1.first_name, T1.last_name, T2.source ORDER BY SUM(T2.amount) DESC LIMIT 1
[ "Which", "students", "manage", "to", "generate", "the", "highest", "income", ".", "State", "his", "/", "her", "full", "name", "along", "with", "the", "income", "source", "." ]
[ { "id": 6, "type": "column", "value": "link_to_member" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 5, "type": "column", "value": "member_id" }, { "id": 2, "type": "column", "value": "source" }, { "id": 3, "type": "table", "value": "member" }, { "id": 4, "type": "table", "value": "income" }, { "id": 7, "type": "column", "value": "amount" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [ 19 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 18 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
14,837
epinions_1
spider:train_spider.json:1714
Find the name of the target user with the lowest trust score.
SELECT T1.name FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.target_u_id ORDER BY trust LIMIT 1
[ "Find", "the", "name", "of", "the", "target", "user", "with", "the", "lowest", "trust", "score", "." ]
[ { "id": 5, "type": "column", "value": "target_u_id" }, { "id": 1, "type": "table", "value": "useracct" }, { "id": 2, "type": "table", "value": "trust" }, { "id": 3, "type": "column", "value": "trust" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "u_id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,838
video_games
bird:train.json:3430
What are the three largest numbers of games sold?
SELECT T.game_platform_id, SUM(T.num_sales) * 100000 FROM region_sales AS T GROUP BY game_platform_id ORDER BY SUM(T.num_sales) * 100000 DESC LIMIT 3
[ "What", "are", "the", "three", "largest", "numbers", "of", "games", "sold", "?" ]
[ { "id": 1, "type": "column", "value": "game_platform_id" }, { "id": 0, "type": "table", "value": "region_sales" }, { "id": 3, "type": "column", "value": "num_sales" }, { "id": 2, "type": "value", "value": "100000" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
14,839
headphone_store
bird:test.json:925
Which headphone class does have more than two headphones?
SELECT CLASS FROM headphone GROUP BY CLASS HAVING count(*) > 2
[ "Which", "headphone", "class", "does", "have", "more", "than", "two", "headphones", "?" ]
[ { "id": 0, "type": "table", "value": "headphone" }, { "id": 1, "type": "column", "value": "class" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
14,840
works_cycles
bird:train.json:7069
What is the first name of the male employee who has a western name style?
SELECT T2.FirstName FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T2.NameStyle = 0 AND T1.Gender = 'M'
[ "What", "is", "the", "first", "name", "of", "the", "male", "employee", "who", "has", "a", "western", "name", "style", "?" ]
[ { "id": 3, "type": "column", "value": "businessentityid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 4, "type": "column", "value": "namestyle" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 2, "type": "table", "value": "person" }, { "id": 6, "type": "column", "value": "gender" }, { "id": 5, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "M" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 13, 14 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,841
simpson_episodes
bird:train.json:4361
Among the people in Animation Department, who are credited for additional time in the episode titled by "How the Test Was Won"?
SELECT T2.person FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'How the Test Was Won' AND T2.role = 'additional timer' AND T2.credited = 'true' AND T2.category = 'Animation Department';
[ "Among", "the", "people", "in", "Animation", "Department", ",", "who", "are", "credited", "for", "additional", "time", "in", "the", "episode", "titled", "by", "\"", "How", "the", "Test", "Was", "Won", "\"", "?" ]
[ { "id": 5, "type": "value", "value": "How the Test Was Won" }, { "id": 11, "type": "value", "value": "Animation Department" }, { "id": 7, "type": "value", "value": "additional timer" }, { "id": 3, "type": "column", "value": "episode_id" }, { "id": 8, "type": "column", "value": "credited" }, { "id": 10, "type": "column", "value": "category" }, { "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" }, { "id": 9, "type": "value", "value": "true" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 15 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [ 19, 20, 21, 22, 23 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 11, 12 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [ 4, 5 ] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
14,842
thrombosis_prediction
bird:dev.json:1188
How many female patients born in 1964 were admitted to the hospital? List them by ID.
SELECT ID FROM Patient WHERE STRFTIME('%Y', Birthday) = '1964' AND SEX = 'F' AND Admission = '+'
[ "How", "many", "female", "patients", "born", "in", "1964", "were", "admitted", "to", "the", "hospital", "?", "List", "them", "by", "ID", "." ]
[ { "id": 5, "type": "column", "value": "admission" }, { "id": 8, "type": "column", "value": "birthday" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 2, "type": "value", "value": "1964" }, { "id": 3, "type": "column", "value": "sex" }, { "id": 1, "type": "column", "value": "id" }, { "id": 7, "type": "value", "value": "%Y" }, { "id": 4, "type": "value", "value": "F" }, { "id": 6, "type": "value", "value": "+" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 16 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,843
online_exams
bird:test.json:193
How many exams are there?
SELECT count(*) FROM Exams
[ "How", "many", "exams", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "exams" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O" ]
14,844
retail_complains
bird:train.json:271
What is the percentage of the complaint calls from Mr Mason Javen Lopez has got the consent provided by the customer?
SELECT CAST(SUM(CASE WHEN T2.`Consumer consent provided?` = 'Consent provided' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.`Consumer consent provided?`) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.sex = 'Male' AND T1.first = 'Mason' AND T1.middle = 'Javen' AND T1.last = 'Lopez'
[ "What", "is", "the", "percentage", "of", "the", "complaint", "calls", "from", "Mr", "Mason", "Javen", "Lopez", "has", "got", "the", "consent", "provided", "by", "the", "customer", "?" ]
[ { "id": 12, "type": "column", "value": "Consumer consent provided?" }, { "id": 15, "type": "value", "value": "Consent provided" }, { "id": 2, "type": "column", "value": "client_id" }, { "id": 0, "type": "table", "value": "client" }, { "id": 1, "type": "table", "value": "events" }, { "id": 7, "type": "column", "value": "middle" }, { "id": 5, "type": "column", "value": "first" }, { "id": 6, "type": "value", "value": "Mason" }, { "id": 8, "type": "value", "value": "Javen" }, { "id": 10, "type": "value", "value": "Lopez" }, { "id": 4, "type": "value", "value": "Male" }, { "id": 9, "type": "column", "value": "last" }, { "id": 3, "type": "column", "value": "sex" }, { "id": 11, "type": "value", "value": "100" }, { "id": 13, "type": "value", "value": "0" }, { "id": 14, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 11 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 12 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [ 15 ] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [ 16, 17 ] }, { "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-VALUE", "B-VALUE", "B-VALUE", "O", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "O", "O", "O", "O" ]
14,845
gas_company
spider:train_spider.json:2022
What are the headquarters without companies that are in the banking industry?
SELECT headquarters FROM company EXCEPT SELECT headquarters FROM company WHERE main_industry = 'Banking'
[ "What", "are", "the", "headquarters", "without", "companies", "that", "are", "in", "the", "banking", "industry", "?" ]
[ { "id": 2, "type": "column", "value": "main_industry" }, { "id": 1, "type": "column", "value": "headquarters" }, { "id": 0, "type": "table", "value": "company" }, { "id": 3, "type": "value", "value": "Banking" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,846
mondial_geo
bird:train.json:8436
Which two nations are separated from one another by the longest border? Please include the entire names of the nations in your answer.
SELECT Country1, Country2 FROM borders ORDER BY Length DESC LIMIT 1
[ "Which", "two", "nations", "are", "separated", "from", "one", "another", "by", "the", "longest", "border", "?", "Please", "include", "the", "entire", "names", "of", "the", "nations", "in", "your", "answer", "." ]
[ { "id": 1, "type": "column", "value": "country1" }, { "id": 2, "type": "column", "value": "country2" }, { "id": 0, "type": "table", "value": "borders" }, { "id": 3, "type": "column", "value": "length" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,847
cre_Students_Information_Systems
bird:test.json:454
What are the personal details and the address type descriptions of each student?
SELECT DISTINCT T1.student_details , T3.address_type_description FROM Students AS T1 JOIN Students_Addresses AS T2 ON T1.student_id = T2.student_id JOIN Ref_Address_Types AS T3 ON T2.address_type_code = T3.address_type_code
[ "What", "are", "the", "personal", "details", "and", "the", "address", "type", "descriptions", "of", "each", "student", "?" ]
[ { "id": 1, "type": "column", "value": "address_type_description" }, { "id": 4, "type": "table", "value": "students_addresses" }, { "id": 2, "type": "table", "value": "ref_address_types" }, { "id": 5, "type": "column", "value": "address_type_code" }, { "id": 0, "type": "column", "value": "student_details" }, { "id": 6, "type": "column", "value": "student_id" }, { "id": 3, "type": "table", "value": "students" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [ 7, 8 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,848
college_2
spider:train_spider.json:1354
Find the department name of the instructor whose name contains 'Soisalon'.
SELECT dept_name FROM instructor WHERE name LIKE '%Soisalon%'
[ "Find", "the", "department", "name", "of", "the", "instructor", "whose", "name", "contains", "'", "Soisalon", "'", "." ]
[ { "id": 0, "type": "table", "value": "instructor" }, { "id": 3, "type": "value", "value": "%Soisalon%" }, { "id": 1, "type": "column", "value": "dept_name" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
14,849
book_press
bird:test.json:1975
What are the names of the publishers that made more than 15 billion profits each year or 1 billion each month?
SELECT name FROM press WHERE Year_Profits_billion > 15 OR Month_Profits_billion > 1
[ "What", "are", "the", "names", "of", "the", "publishers", "that", "made", "more", "than", "15", "billion", "profits", "each", "year", "or", "1", "billion", "each", "month", "?" ]
[ { "id": 4, "type": "column", "value": "month_profits_billion" }, { "id": 2, "type": "column", "value": "year_profits_billion" }, { "id": 0, "type": "table", "value": "press" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "15" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 15, 16, 18 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 17 ] }, { "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", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "B-COLUMN", "O", "O", "O" ]
14,850
bike_share_1
bird:train.json:9005
What is the longest trip duration that started and ended August 29, 2013?
SELECT MAX(duration) FROM trip WHERE start_date LIKE '8/29/2013%' AND end_date LIKE '8/29/2013%'
[ "What", "is", "the", "longest", "trip", "duration", "that", "started", "and", "ended", "August", "29", ",", "2013", "?" ]
[ { "id": 2, "type": "column", "value": "start_date" }, { "id": 3, "type": "value", "value": "8/29/2013%" }, { "id": 1, "type": "column", "value": "duration" }, { "id": 4, "type": "column", "value": "end_date" }, { "id": 0, "type": "table", "value": "trip" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 11, 12, 13 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,851
movie_2
bird:test.json:1822
What are the names of the movie theaters that are playing 'G' or 'PG' rated movies?
SELECT title FROM movies WHERE rating = 'G' OR rating = 'PG'
[ "What", "are", "the", "names", "of", "the", "movie", "theaters", "that", "are", "playing", "'", "G", "'", "or", "'", "PG", "'", "rated", "movies", "?" ]
[ { "id": 0, "type": "table", "value": "movies" }, { "id": 2, "type": "column", "value": "rating" }, { "id": 1, "type": "column", "value": "title" }, { "id": 4, "type": "value", "value": "PG" }, { "id": 3, "type": "value", "value": "G" } ]
[ { "entity_id": 0, "token_idxs": [ 19 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O", "O", "B-TABLE", "O" ]
14,852
public_review_platform
bird:train.json:3810
How many businesses are there in Phoenix city? Find the percentage of businesses in Phoenix city in the total city.
SELECT SUM(CASE WHEN T3.city LIKE 'Phoenix' THEN 1 ELSE 0 END) AS "num" , CAST(SUM(CASE WHEN T3.city LIKE 'Phoenix' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T3.city) FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id
[ "How", "many", "businesses", "are", "there", "in", "Phoenix", "city", "?", "Find", "the", "percentage", "of", "businesses", "in", "Phoenix", "city", "in", "the", "total", "city", "." ]
[ { "id": 1, "type": "table", "value": "business_categories" }, { "id": 3, "type": "column", "value": "business_id" }, { "id": 7, "type": "column", "value": "category_id" }, { "id": 2, "type": "table", "value": "categories" }, { "id": 0, "type": "table", "value": "business" }, { "id": 9, "type": "value", "value": "Phoenix" }, { "id": 6, "type": "column", "value": "city" }, { "id": 5, "type": "value", "value": "100" }, { "id": 4, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,853
sakila_1
spider:train_spider.json:2957
What is the id of the store that has the most items in inventory?
SELECT store_id FROM inventory GROUP BY store_id ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "i", "d", "of", "the", "store", "that", "has", "the", "most", "items", "in", "inventory", "?" ]
[ { "id": 0, "type": "table", "value": "inventory" }, { "id": 1, "type": "column", "value": "store_id" } ]
[ { "entity_id": 0, "token_idxs": [ 14 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,854
aircraft
spider:train_spider.json:4813
List names of all pilot aged 30 or younger in descending alphabetical order.
SELECT Name FROM pilot WHERE Age <= 30 ORDER BY Name DESC
[ "List", "names", "of", "all", "pilot", "aged", "30", "or", "younger", "in", "descending", "alphabetical", "order", "." ]
[ { "id": 0, "type": "table", "value": "pilot" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "age" }, { "id": 3, "type": "value", "value": "30" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "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", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "O", "O" ]
14,855
codebase_community
bird:dev.json:568
Provide the display name of the user who made the vote No.6347.
SELECT T1.DisplayName FROM users AS T1 INNER JOIN votes AS T2 ON T1.Id = T2.UserId WHERE T2.Id = 6347
[ "Provide", "the", "display", "name", "of", "the", "user", "who", "made", "the", "vote", "No.6347", "." ]
[ { "id": 0, "type": "column", "value": "displayname" }, { "id": 5, "type": "column", "value": "userid" }, { "id": 1, "type": "table", "value": "users" }, { "id": 2, "type": "table", "value": "votes" }, { "id": 4, "type": "value", "value": "6347" }, { "id": 3, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-VALUE", "O" ]
14,856
simpson_episodes
bird:train.json:4346
What are the keywords of the episodes which have the air date in 2008?
SELECT T2.keyword FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE SUBSTR(T1.air_date, 1, 4) = '2008';
[ "What", "are", "the", "keywords", "of", "the", "episodes", "which", "have", "the", "air", "date", "in", "2008", "?" ]
[ { "id": 4, "type": "column", "value": "episode_id" }, { "id": 5, "type": "column", "value": "air_date" }, { "id": 0, "type": "column", "value": "keyword" }, { "id": 1, "type": "table", "value": "episode" }, { "id": 2, "type": "table", "value": "keyword" }, { "id": 3, "type": "value", "value": "2008" }, { "id": 6, "type": "value", "value": "1" }, { "id": 7, "type": "value", "value": "4" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 13 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 10, 11 ] }, { "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", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
14,858
mondial_geo
bird:train.json:8502
What year saw the greatest number of organizations created on the European continent?
SELECT STRFTIME('%Y', T4.Established) FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T2.Country = T3.Code INNER JOIN organization AS T4 ON T4.Country = T3.Code WHERE T1.Name = 'Europe' GROUP BY STRFTIME('%Y', T4.Established) ORDER BY COUNT(T4.Name) DESC LIMIT 1
[ "What", "year", "saw", "the", "greatest", "number", "of", "organizations", "created", "on", "the", "European", "continent", "?" ]
[ { "id": 0, "type": "table", "value": "organization" }, { "id": 4, "type": "column", "value": "established" }, { "id": 9, "type": "table", "value": "encompasses" }, { "id": 8, "type": "table", "value": "continent" }, { "id": 10, "type": "column", "value": "continent" }, { "id": 5, "type": "table", "value": "country" }, { "id": 6, "type": "column", "value": "country" }, { "id": 2, "type": "value", "value": "Europe" }, { "id": 1, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "code" }, { "id": 3, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 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", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,860
club_1
spider:train_spider.json:4267
How many clubs does "Linda Smith" have membership for?
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 t3.fname = "Linda" AND t3.lname = "Smith"
[ "How", "many", "clubs", "does", "\"", "Linda", "Smith", "\"", "have", "membership", "for", "?" ]
[ { "id": 2, "type": "table", "value": "member_of_club" }, { "id": 0, "type": "table", "value": "student" }, { "id": 8, "type": "column", "value": "clubid" }, { "id": 3, "type": "column", "value": "stuid" }, { "id": 4, "type": "column", "value": "fname" }, { "id": 5, "type": "column", "value": "Linda" }, { "id": 6, "type": "column", "value": "lname" }, { "id": 7, "type": "column", "value": "Smith" }, { "id": 1, "type": "table", "value": "club" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "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", "B-TABLE", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O" ]
14,861
movie_3
bird:train.json:9323
How many id movies have category id 11?
SELECT COUNT(film_id) FROM film_category WHERE category_id = 11
[ "How", "many", "i", "d", "movies", "have", "category", "i", "d", "11", "?" ]
[ { "id": 0, "type": "table", "value": "film_category" }, { "id": 1, "type": "column", "value": "category_id" }, { "id": 3, "type": "column", "value": "film_id" }, { "id": 2, "type": "value", "value": "11" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 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", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
14,862
election
spider:train_spider.json:2775
For each county, find the name of the county and the number of delegates from that county.
SELECT T1.County_name , COUNT(*) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id
[ "For", "each", "county", ",", "find", "the", "name", "of", "the", "county", "and", "the", "number", "of", "delegates", "from", "that", "county", "." ]
[ { "id": 1, "type": "column", "value": "county_name" }, { "id": 0, "type": "column", "value": "county_id" }, { "id": 3, "type": "table", "value": "election" }, { "id": 4, "type": "column", "value": "district" }, { "id": 2, "type": "table", "value": "county" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,863
company_office
spider:train_spider.json:4558
What are the names of buildings sorted in descending order of building height?
SELECT name FROM buildings ORDER BY Height DESC
[ "What", "are", "the", "names", "of", "buildings", "sorted", "in", "descending", "order", "of", "building", "height", "?" ]
[ { "id": 0, "type": "table", "value": "buildings" }, { "id": 2, "type": "column", "value": "height" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "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", "O", "O", "O", "B-COLUMN", "O" ]
14,864
image_and_language
bird:train.json:7564
Which object has the highest attribute classes?
SELECT OBJ_SAMPLE_ID FROM IMG_OBJ_ATT GROUP BY OBJ_SAMPLE_ID ORDER BY COUNT(OBJ_SAMPLE_ID) DESC LIMIT 1
[ "Which", "object", "has", "the", "highest", "attribute", "classes", "?" ]
[ { "id": 1, "type": "column", "value": "obj_sample_id" }, { "id": 0, "type": "table", "value": "img_obj_att" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O" ]
14,865
e_government
spider:train_spider.json:6342
Which state can address "6862 Kaitlyn Knolls" possibly be in?
SELECT state_province_county FROM addresses WHERE line_1_number_building LIKE "%6862 Kaitlyn Knolls%"
[ "Which", "state", "can", "address", "\"", "6862", "Kaitlyn", "Knolls", "\"", "possibly", "be", "in", "?" ]
[ { "id": 2, "type": "column", "value": "line_1_number_building" }, { "id": 1, "type": "column", "value": "state_province_county" }, { "id": 3, "type": "column", "value": "%6862 Kaitlyn Knolls%" }, { "id": 0, "type": "table", "value": "addresses" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5, 6, 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-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
14,866
tracking_grants_for_research
spider:train_spider.json:4355
When did the first staff member start working?
SELECT date_from FROM Project_Staff ORDER BY date_from ASC LIMIT 1
[ "When", "did", "the", "first", "staff", "member", "start", "working", "?" ]
[ { "id": 0, "type": "table", "value": "project_staff" }, { "id": 1, "type": "column", "value": "date_from" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O" ]
14,867
chinook_1
spider:train_spider.json:817
Find the names of all artists that have "a" in their names.
SELECT Name FROM ARTIST WHERE Name LIKE "%a%"
[ "Find", "the", "names", "of", "all", "artists", "that", "have", "\"", "a", "\"", "in", "their", "names", "." ]
[ { "id": 0, "type": "table", "value": "artist" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "%a%" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 13 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,868
retail_world
bird:train.json:6640
State the name of employee that manages the order from Victuailles en stock?
SELECT DISTINCT T1.FirstName, T1.LastName FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Customers AS T3 ON T2.CustomerID = T3.CustomerID WHERE T3.CompanyName = 'Victuailles en stock'
[ "State", "the", "name", "of", "employee", "that", "manages", "the", "order", "from", "Victuailles", "en", "stock", "?" ]
[ { "id": 4, "type": "value", "value": "Victuailles en stock" }, { "id": 3, "type": "column", "value": "companyname" }, { "id": 7, "type": "column", "value": "customerid" }, { "id": 8, "type": "column", "value": "employeeid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 5, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 6, "type": "table", "value": "orders" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10, 11, 12 ] }, { "entity_id": 5, "token_idxs": [ 4 ] }, { "entity_id": 6, "token_idxs": [ 8 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,869
mondial_geo
bird:train.json:8230
Calculate the population of Arab in each country?
SELECT T2.Percentage * T1.Population FROM country AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Code = T2.Country WHERE T2.Name = 'Arab'
[ "Calculate", "the", "population", "of", "Arab", "in", "each", "country", "?" ]
[ { "id": 1, "type": "table", "value": "ethnicgroup" }, { "id": 4, "type": "column", "value": "percentage" }, { "id": 5, "type": "column", "value": "population" }, { "id": 0, "type": "table", "value": "country" }, { "id": 7, "type": "column", "value": "country" }, { "id": 2, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "Arab" }, { "id": 6, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 2 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 7 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "B-COLUMN", "O" ]
14,870
epinions_1
spider:train_spider.json:1689
Find the id of the item whose title is "orange".
SELECT i_id FROM item WHERE title = "orange"
[ "Find", "the", "i", "d", "of", "the", "item", "whose", "title", "is", "\"", "orange", "\"", "." ]
[ { "id": 3, "type": "column", "value": "orange" }, { "id": 2, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "item" }, { "id": 1, "type": "column", "value": "i_id" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
14,871
shakespeare
bird:train.json:2983
What percentage of all scenes are tragic scenes in Shakespeare's work in 1594?
SELECT CAST(SUM(IIF(T2.GenreType = 'Tragedy', 1, 0)) AS REAL) * 100 / COUNT(T1.Scene) FROM chapters AS T1 INNER JOIN works AS T2 ON T1.work_id = T2.id WHERE T2.Date = '1594'
[ "What", "percentage", "of", "all", "scenes", "are", "tragic", "scenes", "in", "Shakespeare", "'s", "work", "in", "1594", "?" ]
[ { "id": 10, "type": "column", "value": "genretype" }, { "id": 0, "type": "table", "value": "chapters" }, { "id": 4, "type": "column", "value": "work_id" }, { "id": 11, "type": "value", "value": "Tragedy" }, { "id": 1, "type": "table", "value": "works" }, { "id": 7, "type": "column", "value": "scene" }, { "id": 2, "type": "column", "value": "date" }, { "id": 3, "type": "value", "value": "1594" }, { "id": 6, "type": "value", "value": "100" }, { "id": 5, "type": "column", "value": "id" }, { "id": 8, "type": "value", "value": "1" }, { "id": 9, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "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": [ 7 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [ 6 ] }, { "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-VALUE", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
14,872
products_gen_characteristics
spider:train_spider.json:5552
What are the name and typical buying and selling prices of the products that have color described as "yellow"?
SELECT t1.product_name , t1.typical_buying_price , t1.typical_selling_price FROM products AS t1 JOIN ref_colors AS t2 ON t1.color_code = t2.color_code WHERE t2.color_description = "yellow"
[ "What", "are", "the", "name", "and", "typical", "buying", "and", "selling", "prices", "of", "the", "products", "that", "have", "color", "described", "as", "\"", "yellow", "\"", "?" ]
[ { "id": 2, "type": "column", "value": "typical_selling_price" }, { "id": 1, "type": "column", "value": "typical_buying_price" }, { "id": 5, "type": "column", "value": "color_description" }, { "id": 0, "type": "column", "value": "product_name" }, { "id": 4, "type": "table", "value": "ref_colors" }, { "id": 7, "type": "column", "value": "color_code" }, { "id": 3, "type": "table", "value": "products" }, { "id": 6, "type": "column", "value": "yellow" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [ 7, 8, 9 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 16 ] }, { "entity_id": 6, "token_idxs": [ 19 ] }, { "entity_id": 7, "token_idxs": [ 15 ] }, { "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", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
14,873
movie_1
spider:train_spider.json:2447
What is the id of the reviewer named Daniel Lewis?
SELECT rID FROM Reviewer WHERE name = "Daniel Lewis"
[ "What", "is", "the", "i", "d", "of", "the", "reviewer", "named", "Daniel", "Lewis", "?" ]
[ { "id": 3, "type": "column", "value": "Daniel Lewis" }, { "id": 0, "type": "table", "value": "reviewer" }, { "id": 2, "type": "column", "value": "name" }, { "id": 1, "type": "column", "value": "rid" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O" ]
14,874
regional_sales
bird:train.json:2667
Mention the customer names and IDs which ordered total net profit of above 5000 USD through online channel.
SELECT DISTINCT `Customer Names`, CustomerID FROM ( SELECT T2.`Customer Names`, T2.CustomerID , SUM(REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '')) AS T FROM `Sales Orders` T1 INNER JOIN Customers T2 ON T2.CustomerID = T1._CustomerID WHERE T1.`Sales Channel` = 'Online' GROUP BY T2.CustomerID ) WHERE T > 5000
[ "Mention", "the", "customer", "names", "and", "IDs", "which", "ordered", "total", "net", "profit", "of", "above", "5000", "USD", "through", "online", "channel", "." ]
[ { "id": 0, "type": "column", "value": "Customer Names" }, { "id": 6, "type": "column", "value": "Sales Channel" }, { "id": 4, "type": "table", "value": "Sales Orders" }, { "id": 8, "type": "column", "value": "_customerid" }, { "id": 1, "type": "column", "value": "customerid" }, { "id": 9, "type": "column", "value": "Unit Price" }, { "id": 5, "type": "table", "value": "customers" }, { "id": 11, "type": "column", "value": "Unit Cost" }, { "id": 7, "type": "value", "value": "Online" }, { "id": 3, "type": "value", "value": "5000" }, { "id": 2, "type": "column", "value": "t" }, { "id": 10, "type": "value", "value": "," } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 13 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 2 ] }, { "entity_id": 6, "token_idxs": [ 17 ] }, { "entity_id": 7, "token_idxs": [ 16 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 9, 10 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,875
movie_3
bird:train.json:9374
Where can you rent the movie 'Wyoming Storm'? Identify the address of the rental store and the rental rate.
SELECT T2.store_id, T1.address, T4.rental_rate FROM address AS T1 INNER JOIN store AS T2 ON T1.address_id = T2.address_id INNER JOIN inventory AS T3 ON T2.store_id = T3.store_id INNER JOIN film AS T4 ON T3.film_id = T4.film_id WHERE T4.title = 'WYOMING STORM'
[ "Where", "can", "you", "rent", "the", "movie", "'", "Wyoming", "Storm", "'", "?", "Identify", "the", "address", "of", "the", "rental", "store", "and", "the", "rental", "rate", "." ]
[ { "id": 5, "type": "value", "value": "WYOMING STORM" }, { "id": 2, "type": "column", "value": "rental_rate" }, { "id": 10, "type": "column", "value": "address_id" }, { "id": 6, "type": "table", "value": "inventory" }, { "id": 0, "type": "column", "value": "store_id" }, { "id": 1, "type": "column", "value": "address" }, { "id": 7, "type": "column", "value": "film_id" }, { "id": 8, "type": "table", "value": "address" }, { "id": 4, "type": "column", "value": "title" }, { "id": 9, "type": "table", "value": "store" }, { "id": 3, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 20, 21 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7, 8 ] }, { "entity_id": 6, "token_idxs": [ 11 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 13 ] }, { "entity_id": 9, "token_idxs": [ 17 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,876
codebase_comments
bird:train.json:614
Give the repository Url of the one with most solutions.
SELECT T1.Url FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId GROUP BY T2.RepoId ORDER BY COUNT(T2.RepoId) DESC LIMIT 1
[ "Give", "the", "repository", "Url", "of", "the", "one", "with", "most", "solutions", "." ]
[ { "id": 3, "type": "table", "value": "solution" }, { "id": 0, "type": "column", "value": "repoid" }, { "id": 2, "type": "table", "value": "repo" }, { "id": 1, "type": "column", "value": "url" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "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", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,877
tracking_orders
spider:train_spider.json:6888
Find the order id and customer id associated with the oldest order.
SELECT order_id , customer_id FROM orders ORDER BY date_order_placed LIMIT 1
[ "Find", "the", "order", "i", "d", "and", "customer", "i", "d", "associated", "with", "the", "oldest", "order", "." ]
[ { "id": 3, "type": "column", "value": "date_order_placed" }, { "id": 2, "type": "column", "value": "customer_id" }, { "id": 1, "type": "column", "value": "order_id" }, { "id": 0, "type": "table", "value": "orders" } ]
[ { "entity_id": 0, "token_idxs": [ 13 ] }, { "entity_id": 1, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 6, 7, 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-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
14,878
student_loan
bird:train.json:4497
List any ten male students who enlisted for foreign legion.
SELECT T1.name FROM enlist AS T1 INNER JOIN male AS T2 ON T2.name = T1.name WHERE T1.organ = 'foreign_legion' LIMIT 10
[ "List", "any", "ten", "male", "students", "who", "enlisted", "for", "foreign", "legion", "." ]
[ { "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" }, { "id": 2, "type": "table", "value": "male" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "B-COLUMN", "B-VALUE", "O" ]
14,880
donor
bird:train.json:3294
Which item provided for projects with Mathematics as a primary subject is the most expensive?
SELECT T1.item_name FROM resources AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T2.primary_focus_subject = 'Mathematics' ORDER BY T1.item_unit_price DESC LIMIT 1
[ "Which", "item", "provided", "for", "projects", "with", "Mathematics", "as", "a", "primary", "subject", "is", "the", "most", "expensive", "?" ]
[ { "id": 3, "type": "column", "value": "primary_focus_subject" }, { "id": 5, "type": "column", "value": "item_unit_price" }, { "id": 4, "type": "value", "value": "Mathematics" }, { "id": 0, "type": "column", "value": "item_name" }, { "id": 1, "type": "table", "value": "resources" }, { "id": 6, "type": "column", "value": "projectid" }, { "id": 2, "type": "table", "value": "projects" } ]
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[ "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
14,881
retails
bird:train.json:6737
Calculate the percentage of suppliers in Germany.
SELECT CAST(SUM(IIF(T2.n_name = 'GERMANY', 1, 0)) AS REAL) * 100 / COUNT(T1.s_suppkey) FROM supplier AS T1 INNER JOIN nation AS T2 ON T1.s_nationkey = T2.n_nationkey WHERE T1.s_acctbal < 0
[ "Calculate", "the", "percentage", "of", "suppliers", "in", "Germany", "." ]
[ { "id": 4, "type": "column", "value": "s_nationkey" }, { "id": 5, "type": "column", "value": "n_nationkey" }, { "id": 2, "type": "column", "value": "s_acctbal" }, { "id": 7, "type": "column", "value": "s_suppkey" }, { "id": 0, "type": "table", "value": "supplier" }, { "id": 10, "type": "value", "value": "GERMANY" }, { "id": 1, "type": "table", "value": "nation" }, { "id": 9, "type": "column", "value": "n_name" }, { "id": 6, "type": "value", "value": "100" }, { "id": 3, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
14,882
synthea
bird:train.json:1500
Among all patients who sought medical attention in 2010 due to contact dermatitis, identify the percentage of females.
SELECT CAST(SUM(CASE WHEN T2.gender = 'F' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.PATIENT) FROM encounters AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE strftime('%Y', T1.DATE) = '2010' AND T1.REASONDESCRIPTION = 'Contact dermatitis'
[ "Among", "all", "patients", "who", "sought", "medical", "attention", "in", "2010", "due", "to", "contact", "dermatitis", ",", "identify", "the", "percentage", "of", "females", "." ]
[ { "id": 5, "type": "value", "value": "Contact dermatitis" }, { "id": 4, "type": "column", "value": "reasondescription" }, { "id": 0, "type": "table", "value": "encounters" }, { "id": 1, "type": "table", "value": "patients" }, { "id": 2, "type": "column", "value": "patient" }, { "id": 11, "type": "column", "value": "gender" }, { "id": 3, "type": "value", "value": "2010" }, { "id": 8, "type": "column", "value": "date" }, { "id": 6, "type": "value", "value": "100" }, { "id": 7, "type": "value", "value": "%Y" }, { "id": 9, "type": "value", "value": "0" }, { "id": 10, "type": "value", "value": "1" }, { "id": 12, "type": "value", "value": "F" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
14,883
bike_share_1
bird:train.json:9018
What is the average duration of bike trips in the city of Palo Alto?
SELECT AVG(T1.duration) FROM trip AS T1 LEFT JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.city = 'Palo Alto'
[ "What", "is", "the", "average", "duration", "of", "bike", "trips", "in", "the", "city", "of", "Palo", "Alto", "?" ]
[ { "id": 6, "type": "column", "value": "start_station_name" }, { "id": 3, "type": "value", "value": "Palo Alto" }, { "id": 4, "type": "column", "value": "duration" }, { "id": 1, "type": "table", "value": "station" }, { "id": 0, "type": "table", "value": "trip" }, { "id": 2, "type": "column", "value": "city" }, { "id": 5, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 12, 13 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
14,885
art_1
bird:test.json:1275
What are the titles of paintings that have a width less than 600 or a height taller taller than 800?
SELECT title FROM paintings WHERE width_mm < 600 OR height_mm > 800
[ "What", "are", "the", "titles", "of", "paintings", "that", "have", "a", "width", "less", "than", "600", "or", "a", "height", "taller", "taller", "than", "800", "?" ]
[ { "id": 0, "type": "table", "value": "paintings" }, { "id": 4, "type": "column", "value": "height_mm" }, { "id": 2, "type": "column", "value": "width_mm" }, { "id": 1, "type": "column", "value": "title" }, { "id": 3, "type": "value", "value": "600" }, { "id": 5, "type": "value", "value": "800" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]