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1,069
public_review_platform
bird:train.json:4061
Please indicate the business id have the closing time with the category of Arts & Entertainment on Sunday.
SELECT T1.business_id, T3.closing_time FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business_Hours AS T3 ON T1.business_id = T3.business_id INNER JOIN Days AS T4 ON T3.day_id = T4.day_id WHERE T2.category_name = 'Arts & Entertainment' AND T4.day_of_week = 'Sunday'
[ "Please", "indicate", "the", "business", "i", "d", "have", "the", "closing", "time", "with", "the", "category", "of", "Arts", "&", "Entertainment", "on", "Sunday", "." ]
[ { "id": 6, "type": "value", "value": "Arts & Entertainment" }, { "id": 9, "type": "table", "value": "business_categories" }, { "id": 3, "type": "table", "value": "business_hours" }, { "id": 5, "type": "column", "value": "category_name" }, { "id": 1, "type": "column", "value": "closing_time" }, { "id": 0, "type": "column", "value": "business_id" }, { "id": 7, "type": "column", "value": "day_of_week" }, { "id": 11, "type": "column", "value": "category_id" }, { "id": 10, "type": "table", "value": "categories" }, { "id": 4, "type": "column", "value": "day_id" }, { "id": 8, "type": "value", "value": "Sunday" }, { "id": 2, "type": "table", "value": "days" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
1,070
movielens
bird:train.json:2297
Please list all horror films that have a rating of 1.
SELECT T1.movieid FROM u2base AS T1 INNER JOIN movies2directors AS T2 ON T1.movieid = T2.movieid WHERE T1.rating = 1 AND T2.genre = 'Horror'
[ "Please", "list", "all", "horror", "films", "that", "have", "a", "rating", "of", "1", "." ]
[ { "id": 2, "type": "table", "value": "movies2directors" }, { "id": 0, "type": "column", "value": "movieid" }, { "id": 1, "type": "table", "value": "u2base" }, { "id": 3, "type": "column", "value": "rating" }, { "id": 6, "type": "value", "value": "Horror" }, { "id": 5, "type": "column", "value": "genre" }, { "id": 4, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
1,071
codebase_community
bird:dev.json:692
How long did it take the user, known by his or her display name 'Zolomon' to get the badge? Count from the date the user's account was created.
SELECT T1.Date - T2.CreationDate FROM badges AS T1 INNER JOIN users AS T2 ON T1.UserId = T2.Id WHERE T2.DisplayName = 'Zolomon'
[ "How", "long", "did", "it", "take", "the", "user", ",", "known", "by", "his", "or", "her", "display", "name", "'", "Zolomon", "'", "to", "get", "the", "badge", "?", "Count", "from", "the", "date", "the", "user", "'s", "account", "was", "created", "." ]
[ { "id": 5, "type": "column", "value": "creationdate" }, { "id": 2, "type": "column", "value": "displayname" }, { "id": 3, "type": "value", "value": "Zolomon" }, { "id": 0, "type": "table", "value": "badges" }, { "id": 6, "type": "column", "value": "userid" }, { "id": 1, "type": "table", "value": "users" }, { "id": 4, "type": "column", "value": "date" }, { "id": 7, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "O", "B-COLUMN", "O" ]
1,072
mondial_geo
bird:train.json:8260
How many organizations are established in the country with the most ethnic groups?
SELECT COUNT(T2.Province) FROM country AS T1 INNER JOIN organization AS T2 ON T1.Code = T2.Country INNER JOIN ethnicGroup AS T3 ON T3.Country = T2.Country GROUP BY T1.Name ORDER BY COUNT(T3.Name) DESC LIMIT 1
[ "How", "many", "organizations", "are", "established", "in", "the", "country", "with", "the", "most", "ethnic", "groups", "?" ]
[ { "id": 4, "type": "table", "value": "organization" }, { "id": 1, "type": "table", "value": "ethnicgroup" }, { "id": 2, "type": "column", "value": "province" }, { "id": 3, "type": "table", "value": "country" }, { "id": 5, "type": "column", "value": "country" }, { "id": 0, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "code" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
1,073
election
spider:train_spider.json:2782
Show the name of the county with the biggest population.
SELECT County_name FROM county ORDER BY Population DESC LIMIT 1
[ "Show", "the", "name", "of", "the", "county", "with", "the", "biggest", "population", "." ]
[ { "id": 1, "type": "column", "value": "county_name" }, { "id": 2, "type": "column", "value": "population" }, { "id": 0, "type": "table", "value": "county" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
1,074
professional_basketball
bird:train.json:2836
Who are the coaches for team with winning rate of 80% and above?
SELECT coachID FROM coaches GROUP BY tmID, coachID, won, lost HAVING CAST(won AS REAL) * 100 / (won + lost) > 80
[ "Who", "are", "the", "coaches", "for", "team", "with", "winning", "rate", "of", "80", "%", "and", "above", "?" ]
[ { "id": 0, "type": "table", "value": "coaches" }, { "id": 2, "type": "column", "value": "coachid" }, { "id": 1, "type": "column", "value": "tmid" }, { "id": 4, "type": "column", "value": "lost" }, { "id": 3, "type": "column", "value": "won" }, { "id": 6, "type": "value", "value": "100" }, { "id": 5, "type": "value", "value": "80" } ]
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[ "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
1,075
icfp_1
spider:train_spider.json:2880
Find the first and last name of the author(s) who wrote the paper "Nameless, Painless".
SELECT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Nameless , Painless"
[ "Find", "the", "first", "and", "last", "name", "of", "the", "author(s", ")", "who", "wrote", "the", "paper", "\"", "Nameless", ",", "Painless", "\"", "." ]
[ { "id": 4, "type": "column", "value": "Nameless , Painless" }, { "id": 6, "type": "table", "value": "authorship" }, { "id": 5, "type": "table", "value": "authors" }, { "id": 7, "type": "column", "value": "paperid" }, { "id": 2, "type": "table", "value": "papers" }, { "id": 8, "type": "column", "value": "authid" }, { "id": 0, "type": "column", "value": "fname" }, { "id": 1, "type": "column", "value": "lname" }, { "id": 3, "type": "column", "value": "title" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
1,076
farm
spider:train_spider.json:37
What are the official names of cities that have hosted more than one competition?
SELECT T1.Official_Name FROM city AS T1 JOIN farm_competition AS T2 ON T1.City_ID = T2.Host_city_ID GROUP BY T2.Host_city_ID HAVING COUNT(*) > 1
[ "What", "are", "the", "official", "names", "of", "cities", "that", "have", "hosted", "more", "than", "one", "competition", "?" ]
[ { "id": 3, "type": "table", "value": "farm_competition" }, { "id": 1, "type": "column", "value": "official_name" }, { "id": 0, "type": "column", "value": "host_city_id" }, { "id": 5, "type": "column", "value": "city_id" }, { "id": 2, "type": "table", "value": "city" }, { "id": 4, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
1,077
retail_world
bird:train.json:6626
How many products supplied by Plutzer Lebensmittelgromrkte AG that is currently out of stock and on order?
SELECT COUNT(T1.ProductID) FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Plutzer Lebensmittelgromrkte AG' AND T1.UnitsInStock = 0 AND T1.UnitsOnOrder = 0
[ "How", "many", "products", "supplied", "by", "Plutzer", "Lebensmittelgromrkte", "AG", "that", "is", "currently", "out", "of", "stock", "and", "on", "order", "?" ]
[ { "id": 5, "type": "value", "value": "Plutzer Lebensmittelgromrkte AG" }, { "id": 6, "type": "column", "value": "unitsinstock" }, { "id": 8, "type": "column", "value": "unitsonorder" }, { "id": 4, "type": "column", "value": "companyname" }, { "id": 3, "type": "column", "value": "supplierid" }, { "id": 1, "type": "table", "value": "suppliers" }, { "id": 2, "type": "column", "value": "productid" }, { "id": 0, "type": "table", "value": "products" }, { "id": 7, "type": "value", "value": "0" } ]
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[ "O", "O", "B-TABLE", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
1,078
soccer_2016
bird:train.json:1955
How many cities are in U.A.E?
SELECT SUM(CASE WHEN T2.Country_Name = 'U.A.E' THEN 1 ELSE 0 END) FROM City AS T1 INNER JOIN country AS T2 ON T1.Country_id = T2.Country_id
[ "How", "many", "cities", "are", "in", "U.A.E", "?" ]
[ { "id": 5, "type": "column", "value": "country_name" }, { "id": 2, "type": "column", "value": "country_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 6, "type": "value", "value": "U.A.E" }, { "id": 0, "type": "table", "value": "city" }, { "id": 3, "type": "value", "value": "0" }, { "id": 4, "type": "value", "value": "1" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
1,079
music_platform_2
bird:train.json:7924
How many people rated 5 for the podcast which title contains the word 'spoiler' under the 'art' category '?
SELECT COUNT(T3.podcast_id) FROM categories AS T1 INNER JOIN podcasts AS T2 ON T2.podcast_id = T1.podcast_id INNER JOIN reviews AS T3 ON T3.podcast_id = T2.podcast_id WHERE T2.title LIKE '%spoilers%' AND T1.category = 'arts' AND T3.rating = 5
[ "How", "many", "people", "rated", "5", "for", "the", "podcast", "which", "title", "contains", "the", "word", "'", "spoiler", "'", "under", "the", "'", "art", "'", "category", "'", "?" ]
[ { "id": 1, "type": "column", "value": "podcast_id" }, { "id": 2, "type": "table", "value": "categories" }, { "id": 5, "type": "value", "value": "%spoilers%" }, { "id": 3, "type": "table", "value": "podcasts" }, { "id": 6, "type": "column", "value": "category" }, { "id": 0, "type": "table", "value": "reviews" }, { "id": 8, "type": "column", "value": "rating" }, { "id": 4, "type": "column", "value": "title" }, { "id": 7, "type": "value", "value": "arts" }, { "id": 9, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "O", "B-VALUE", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "O", "O" ]
1,080
bike_share_1
bird:train.json:9061
How many bikes can be borrowed in San Jose Diridon Caltrain Station at 12:06:01 on 2013/8/29?
SELECT T2.bikes_available FROM station AS T1 INNER JOIN status AS T2 ON T1.id = T2.station_id WHERE T1.name = 'San Jose Diridon Caltrain Station' AND T2.time = '2013/08/29 12:06:01'
[ "How", "many", "bikes", "can", "be", "borrowed", "in", "San", "Jose", "Diridon", "Caltrain", "Station", "at", "12:06:01", "on", "2013/8/29", "?" ]
[ { "id": 6, "type": "value", "value": "San Jose Diridon Caltrain Station" }, { "id": 8, "type": "value", "value": "2013/08/29 12:06:01" }, { "id": 0, "type": "column", "value": "bikes_available" }, { "id": 4, "type": "column", "value": "station_id" }, { "id": 1, "type": "table", "value": "station" }, { "id": 2, "type": "table", "value": "status" }, { "id": 5, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "time" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
1,081
menu
bird:train.json:5512
State the full height and width for menu called "El Fuerte Del Palmar".
SELECT T1.full_height, T1.full_width FROM MenuPage AS T1 INNER JOIN Menu AS T2 ON T2.id = T1.menu_id WHERE T2.name = 'El Fuerte Del Palmar'
[ "State", "the", "full", "height", "and", "width", "for", "menu", "called", "\"", "El", "Fuerte", "Del", "Palmar", "\"", "." ]
[ { "id": 5, "type": "value", "value": "El Fuerte Del Palmar" }, { "id": 0, "type": "column", "value": "full_height" }, { "id": 1, "type": "column", "value": "full_width" }, { "id": 2, "type": "table", "value": "menupage" }, { "id": 7, "type": "column", "value": "menu_id" }, { "id": 3, "type": "table", "value": "menu" }, { "id": 4, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
1,082
ship_mission
spider:train_spider.json:4018
Show codes and fates of missions, and names of ships involved.
SELECT T1.Code , T1.Fate , T2.Name FROM mission AS T1 JOIN ship AS T2 ON T1.Ship_ID = T2.Ship_ID
[ "Show", "codes", "and", "fates", "of", "missions", ",", "and", "names", "of", "ships", "involved", "." ]
[ { "id": 3, "type": "table", "value": "mission" }, { "id": 5, "type": "column", "value": "ship_id" }, { "id": 0, "type": "column", "value": "code" }, { "id": 1, "type": "column", "value": "fate" }, { "id": 2, "type": "column", "value": "name" }, { "id": 4, "type": "table", "value": "ship" } ]
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[ "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O" ]
1,083
food_inspection_2
bird:train.json:6141
What is the full name of the employee with the lowest salary?
SELECT first_name, last_name FROM employee ORDER BY salary ASC LIMIT 1
[ "What", "is", "the", "full", "name", "of", "the", "employee", "with", "the", "lowest", "salary", "?" ]
[ { "id": 1, "type": "column", "value": "first_name" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 3, "type": "column", "value": "salary" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
1,085
chinook_1
spider:train_spider.json:811
Find all the customer information in state NY.
SELECT * FROM CUSTOMER WHERE State = "NY"
[ "Find", "all", "the", "customer", "information", "in", "state", "NY", "." ]
[ { "id": 0, "type": "table", "value": "customer" }, { "id": 1, "type": "column", "value": "state" }, { "id": 2, "type": "column", "value": "NY" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
1,086
card_games
bird:dev.json:497
List the expansion type of the set "Huitième édition".
SELECT type FROM sets WHERE code IN ( SELECT setCode FROM set_translations WHERE translation = 'Huitième édition' )
[ "List", "the", "expansion", "type", "of", "the", "set", "\"", "Huitième", "édition", "\"", "." ]
[ { "id": 3, "type": "table", "value": "set_translations" }, { "id": 6, "type": "value", "value": "Huitième édition" }, { "id": 5, "type": "column", "value": "translation" }, { "id": 4, "type": "column", "value": "setcode" }, { "id": 0, "type": "table", "value": "sets" }, { "id": 1, "type": "column", "value": "type" }, { "id": 2, "type": "column", "value": "code" } ]
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[ "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O" ]
1,087
movies_4
bird:train.json:533
What is the title of the movie with the most keywords?
SELECT T1.title FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id GROUP BY T1.title ORDER BY COUNT(T2.keyword_id) DESC LIMIT 1
[ "What", "is", "the", "title", "of", "the", "movie", "with", "the", "most", "keywords", "?" ]
[ { "id": 2, "type": "table", "value": "movie_keywords" }, { "id": 4, "type": "column", "value": "keyword_id" }, { "id": 3, "type": "column", "value": "movie_id" }, { "id": 0, "type": "column", "value": "title" }, { "id": 1, "type": "table", "value": "movie" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
1,088
restaurant_1
spider:train_spider.json:2827
What is the gender of the student Linda Smith?
SELECT Sex FROM Student WHERE Fname = "Linda" AND Lname = "Smith";
[ "What", "is", "the", "gender", "of", "the", "student", "Linda", "Smith", "?" ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 2, "type": "column", "value": "fname" }, { "id": 3, "type": "column", "value": "Linda" }, { "id": 4, "type": "column", "value": "lname" }, { "id": 5, "type": "column", "value": "Smith" }, { "id": 1, "type": "column", "value": "sex" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O" ]
1,089
movies_4
bird:train.json:469
List the title of movies in Latin released between 1/01/1990 and 12/31/1995.
SELECT T1.title FROM movie AS T1 INNER JOIN movie_languages AS T2 ON T1.movie_id = T2.movie_id INNER JOIN language AS T3 ON T2.language_id = T3.language_id WHERE T3.language_name = 'Latin' AND T1.release_date BETWEEN '1990-01-01' AND '1995-12-31'
[ "List", "the", "title", "of", "movies", "in", "Latin", "released", "between", "1/01/1990", "and", "12/31/1995", "." ]
[ { "id": 3, "type": "table", "value": "movie_languages" }, { "id": 5, "type": "column", "value": "language_name" }, { "id": 7, "type": "column", "value": "release_date" }, { "id": 4, "type": "column", "value": "language_id" }, { "id": 8, "type": "value", "value": "1990-01-01" }, { "id": 9, "type": "value", "value": "1995-12-31" }, { "id": 1, "type": "table", "value": "language" }, { "id": 10, "type": "column", "value": "movie_id" }, { "id": 0, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "movie" }, { "id": 6, "type": "value", "value": "Latin" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "O" ]
1,090
conference
bird:test.json:1075
Show institution name which there is no staff in our record.
SELECT institution_name FROM institution WHERE institution_id NOT IN (SELECT institution_id FROM staff)
[ "Show", "institution", "name", "which", "there", "is", "no", "staff", "in", "our", "record", "." ]
[ { "id": 1, "type": "column", "value": "institution_name" }, { "id": 2, "type": "column", "value": "institution_id" }, { "id": 0, "type": "table", "value": "institution" }, { "id": 3, "type": "table", "value": "staff" } ]
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[ "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
1,091
financial
bird:dev.json:170
How many credit card withdrawals were recorded after 1995?
SELECT COUNT(account_id) FROM trans WHERE STRFTIME('%Y', date) > '1995' AND operation = 'VYBER KARTOU'
[ "How", "many", "credit", "card", "withdrawals", "were", "recorded", "after", "1995", "?" ]
[ { "id": 4, "type": "value", "value": "VYBER KARTOU" }, { "id": 1, "type": "column", "value": "account_id" }, { "id": 3, "type": "column", "value": "operation" }, { "id": 0, "type": "table", "value": "trans" }, { "id": 2, "type": "value", "value": "1995" }, { "id": 6, "type": "column", "value": "date" }, { "id": 5, "type": "value", "value": "%Y" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
1,092
works_cycles
bird:train.json:7077
Among the employees who are married and wish to receive e-mail promotions, how much higher is their highest pay rate from the average pay rate?
SELECT MAX(T1.Rate) - SUM(T1.Rate) / COUNT(T1.BusinessEntityID) FROM EmployeePayHistory AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN Employee AS T3 ON T2.BusinessEntityID = T3.BusinessEntityID WHERE T2.EmailPromotion = 2 AND T3.MaritalStatus = 'M'
[ "Among", "the", "employees", "who", "are", "married", "and", "wish", "to", "receive", "e", "-", "mail", "promotions", ",", "how", "much", "higher", "is", "their", "highest", "pay", "rate", "from", "the", "average", "pay", "rate", "?" ]
[ { "id": 1, "type": "table", "value": "employeepayhistory" }, { "id": 3, "type": "column", "value": "businessentityid" }, { "id": 4, "type": "column", "value": "emailpromotion" }, { "id": 6, "type": "column", "value": "maritalstatus" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 2, "type": "table", "value": "person" }, { "id": 8, "type": "column", "value": "rate" }, { "id": 5, "type": "value", "value": "2" }, { "id": 7, "type": "value", "value": "M" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,093
public_review_platform
bird:train.json:3761
How many users have "uber" number of fans?
SELECT COUNT(user_id) FROM Users WHERE user_fans LIKE 'Uber'
[ "How", "many", "users", "have", "\"", "uber", "\"", "number", "of", "fans", "?" ]
[ { "id": 1, "type": "column", "value": "user_fans" }, { "id": 3, "type": "column", "value": "user_id" }, { "id": 0, "type": "table", "value": "users" }, { "id": 2, "type": "value", "value": "Uber" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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-VALUE", "O", "O", "O", "O", "O" ]
1,094
language_corpus
bird:train.json:5742
Which Wikipedia page number has the highest number of words in the Catalan language?
SELECT page FROM pages WHERE words = ( SELECT MAX(words) FROM pages )
[ "Which", "Wikipedia", "page", "number", "has", "the", "highest", "number", "of", "words", "in", "the", "Catalan", "language", "?" ]
[ { "id": 0, "type": "table", "value": "pages" }, { "id": 2, "type": "column", "value": "words" }, { "id": 1, "type": "column", "value": "page" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
1,095
human_resources
bird:train.json:8958
What is Kenneth Charles's position title?
SELECT T2.positiontitle FROM employee AS T1 INNER JOIN position AS T2 ON T1.positionID = T2.positionID WHERE T1.firstname = 'Kenneth' AND T1.lastname = 'Charles'
[ "What", "is", "Kenneth", "Charles", "'s", "position", "title", "?" ]
[ { "id": 0, "type": "column", "value": "positiontitle" }, { "id": 3, "type": "column", "value": "positionid" }, { "id": 4, "type": "column", "value": "firstname" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 2, "type": "table", "value": "position" }, { "id": 6, "type": "column", "value": "lastname" }, { "id": 5, "type": "value", "value": "Kenneth" }, { "id": 7, "type": "value", "value": "Charles" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 2 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 3 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "B-VALUE", "O", "B-TABLE", "B-COLUMN", "O" ]
1,096
apartment_rentals
spider:train_spider.json:1198
Show all distinct building descriptions.
SELECT DISTINCT building_description FROM Apartment_Buildings
[ "Show", "all", "distinct", "building", "descriptions", "." ]
[ { "id": 1, "type": "column", "value": "building_description" }, { "id": 0, "type": "table", "value": "apartment_buildings" } ]
[ { "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" ]
1,097
party_host
spider:train_spider.json:2674
Show the most common nationality of hosts.
SELECT Nationality FROM HOST GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1
[ "Show", "the", "most", "common", "nationality", "of", "hosts", "." ]
[ { "id": 1, "type": "column", "value": "nationality" }, { "id": 0, "type": "table", "value": "host" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "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", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
1,098
voter_2
spider:train_spider.json:5511
Find the major that is studied by the most female students.
SELECT Major FROM STUDENT WHERE Sex = "F" GROUP BY major ORDER BY count(*) DESC LIMIT 1
[ "Find", "the", "major", "that", "is", "studied", "by", "the", "most", "female", "students", "." ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "major" }, { "id": 2, "type": "column", "value": "sex" }, { "id": 3, "type": "column", "value": "F" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "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", "O", "O", "B-TABLE", "O" ]
1,099
law_episode
bird:train.json:1266
Who was nominated for award no.313? Give the full name.
SELECT T1.name FROM Person AS T1 INNER JOIN Award AS T2 ON T1.person_id = T2.person_id WHERE T2.award_id = 313
[ "Who", "was", "nominated", "for", "award", "no.313", "?", "Give", "the", "full", "name", "." ]
[ { "id": 5, "type": "column", "value": "person_id" }, { "id": 3, "type": "column", "value": "award_id" }, { "id": 1, "type": "table", "value": "person" }, { "id": 2, "type": "table", "value": "award" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "313" } ]
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[ "O", "O", "O", "O", "B-TABLE", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,100
manufactory_1
spider:train_spider.json:5311
What is the total revenue of each manufacturer?
SELECT sum(revenue) , name FROM manufacturers GROUP BY name
[ "What", "is", "the", "total", "revenue", "of", "each", "manufacturer", "?" ]
[ { "id": 0, "type": "table", "value": "manufacturers" }, { "id": 2, "type": "column", "value": "revenue" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
1,101
conference
bird:test.json:1074
For each institution id , how many staff members does each institution have that was founded after 1800 ? return their names .
select t1.institution_name , count(*) from institution as t1 join staff as t2 on t1.institution_id = t2.institution_id where t1.founded > 1800 group by t2.institution_id
[ "For", "each", "institution", "i", "d", ",", "how", "many", "staff", "members", "does", "each", "institution", "have", "that", "was", "founded", "after", "1800", "?", "return", "their", "names", "." ]
[ { "id": 1, "type": "column", "value": "institution_name" }, { "id": 0, "type": "column", "value": "institution_id" }, { "id": 2, "type": "table", "value": "institution" }, { "id": 4, "type": "column", "value": "founded" }, { "id": 3, "type": "table", "value": "staff" }, { "id": 5, "type": "value", "value": "1800" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O" ]
1,102
book_1
bird:test.json:575
What is the title of the book written by George Orwell that has the lowest sale price?
SELECT T1.title FROM Book AS T1 JOIN Author_book AS T2 ON T1.isbn = T2.isbn JOIN Author AS T3 ON T2.Author = T3.idAuthor WHERE T3.name = "George Orwell" ORDER BY T1.saleprice LIMIT 1
[ "What", "is", "the", "title", "of", "the", "book", "written", "by", "George", "Orwell", "that", "has", "the", "lowest", "sale", "price", "?" ]
[ { "id": 3, "type": "column", "value": "George Orwell" }, { "id": 6, "type": "table", "value": "author_book" }, { "id": 4, "type": "column", "value": "saleprice" }, { "id": 8, "type": "column", "value": "idauthor" }, { "id": 1, "type": "table", "value": "author" }, { "id": 7, "type": "column", "value": "author" }, { "id": 0, "type": "column", "value": "title" }, { "id": 2, "type": "column", "value": "name" }, { "id": 5, "type": "table", "value": "book" }, { "id": 9, "type": "column", "value": "isbn" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [ 15, 16 ] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 1 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
1,103
sales_in_weather
bird:train.json:8211
What was the difference of number of units sold in station number 1 and number 2 on year 2012?
SELECT SUM(CASE WHEN T1.station_nbr = 1 THEN units ELSE 0 END) - SUM(CASE WHEN T1.station_nbr = 2 THEN units ELSE 0 END) FROM relation AS T1 INNER JOIN sales_in_weather AS T2 ON T1.store_nbr = T2.store_nbr WHERE T2.`date` LIKE '%2012%'
[ "What", "was", "the", "difference", "of", "number", "of", "units", "sold", "in", "station", "number", "1", "and", "number", "2", "on", "year", "2012", "?" ]
[ { "id": 1, "type": "table", "value": "sales_in_weather" }, { "id": 7, "type": "column", "value": "station_nbr" }, { "id": 4, "type": "column", "value": "store_nbr" }, { "id": 0, "type": "table", "value": "relation" }, { "id": 3, "type": "value", "value": "%2012%" }, { "id": 6, "type": "column", "value": "units" }, { "id": 2, "type": "column", "value": "date" }, { "id": 5, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" }, { "id": 9, "type": "value", "value": "2" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O", "O", "B-VALUE", "O", "O", "B-VALUE", "O" ]
1,105
public_review_platform
bird:train.json:3780
How many "5" star reviews does the Yelp business No. "10682" get?
SELECT COUNT(review_length) FROM Reviews WHERE business_id = 10682 AND review_stars = 5
[ "How", "many", "\"", "5", "\"", "star", "reviews", "does", "the", "Yelp", "business", "No", ".", "\"", "10682", "\"", "get", "?" ]
[ { "id": 1, "type": "column", "value": "review_length" }, { "id": 4, "type": "column", "value": "review_stars" }, { "id": 2, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "reviews" }, { "id": 3, "type": "value", "value": "10682" }, { "id": 5, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 7, 8 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3 ] }, { "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", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
1,106
program_share
spider:train_spider.json:3750
find the number of different programs that are broadcast during night time.
SELECT count(DISTINCT program_id) FROM broadcast WHERE time_of_day = 'Night'
[ "find", "the", "number", "of", "different", "programs", "that", "are", "broadcast", "during", "night", "time", "." ]
[ { "id": 1, "type": "column", "value": "time_of_day" }, { "id": 3, "type": "column", "value": "program_id" }, { "id": 0, "type": "table", "value": "broadcast" }, { "id": 2, "type": "value", "value": "Night" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "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", "B-TABLE", "O", "B-VALUE", "O", "O" ]
1,107
chicago_crime
bird:train.json:8631
How many solicit on public way prostitution crimes were arrested in West Garfield Park?
SELECT SUM(CASE WHEN T2.arrest = 'TRUE' THEN 1 ELSE 0 END) FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T1.community_area_no = T2.community_area_no INNER JOIN IUCR AS T3 ON T2.iucr_no = T3.iucr_no WHERE T1.community_area_name = 'West Garfield Park' AND T3.secondary_description = 'SOLICIT ON PUBLIC WAY' AND T3.primary_description = 'PROSTITUTION'
[ "How", "many", "solicit", "on", "public", "way", "prostitution", "crimes", "were", "arrested", "in", "West", "Garfield", "Park", "?" ]
[ { "id": 6, "type": "column", "value": "secondary_description" }, { "id": 7, "type": "value", "value": "SOLICIT ON PUBLIC WAY" }, { "id": 4, "type": "column", "value": "community_area_name" }, { "id": 8, "type": "column", "value": "primary_description" }, { "id": 5, "type": "value", "value": "West Garfield Park" }, { "id": 11, "type": "column", "value": "community_area_no" }, { "id": 1, "type": "table", "value": "community_area" }, { "id": 9, "type": "value", "value": "PROSTITUTION" }, { "id": 3, "type": "column", "value": "iucr_no" }, { "id": 13, "type": "column", "value": "arrest" }, { "id": 2, "type": "table", "value": "crime" }, { "id": 0, "type": "table", "value": "iucr" }, { "id": 14, "type": "value", "value": "TRUE" }, { "id": 10, "type": "value", "value": "0" }, { "id": 12, "type": "value", "value": "1" } ]
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[ "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-VALUE", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
1,108
toxicology
bird:dev.json:225
Please list top five molecules that have double bonds in alphabetical order.
SELECT DISTINCT T.molecule_id FROM bond AS T WHERE T.bond_type = '=' ORDER BY T.molecule_id LIMIT 5
[ "Please", "list", "top", "five", "molecules", "that", "have", "double", "bonds", "in", "alphabetical", "order", "." ]
[ { "id": 1, "type": "column", "value": "molecule_id" }, { "id": 2, "type": "column", "value": "bond_type" }, { "id": 0, "type": "table", "value": "bond" }, { "id": 3, "type": "value", "value": "=" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "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", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
1,109
menu
bird:train.json:5489
How many dishes are included in the menu page ID 144?
SELECT COUNT(*) FROM MenuItem WHERE menu_page_id = 144
[ "How", "many", "dishes", "are", "included", "in", "the", "menu", "page", "ID", "144", "?" ]
[ { "id": 1, "type": "column", "value": "menu_page_id" }, { "id": 0, "type": "table", "value": "menuitem" }, { "id": 2, "type": "value", "value": "144" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 8, 9 ] }, { "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", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
1,110
baseball_1
spider:train_spider.json:3710
Which park did the most people attend in 2008?
SELECT T2.park_name FROM home_game AS T1 JOIN park AS T2 ON T1.park_id = T2.park_id WHERE T1.year = 2008 ORDER BY T1.attendance DESC LIMIT 1;
[ "Which", "park", "did", "the", "most", "people", "attend", "in", "2008", "?" ]
[ { "id": 5, "type": "column", "value": "attendance" }, { "id": 0, "type": "column", "value": "park_name" }, { "id": 1, "type": "table", "value": "home_game" }, { "id": 6, "type": "column", "value": "park_id" }, { "id": 2, "type": "table", "value": "park" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "2008" } ]
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[ "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
1,111
thrombosis_prediction
bird:dev.json:1256
How many patients with a abnormal C-reactive protein don't have their data recorded?
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE (T2.CRP = '+' ) AND T1.Description IS NULL
[ "How", "many", "patients", "with", "a", "abnormal", "C", "-", "reactive", "protein", "do", "n't", "have", "their", "data", "recorded", "?" ]
[ { "id": 5, "type": "column", "value": "description" }, { "id": 1, "type": "table", "value": "laboratory" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 3, "type": "column", "value": "crp" }, { "id": 2, "type": "column", "value": "id" }, { "id": 4, "type": "value", "value": "+" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,112
advertising_agencies
bird:test.json:2119
Show the agency ids and the number of staff in each agent?
SELECT agency_id , count(*) FROM Staff GROUP BY agency_id
[ "Show", "the", "agency", "ids", "and", "the", "number", "of", "staff", "in", "each", "agent", "?" ]
[ { "id": 1, "type": "column", "value": "agency_id" }, { "id": 0, "type": "table", "value": "staff" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
1,114
car_retails
bird:train.json:1566
Please calculate the total payment amount of customers who come from the USA.
SELECT SUM(T1.amount) FROM payments AS T1 INNER JOIN customers AS T2 ON T1.customerNumber = T2.customerNumber WHERE T2.country = 'USA'
[ "Please", "calculate", "the", "total", "payment", "amount", "of", "customers", "who", "come", "from", "the", "USA", "." ]
[ { "id": 5, "type": "column", "value": "customernumber" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 0, "type": "table", "value": "payments" }, { "id": 2, "type": "column", "value": "country" }, { "id": 4, "type": "column", "value": "amount" }, { "id": 3, "type": "value", "value": "USA" } ]
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[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O" ]
1,115
flight_1
spider:train_spider.json:438
What is the salaray and name of the employee with the most certificates to fly planes more than 5000?
SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.distance > 5000 GROUP BY T1.eid ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "salaray", "and", "name", "of", "the", "employee", "with", "the", "most", "certificates", "to", "fly", "planes", "more", "than", "5000", "?" ]
[ { "id": 6, "type": "table", "value": "certificate" }, { "id": 2, "type": "table", "value": "aircraft" }, { "id": 3, "type": "column", "value": "distance" }, { "id": 5, "type": "table", "value": "employee" }, { "id": 1, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "5000" }, { "id": 0, "type": "column", "value": "eid" }, { "id": 7, "type": "column", "value": "aid" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
1,116
music_platform_2
bird:train.json:7931
Name the podcast title, rating and review content created by '76A4C24B6038145'.
SELECT T2.title, T2.rating, T2.content FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T2.author_id = '76A4C24B6038145'
[ "Name", "the", "podcast", "title", ",", "rating", "and", "review", "content", "created", "by", "'", "76A4C24B6038145", "'", "." ]
[ { "id": 6, "type": "value", "value": "76A4C24B6038145" }, { "id": 7, "type": "column", "value": "podcast_id" }, { "id": 5, "type": "column", "value": "author_id" }, { "id": 3, "type": "table", "value": "podcasts" }, { "id": 2, "type": "column", "value": "content" }, { "id": 4, "type": "table", "value": "reviews" }, { "id": 1, "type": "column", "value": "rating" }, { "id": 0, "type": "column", "value": "title" } ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O" ]
1,117
inn_1
spider:train_spider.json:2580
How many times does ROY SWEAZY has reserved a room.
SELECT count(*) FROM Reservations WHERE FirstName = "ROY" AND LastName = "SWEAZY";
[ "How", "many", "times", "does", "ROY", "SWEAZY", "has", "reserved", "a", "room", "." ]
[ { "id": 0, "type": "table", "value": "reservations" }, { "id": 1, "type": "column", "value": "firstname" }, { "id": 3, "type": "column", "value": "lastname" }, { "id": 4, "type": "column", "value": "SWEAZY" }, { "id": 2, "type": "column", "value": "ROY" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "O" ]
1,118
student_loan
bird:train.json:4514
How many male students filed for bankruptcy as compare to female students?
SELECT COUNT(T2.name) - SUM(IIF(T2.name IS NULL, 1, 0)) AS num FROM filed_for_bankrupcy AS T1 LEFT JOIN male AS T2 ON T2.name = T1.name
[ "How", "many", "male", "students", "filed", "for", "bankruptcy", "as", "compare", "to", "female", "students", "?" ]
[ { "id": 0, "type": "table", "value": "filed_for_bankrupcy" }, { "id": 1, "type": "table", "value": "male" }, { "id": 2, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "1" }, { "id": 4, "type": "value", "value": "0" } ]
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[ "O", "O", "B-TABLE", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O" ]
1,119
manufactory_1
spider:train_spider.json:5329
What is all the information of all the products that have a price between 60 and 120?
SELECT * FROM products WHERE price BETWEEN 60 AND 120
[ "What", "is", "all", "the", "information", "of", "all", "the", "products", "that", "have", "a", "price", "between", "60", "and", "120", "?" ]
[ { "id": 0, "type": "table", "value": "products" }, { "id": 1, "type": "column", "value": "price" }, { "id": 3, "type": "value", "value": "120" }, { "id": 2, "type": "value", "value": "60" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O" ]
1,120
card_games
bird:dev.json:353
List all the sets available in Italian translation. State the total number of cards per set.
SELECT T1.name, T1.totalSetSize FROM sets AS T1 INNER JOIN set_translations AS T2 ON T1.code = T2.setCode WHERE T2.language = 'Italian'
[ "List", "all", "the", "sets", "available", "in", "Italian", "translation", ".", "State", "the", "total", "number", "of", "cards", "per", "set", "." ]
[ { "id": 3, "type": "table", "value": "set_translations" }, { "id": 1, "type": "column", "value": "totalsetsize" }, { "id": 4, "type": "column", "value": "language" }, { "id": 5, "type": "value", "value": "Italian" }, { "id": 7, "type": "column", "value": "setcode" }, { "id": 0, "type": "column", "value": "name" }, { "id": 2, "type": "table", "value": "sets" }, { "id": 6, "type": "column", "value": "code" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O" ]
1,121
roller_coaster
spider:train_spider.json:6215
Show the names of countries that have more than one roller coaster.
SELECT T1.Name FROM country AS T1 JOIN roller_coaster AS T2 ON T1.Country_ID = T2.Country_ID GROUP BY T1.Name HAVING COUNT(*) > 1
[ "Show", "the", "names", "of", "countries", "that", "have", "more", "than", "one", "roller", "coaster", "." ]
[ { "id": 2, "type": "table", "value": "roller_coaster" }, { "id": 4, "type": "column", "value": "country_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 10, 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
1,123
car_retails
bird:train.json:1544
List the country and how many customers are there.
SELECT country, COUNT(customerNumber) FROM customers GROUP BY country
[ "List", "the", "country", "and", "how", "many", "customers", "are", "there", "." ]
[ { "id": 2, "type": "column", "value": "customernumber" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 1, "type": "column", "value": "country" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "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", "B-TABLE", "O", "O", "O" ]
1,125
formula_1
bird:dev.json:849
Where can the introduction of the races held on Circuit de Barcelona-Catalunya be found?
SELECT DISTINCT T1.url FROM circuits AS T1 INNER JOIN races AS T2 ON T2.circuitID = T1.circuitId WHERE T1.name = 'Circuit de Barcelona-Catalunya'
[ "Where", "can", "the", "introduction", "of", "the", "races", "held", "on", "Circuit", "de", "Barcelona", "-", "Catalunya", "be", "found", "?" ]
[ { "id": 4, "type": "value", "value": "Circuit de Barcelona-Catalunya" }, { "id": 5, "type": "column", "value": "circuitid" }, { "id": 1, "type": "table", "value": "circuits" }, { "id": 2, "type": "table", "value": "races" }, { "id": 3, "type": "column", "value": "name" }, { "id": 0, "type": "column", "value": "url" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O" ]
1,126
regional_sales
bird:train.json:2604
Among the sales team in South region, write down the numbers of orders made by the sales team ID of one digit.
SELECT COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.Region = 'South' AND T2.SalesTeamID BETWEEN 1 AND 9 GROUP BY T2.SalesTeamID HAVING COUNT(T1.OrderNumber)
[ "Among", "the", "sales", "team", "in", "South", "region", ",", "write", "down", "the", "numbers", "of", "orders", "made", "by", "the", "sales", "team", "ID", "of", "one", "digit", "." ]
[ { "id": 1, "type": "table", "value": "Sales Orders" }, { "id": 4, "type": "column", "value": "_salesteamid" }, { "id": 0, "type": "column", "value": "salesteamid" }, { "id": 3, "type": "column", "value": "ordernumber" }, { "id": 2, "type": "table", "value": "Sales Team" }, { "id": 5, "type": "column", "value": "region" }, { "id": 6, "type": "value", "value": "South" }, { "id": 7, "type": "value", "value": "1" }, { "id": 8, "type": "value", "value": "9" } ]
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[ "O", "O", "B-TABLE", "I-TABLE", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
1,128
network_2
spider:train_spider.json:4400
How many females does this network has?
SELECT count(*) FROM Person WHERE gender = 'female'
[ "How", "many", "females", "does", "this", "network", "has", "?" ]
[ { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "gender" }, { "id": 2, "type": "value", "value": "female" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "O", "O", "O", "O", "O" ]
1,129
insurance_policies
spider:train_spider.json:3853
Give me the the customer details and id for the customers who had two or more policies but did not file any claims.
SELECT T1.customer_details , T1.customer_id FROM Customers AS T1 JOIN Customer_Policies AS T2 ON T1.Customer_id = T2.customer_id GROUP BY T1.customer_id HAVING count(*) >= 2 EXCEPT SELECT T1.customer_details , T1.customer_id FROM Customers AS T1 JOIN Customer_Policies AS T2 ON T1.Customer_id = T2.customer_id JOIN Claims AS T3 ON T2.policy_id = T3.policy_id
[ "Give", "me", "the", "the", "customer", "details", "and", "i", "d", "for", "the", "customers", "who", "had", "two", "or", "more", "policies", "but", "did", "not", "file", "any", "claims", "." ]
[ { "id": 3, "type": "table", "value": "customer_policies" }, { "id": 1, "type": "column", "value": "customer_details" }, { "id": 0, "type": "column", "value": "customer_id" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 6, "type": "column", "value": "policy_id" }, { "id": 5, "type": "table", "value": "claims" }, { "id": 4, "type": "value", "value": "2" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
1,130
culture_company
spider:train_spider.json:6970
Show all publishers and the number of books for each publisher.
SELECT publisher , count(*) FROM book_club GROUP BY publisher
[ "Show", "all", "publishers", "and", "the", "number", "of", "books", "for", "each", "publisher", "." ]
[ { "id": 0, "type": "table", "value": "book_club" }, { "id": 1, "type": "column", "value": "publisher" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,131
law_episode
bird:train.json:1281
Among the episodes that were aired in 1998, how many won an International Monitor Awards?
SELECT COUNT(T1.episode_id) FROM Episode AS T1 INNER JOIN Award AS T2 ON T1.episode_id = T2.episode_id WHERE strftime('%Y', T1.air_date) = '1998' AND T2.organization = 'International Monitor Awards' AND T2.result = 'Winner'
[ "Among", "the", "episodes", "that", "were", "aired", "in", "1998", ",", "how", "many", "won", "an", "International", "Monitor", "Awards", "?" ]
[ { "id": 5, "type": "value", "value": "International Monitor Awards" }, { "id": 4, "type": "column", "value": "organization" }, { "id": 2, "type": "column", "value": "episode_id" }, { "id": 9, "type": "column", "value": "air_date" }, { "id": 0, "type": "table", "value": "episode" }, { "id": 6, "type": "column", "value": "result" }, { "id": 7, "type": "value", "value": "Winner" }, { "id": 1, "type": "table", "value": "award" }, { "id": 3, "type": "value", "value": "1998" }, { "id": 8, "type": "value", "value": "%Y" } ]
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[ "O", "O", "B-TABLE", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "B-TABLE", "O" ]
1,132
government_shift
bird:test.json:383
Find all the details of the customers who have been involved in an interaction with status `` Stuck '' and service and channel detail `` bad '' .
select t1.customer_details from customers as t1 join customer_interactions as t2 on t1.customer_id = t2.customer_id where t2.status_code = "stuck" and services_and_channels_details = "bad"
[ "Find", "all", "the", "details", "of", "the", "customers", "who", "have", "been", "involved", "in", "an", "interaction", "with", "status", "`", "`", "Stuck", "''", "and", "service", "and", "channel", "detail", "`", "`", "bad", "''", "." ]
[ { "id": 6, "type": "column", "value": "services_and_channels_details" }, { "id": 2, "type": "table", "value": "customer_interactions" }, { "id": 0, "type": "column", "value": "customer_details" }, { "id": 3, "type": "column", "value": "customer_id" }, { "id": 4, "type": "column", "value": "status_code" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 5, "type": "column", "value": "stuck" }, { "id": 7, "type": "column", "value": "bad" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
1,134
bike_share_1
bird:train.json:8993
Name all the trips where the bike was borrowed and returned on a different day. State the city where the bike was returned.
SELECT DISTINCT T1.city FROM station AS T1 INNER JOIN trip AS T2 ON T2.start_station_name = T1.name WHERE SUBSTR(CAST(T2.start_date AS TEXT), INSTR(T2.start_date, '/') + 1) - SUBSTR(CAST(T2.start_date AS TEXT), INSTR(T2.start_date, ' ') - 5) <> SUBSTR(CAST(T2.end_date AS TEXT), INSTR(T2.end_date, '/') + 1) - SUBSTR(CAST(T2.end_date AS TEXT), INSTR(T2.end_date, ' ') - 5)
[ "Name", "all", "the", "trips", "where", "the", "bike", "was", "borrowed", "and", "returned", "on", "a", "different", "day", ".", "State", "the", "city", "where", "the", "bike", "was", "returned", "." ]
[ { "id": 3, "type": "column", "value": "start_station_name" }, { "id": 5, "type": "column", "value": "start_date" }, { "id": 8, "type": "column", "value": "end_date" }, { "id": 1, "type": "table", "value": "station" }, { "id": 0, "type": "column", "value": "city" }, { "id": 2, "type": "table", "value": "trip" }, { "id": 4, "type": "column", "value": "name" }, { "id": 6, "type": "value", "value": "1" }, { "id": 7, "type": "value", "value": "5" }, { "id": 9, "type": "value", "value": "/" }, { "id": 10, "type": "value", "value": " " } ]
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[ "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
1,135
shooting
bird:train.json:2471
For case number '134472-2015', list the last name of the officers involved and state the subject statuses.
SELECT T2.last_name, T1.subject_statuses FROM incidents AS T1 INNER JOIN officers AS T2 ON T1.case_number = T2.case_number WHERE T1.case_number = '134472-2015'
[ "For", "case", "number", "'", "134472", "-", "2015", "'", ",", "list", "the", "last", "name", "of", "the", "officers", "involved", "and", "state", "the", "subject", "statuses", "." ]
[ { "id": 1, "type": "column", "value": "subject_statuses" }, { "id": 4, "type": "column", "value": "case_number" }, { "id": 5, "type": "value", "value": "134472-2015" }, { "id": 0, "type": "column", "value": "last_name" }, { "id": 2, "type": "table", "value": "incidents" }, { "id": 3, "type": "table", "value": "officers" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
1,136
real_estate_rentals
bird:test.json:1446
How many properties are there with at least 2 features?
SELECT count(*) FROM Properties GROUP BY property_id HAVING count(*) >= 2;
[ "How", "many", "properties", "are", "there", "with", "at", "least", "2", "features", "?" ]
[ { "id": 1, "type": "column", "value": "property_id" }, { "id": 0, "type": "table", "value": "properties" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
1,138
apartment_rentals
spider:train_spider.json:1214
Return the apartment numbers of the apartments with type code "Flat".
SELECT apt_number FROM Apartments WHERE apt_type_code = "Flat"
[ "Return", "the", "apartment", "numbers", "of", "the", "apartments", "with", "type", "code", "\"", "Flat", "\"", "." ]
[ { "id": 2, "type": "column", "value": "apt_type_code" }, { "id": 0, "type": "table", "value": "apartments" }, { "id": 1, "type": "column", "value": "apt_number" }, { "id": 3, "type": "column", "value": "Flat" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 8, 9 ] }, { "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", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O" ]
1,140
cookbook
bird:train.json:8868
How many calories does the recipe "Raspberry Chiffon Pie" contain?
SELECT T2.calories FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Raspberry Chiffon Pie'
[ "How", "many", "calories", "does", "the", "recipe", "\"", "Raspberry", "Chiffon", "Pie", "\"", "contain", "?" ]
[ { "id": 4, "type": "value", "value": "Raspberry Chiffon Pie" }, { "id": 2, "type": "table", "value": "nutrition" }, { "id": 5, "type": "column", "value": "recipe_id" }, { "id": 0, "type": "column", "value": "calories" }, { "id": 1, "type": "table", "value": "recipe" }, { "id": 3, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 7, 8, 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O" ]
1,141
e_learning
spider:train_spider.json:3849
What are the personal names used both by some course authors and some students?
SELECT personal_name FROM Course_Authors_and_Tutors INTERSECT SELECT personal_name FROM Students
[ "What", "are", "the", "personal", "names", "used", "both", "by", "some", "course", "authors", "and", "some", "students", "?" ]
[ { "id": 0, "type": "table", "value": "course_authors_and_tutors" }, { "id": 2, "type": "column", "value": "personal_name" }, { "id": 1, "type": "table", "value": "students" } ]
[ { "entity_id": 0, "token_idxs": [ 9, 10, 11 ] }, { "entity_id": 1, "token_idxs": [ 13 ] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "B-TABLE", "O" ]
1,142
retail_world
bird:train.json:6329
How much lower in percentage is the unit price of Ikura in order no. 10273 than its standard unit price?
SELECT CAST((T1.UnitPrice - T2.UnitPrice) AS REAL) * 100 / T1.UnitPrice FROM Products AS T1 INNER JOIN `Order Details` AS T2 ON T1.ProductID = T2.ProductID WHERE T2.OrderID = 10273 AND T1.ProductName = 'Ikura'
[ "How", "much", "lower", "in", "percentage", "is", "the", "unit", "price", "of", "Ikura", "in", "order", "no", ".", "10273", "than", "its", "standard", "unit", "price", "?" ]
[ { "id": 1, "type": "table", "value": "Order Details" }, { "id": 6, "type": "column", "value": "productname" }, { "id": 2, "type": "column", "value": "unitprice" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 0, "type": "table", "value": "products" }, { "id": 4, "type": "column", "value": "orderid" }, { "id": 5, "type": "value", "value": "10273" }, { "id": 7, "type": "value", "value": "Ikura" }, { "id": 8, "type": "value", "value": "100" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O" ]
1,143
planet_1
bird:test.json:1869
List all package numbers received by Leo Wong ?
select t1.packagenumber from package as t1 join client as t2 on t1.recipient = t2.accountnumber where t2.name = "leo wong";
[ "List", "all", "package", "numbers", "received", "by", "Leo", "Wong", "?" ]
[ { "id": 0, "type": "column", "value": "packagenumber" }, { "id": 6, "type": "column", "value": "accountnumber" }, { "id": 5, "type": "column", "value": "recipient" }, { "id": 4, "type": "column", "value": "leo wong" }, { "id": 1, "type": "table", "value": "package" }, { "id": 2, "type": "table", "value": "client" }, { "id": 3, "type": "column", "value": "name" } ]
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[ "B-TABLE", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
1,144
medicine_enzyme_interaction
spider:train_spider.json:942
What is the product, chromosome, and porphyria of the enzymes located at 'Cytosol'?
SELECT product , chromosome , porphyria FROM enzyme WHERE LOCATION = 'Cytosol'
[ "What", "is", "the", "product", ",", "chromosome", ",", "and", "porphyria", "of", "the", "enzymes", "located", "at", "'", "Cytosol", "'", "?" ]
[ { "id": 2, "type": "column", "value": "chromosome" }, { "id": 3, "type": "column", "value": "porphyria" }, { "id": 4, "type": "column", "value": "location" }, { "id": 1, "type": "column", "value": "product" }, { "id": 5, "type": "value", "value": "Cytosol" }, { "id": 0, "type": "table", "value": "enzyme" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O", "O" ]
1,145
retail_world
bird:train.json:6480
What is the average sales for each categories?
SELECT AVG(ProductSales) FROM `Sales by Category` GROUP BY CategoryName
[ "What", "is", "the", "average", "sales", "for", "each", "categories", "?" ]
[ { "id": 0, "type": "table", "value": "Sales by Category" }, { "id": 1, "type": "column", "value": "categoryname" }, { "id": 2, "type": "column", "value": "productsales" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "B-COLUMN", "O" ]
1,147
sakila_1
spider:train_spider.json:2928
What is the most popular full name of the actors?
SELECT first_name , last_name FROM actor GROUP BY first_name , last_name ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "most", "popular", "full", "name", "of", "the", "actors", "?" ]
[ { "id": 1, "type": "column", "value": "first_name" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 0, "type": "table", "value": "actor" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
1,148
university_rank
bird:test.json:1790
What is the name and rank of every university in Wisconsin?
SELECT T1.university_name , T2.rank FROM University AS T1 JOIN Overall_ranking AS T2 ON T1.university_id = T2.university_id WHERE T1.state = 'Wisconsin'
[ "What", "is", "the", "name", "and", "rank", "of", "every", "university", "in", "Wisconsin", "?" ]
[ { "id": 0, "type": "column", "value": "university_name" }, { "id": 3, "type": "table", "value": "overall_ranking" }, { "id": 6, "type": "column", "value": "university_id" }, { "id": 2, "type": "table", "value": "university" }, { "id": 5, "type": "value", "value": "Wisconsin" }, { "id": 4, "type": "column", "value": "state" }, { "id": 1, "type": "column", "value": "rank" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
1,149
authors
bird:train.json:3599
List the short name and home page URL of all the international conferences on artificial intelligence.
SELECT ShortName, HomePage FROM Conference WHERE FullName LIKE 'International Conference on Artificial Intelligence%'
[ "List", "the", "short", "name", "and", "home", "page", "URL", "of", "all", "the", "international", "conferences", "on", "artificial", "intelligence", "." ]
[ { "id": 4, "type": "value", "value": "International Conference on Artificial Intelligence%" }, { "id": 0, "type": "table", "value": "conference" }, { "id": 1, "type": "column", "value": "shortname" }, { "id": 2, "type": "column", "value": "homepage" }, { "id": 3, "type": "column", "value": "fullname" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [ 11, 13, 14, 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", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
1,150
swimming
spider:train_spider.json:5621
Find the name and capacity of the stadium where the event named "World Junior" happened.
SELECT t1.name , t1.capacity FROM stadium AS t1 JOIN event AS t2 ON t1.id = t2.stadium_id WHERE t2.name = 'World Junior'
[ "Find", "the", "name", "and", "capacity", "of", "the", "stadium", "where", "the", "event", "named", "\"", "World", "Junior", "\"", "happened", "." ]
[ { "id": 4, "type": "value", "value": "World Junior" }, { "id": 6, "type": "column", "value": "stadium_id" }, { "id": 1, "type": "column", "value": "capacity" }, { "id": 2, "type": "table", "value": "stadium" }, { "id": 3, "type": "table", "value": "event" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "id" } ]
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[ "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O" ]
1,151
sports_competition
spider:train_spider.json:3352
What are the names of all the clubs starting with the oldest?
SELECT name FROM club ORDER BY Start_year ASC
[ "What", "are", "the", "names", "of", "all", "the", "clubs", "starting", "with", "the", "oldest", "?" ]
[ { "id": 2, "type": "column", "value": "start_year" }, { "id": 0, "type": "table", "value": "club" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
1,152
ice_hockey_draft
bird:train.json:6936
What are the names of the players who played for Acadie-Bathurst Titan during the regular season in 1998-1999?
SELECT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '1998-1999' AND T1.GAMETYPE = 'Regular Season' AND T1.TEAM = 'Acadie-Bathurst Titan'
[ "What", "are", "the", "names", "of", "the", "players", "who", "played", "for", "Acadie", "-", "Bathurst", "Titan", "during", "the", "regular", "season", "in", "1998", "-", "1999", "?" ]
[ { "id": 9, "type": "value", "value": "Acadie-Bathurst Titan" }, { "id": 7, "type": "value", "value": "Regular Season" }, { "id": 1, "type": "table", "value": "seasonstatus" }, { "id": 0, "type": "column", "value": "playername" }, { "id": 2, "type": "table", "value": "playerinfo" }, { "id": 5, "type": "value", "value": "1998-1999" }, { "id": 6, "type": "column", "value": "gametype" }, { "id": 3, "type": "column", "value": "eliteid" }, { "id": 4, "type": "column", "value": "season" }, { "id": 8, "type": "column", "value": "team" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
1,153
simpson_episodes
bird:train.json:4294
What is the credited cast for the episode "In the Name of the Grandfather"?
SELECT DISTINCT T2.person FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'In the Name of the Grandfather' AND T2.category = 'Cast' AND T2.credited = 'true';
[ "What", "is", "the", "credited", "cast", "for", "the", "episode", "\"", "In", "the", "Name", "of", "the", "Grandfather", "\"", "?" ]
[ { "id": 5, "type": "value", "value": "In the Name of the Grandfather" }, { "id": 3, "type": "column", "value": "episode_id" }, { "id": 6, "type": "column", "value": "category" }, { "id": 8, "type": "column", "value": "credited" }, { "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": 7, "type": "value", "value": "Cast" }, { "id": 9, "type": "value", "value": "true" } ]
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[ "O", "O", "O", "B-TABLE", "B-VALUE", "B-COLUMN", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
1,154
mondial_geo
bird:train.json:8404
How many times longer is the longest river in Tajikistan than the shortest river?
SELECT MAX(T2.Length) / MIN(T2.Length) FROM located AS T1 INNER JOIN river AS T2 ON T1.River = T2.Name WHERE T1.Country = 'TJ'
[ "How", "many", "times", "longer", "is", "the", "longest", "river", "in", "Tajikistan", "than", "the", "shortest", "river", "?" ]
[ { "id": 0, "type": "table", "value": "located" }, { "id": 2, "type": "column", "value": "country" }, { "id": 6, "type": "column", "value": "length" }, { "id": 1, "type": "table", "value": "river" }, { "id": 4, "type": "column", "value": "river" }, { "id": 5, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "TJ" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,155
store_1
spider:train_spider.json:560
What are the total amount of money in the invoices billed from Chicago, Illinois?
SELECT sum(total) FROM invoices WHERE billing_city = "Chicago" AND billing_state = "IL";
[ "What", "are", "the", "total", "amount", "of", "money", "in", "the", "invoices", "billed", "from", "Chicago", ",", "Illinois", "?" ]
[ { "id": 4, "type": "column", "value": "billing_state" }, { "id": 2, "type": "column", "value": "billing_city" }, { "id": 0, "type": "table", "value": "invoices" }, { "id": 3, "type": "column", "value": "Chicago" }, { "id": 1, "type": "column", "value": "total" }, { "id": 5, "type": "column", "value": "IL" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
1,156
journal_committee
spider:train_spider.json:664
List the names of editors that are not on any journal committee.
SELECT Name FROM editor WHERE editor_id NOT IN (SELECT editor_id FROM journal_committee)
[ "List", "the", "names", "of", "editors", "that", "are", "not", "on", "any", "journal", "committee", "." ]
[ { "id": 3, "type": "table", "value": "journal_committee" }, { "id": 2, "type": "column", "value": "editor_id" }, { "id": 0, "type": "table", "value": "editor" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10, 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
1,157
public_review_platform
bird:train.json:4093
List down the closing day of businesses located at SC State.
SELECT T3.day_id - T2.day_id FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T1.state = 'SC'
[ "List", "down", "the", "closing", "day", "of", "businesses", "located", "at", "SC", "State", "." ]
[ { "id": 5, "type": "table", "value": "business_hours" }, { "id": 6, "type": "column", "value": "business_id" }, { "id": 4, "type": "table", "value": "business" }, { "id": 3, "type": "column", "value": "day_id" }, { "id": 1, "type": "column", "value": "state" }, { "id": 0, "type": "table", "value": "days" }, { "id": 2, "type": "value", "value": "SC" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "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", "B-TABLE", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
1,158
aan_1
bird:test.json:1041
Find the number of papers published in different conferences each year.
SELECT count(*) , venue , YEAR FROM Paper GROUP BY venue , YEAR
[ "Find", "the", "number", "of", "papers", "published", "in", "different", "conferences", "each", "year", "." ]
[ { "id": 0, "type": "table", "value": "paper" }, { "id": 1, "type": "column", "value": "venue" }, { "id": 2, "type": "column", "value": "year" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,159
insurance_policies
spider:train_spider.json:3869
Find the claim id and the number of settlements made for the claim with the most recent settlement date.
SELECT count(*) , T1.claim_id FROM Claims AS T1 JOIN Settlements AS T2 ON T1.claim_id = T2.claim_id GROUP BY T1.claim_id ORDER BY T1.Date_Claim_Settled DESC LIMIT 1
[ "Find", "the", "claim", "i", "d", "and", "the", "number", "of", "settlements", "made", "for", "the", "claim", "with", "the", "most", "recent", "settlement", "date", "." ]
[ { "id": 3, "type": "column", "value": "date_claim_settled" }, { "id": 2, "type": "table", "value": "settlements" }, { "id": 0, "type": "column", "value": "claim_id" }, { "id": 1, "type": "table", "value": "claims" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "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-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,161
country_language
bird:test.json:1379
What are the names of the different official languages, as well as the number of countries that speak each?
SELECT T2.name , COUNT(*) FROM official_languages AS T1 JOIN languages AS T2 ON T1.language_id = T2.id GROUP BY T2.name
[ "What", "are", "the", "names", "of", "the", "different", "official", "languages", ",", "as", "well", "as", "the", "number", "of", "countries", "that", "speak", "each", "?" ]
[ { "id": 1, "type": "table", "value": "official_languages" }, { "id": 3, "type": "column", "value": "language_id" }, { "id": 2, "type": "table", "value": "languages" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,162
video_games
bird:train.json:3402
How many games do not have any sales in Europe?
SELECT COUNT(*) FROM region_sales AS T1 INNER JOIN region AS T2 ON T1.region_id = T2.id WHERE T2.region_name = 'Europe' AND T1.num_sales = 0
[ "How", "many", "games", "do", "not", "have", "any", "sales", "in", "Europe", "?" ]
[ { "id": 0, "type": "table", "value": "region_sales" }, { "id": 4, "type": "column", "value": "region_name" }, { "id": 2, "type": "column", "value": "region_id" }, { "id": 6, "type": "column", "value": "num_sales" }, { "id": 1, "type": "table", "value": "region" }, { "id": 5, "type": "value", "value": "Europe" }, { "id": 3, "type": "column", "value": "id" }, { "id": 7, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
1,164
music_platform_2
bird:train.json:7974
List the urls for all the "fiction-science-fiction" podcasts.
SELECT itunes_url FROM podcasts WHERE podcast_id IN ( SELECT podcast_id FROM categories WHERE category = 'fiction-science-fiction' )
[ "List", "the", "urls", "for", "all", "the", "\"", "fiction", "-", "science", "-", "fiction", "\"", "podcasts", "." ]
[ { "id": 5, "type": "value", "value": "fiction-science-fiction" }, { "id": 1, "type": "column", "value": "itunes_url" }, { "id": 2, "type": "column", "value": "podcast_id" }, { "id": 3, "type": "table", "value": "categories" }, { "id": 0, "type": "table", "value": "podcasts" }, { "id": 4, "type": "column", "value": "category" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
1,165
aan_1
bird:test.json:972
Count the number of papers published by Columbia University in 2009.
SELECT count(DISTINCT T1.paper_id) FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T3.name LIKE "Columbia University" AND T1.year = 2009
[ "Count", "the", "number", "of", "papers", "published", "by", "Columbia", "University", "in", "2009", "." ]
[ { "id": 6, "type": "column", "value": "Columbia University" }, { "id": 4, "type": "column", "value": "affiliation_id" }, { "id": 0, "type": "table", "value": "affiliation" }, { "id": 3, "type": "table", "value": "author_list" }, { "id": 1, "type": "column", "value": "paper_id" }, { "id": 2, "type": "table", "value": "paper" }, { "id": 5, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "2009" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
1,166
student_1
spider:train_spider.json:4037
What are the grade number and classroom number of each class in the list?
SELECT DISTINCT classroom , grade FROM list
[ "What", "are", "the", "grade", "number", "and", "classroom", "number", "of", "each", "class", "in", "the", "list", "?" ]
[ { "id": 1, "type": "column", "value": "classroom" }, { "id": 2, "type": "column", "value": "grade" }, { "id": 0, "type": "table", "value": "list" } ]
[ { "entity_id": 0, "token_idxs": [ 13 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "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", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
1,167
university
bird:train.json:8094
How many Turkish universities are there in the database?
SELECT COUNT(*) FROM university AS T1 INNER JOIN country AS T2 ON T1.country_id = T2.id WHERE T2.country_name = 'Turkey'
[ "How", "many", "Turkish", "universities", "are", "there", "in", "the", "database", "?" ]
[ { "id": 2, "type": "column", "value": "country_name" }, { "id": 0, "type": "table", "value": "university" }, { "id": 4, "type": "column", "value": "country_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 3, "type": "value", "value": "Turkey" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 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-VALUE", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
1,168
superhero
bird:dev.json:784
Provide the full names of vampire heroes.
SELECT T1.full_name FROM superhero AS T1 INNER JOIN race AS T2 ON T1.race_id = T2.id WHERE T2.race = 'Vampire'
[ "Provide", "the", "full", "names", "of", "vampire", "heroes", "." ]
[ { "id": 0, "type": "column", "value": "full_name" }, { "id": 1, "type": "table", "value": "superhero" }, { "id": 4, "type": "value", "value": "Vampire" }, { "id": 5, "type": "column", "value": "race_id" }, { "id": 2, "type": "table", "value": "race" }, { "id": 3, "type": "column", "value": "race" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O" ]
1,170
retail_world
bird:train.json:6551
Provide the list of product IDs and names under the meat/poultry category.
SELECT T2.ProductName, T1.CategoryName FROM Categories AS T1 INNER JOIN Products AS T2 ON T1.CategoryID = T2.CategoryID WHERE T2.ReorderLevel = ( SELECT MAX(ReorderLevel) FROM Products )
[ "Provide", "the", "list", "of", "product", "IDs", "and", "names", "under", "the", "meat", "/", "poultry", "category", "." ]
[ { "id": 1, "type": "column", "value": "categoryname" }, { "id": 4, "type": "column", "value": "reorderlevel" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 2, "type": "table", "value": "categories" }, { "id": 5, "type": "column", "value": "categoryid" }, { "id": 3, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,171
music_1
spider:train_spider.json:3620
What are the top 3 artists with the largest number of songs in the language Bangla?
SELECT T1.artist_name FROM artist AS T1 JOIN song AS T2 ON T1.artist_name = T2.artist_name WHERE T2.languages = "bangla" GROUP BY T2.artist_name ORDER BY count(*) DESC LIMIT 3
[ "What", "are", "the", "top", "3", "artists", "with", "the", "largest", "number", "of", "songs", "in", "the", "language", "Bangla", "?" ]
[ { "id": 0, "type": "column", "value": "artist_name" }, { "id": 3, "type": "column", "value": "languages" }, { "id": 1, "type": "table", "value": "artist" }, { "id": 4, "type": "column", "value": "bangla" }, { "id": 2, "type": "table", "value": "song" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "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", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
1,172
activity_1
spider:train_spider.json:6743
Show all the ranks and the number of male and female faculty for each rank.
SELECT rank , sex , count(*) FROM Faculty GROUP BY rank , sex
[ "Show", "all", "the", "ranks", "and", "the", "number", "of", "male", "and", "female", "faculty", "for", "each", "rank", "." ]
[ { "id": 0, "type": "table", "value": "faculty" }, { "id": 1, "type": "column", "value": "rank" }, { "id": 2, "type": "column", "value": "sex" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
1,173
institution_sports
bird:test.json:1676
Return all the enrollments of institutions in either the city of Vancouver or the city of Calgary .
select sum(enrollment) from institution where city = "vancouver" or city = "calgary"
[ "Return", "all", "the", "enrollments", "of", "institutions", "in", "either", "the", "city", "of", "Vancouver", "or", "the", "city", "of", "Calgary", "." ]
[ { "id": 0, "type": "table", "value": "institution" }, { "id": 1, "type": "column", "value": "enrollment" }, { "id": 3, "type": "column", "value": "vancouver" }, { "id": 4, "type": "column", "value": "calgary" }, { "id": 2, "type": "column", "value": "city" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,174
retails
bird:train.json:6779
Calculate the difference in the average number of low-priority orders shipped by truck in each month of 1995 and 1996.
SELECT (CAST(SUM(IIF(STRFTIME('%Y', T2.l_shipdate) = 1995, 1, 0)) AS REAL) / 12) - (CAST(SUM(IIF(STRFTIME('%Y', T2.l_shipdate) = 1996, 1, 0)) AS REAL) / 12) FROM orders AS T1 INNER JOIN lineitem AS T2 ON T1.o_orderkey = T2.l_orderkey WHERE T1.o_orderpriority = '5-LOW' AND T2.l_shipmode = 'TRUCK'
[ "Calculate", "the", "difference", "in", "the", "average", "number", "of", "low", "-", "priority", "orders", "shipped", "by", "truck", "in", "each", "month", "of", "1995", "and", "1996", "." ]
[ { "id": 4, "type": "column", "value": "o_orderpriority" }, { "id": 2, "type": "column", "value": "o_orderkey" }, { "id": 3, "type": "column", "value": "l_orderkey" }, { "id": 6, "type": "column", "value": "l_shipmode" }, { "id": 14, "type": "column", "value": "l_shipdate" }, { "id": 1, "type": "table", "value": "lineitem" }, { "id": 0, "type": "table", "value": "orders" }, { "id": 5, "type": "value", "value": "5-LOW" }, { "id": 7, "type": "value", "value": "TRUCK" }, { "id": 11, "type": "value", "value": "1995" }, { "id": 12, "type": "value", "value": "1996" }, { "id": 8, "type": "value", "value": "12" }, { "id": 13, "type": "value", "value": "%Y" }, { "id": 9, "type": "value", "value": "1" }, { "id": 10, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
1,175
shipping
bird:train.json:5647
How many cities are in Connecticut?
SELECT COUNT(*) FROM city WHERE state = 'Connecticut'
[ "How", "many", "cities", "are", "in", "Connecticut", "?" ]
[ { "id": 2, "type": "value", "value": "Connecticut" }, { "id": 1, "type": "column", "value": "state" }, { "id": 0, "type": "table", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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-VALUE", "O" ]
1,176
public_review_platform
bird:train.json:3986
List all the businesses that closed at 8PM.
SELECT DISTINCT business_id FROM Business_Hours WHERE closing_time = '8PM'
[ "List", "all", "the", "businesses", "that", "closed", "at", "8PM", "." ]
[ { "id": 0, "type": "table", "value": "business_hours" }, { "id": 2, "type": "column", "value": "closing_time" }, { "id": 1, "type": "column", "value": "business_id" }, { "id": 3, "type": "value", "value": "8PM" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
1,177
movie_2
bird:test.json:1823
Find the name of the movies that are played in either cinema Odeon or Imperial.
SELECT T1.title FROM movies AS T1 JOIN movietheaters AS T2 ON T1.code = T2.movie WHERE T2.name = 'Odeon' OR T2.name = 'Imperial'
[ "Find", "the", "name", "of", "the", "movies", "that", "are", "played", "in", "either", "cinema", "Odeon", "or", "Imperial", "." ]
[ { "id": 2, "type": "table", "value": "movietheaters" }, { "id": 7, "type": "value", "value": "Imperial" }, { "id": 1, "type": "table", "value": "movies" }, { "id": 0, "type": "column", "value": "title" }, { "id": 4, "type": "column", "value": "movie" }, { "id": 6, "type": "value", "value": "Odeon" }, { "id": 3, "type": "column", "value": "code" }, { "id": 5, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [ 2 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "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", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
1,178
customers_and_orders
bird:test.json:301
How many customers do not have an order?
SELECT count(*) FROM Customers WHERE customer_id NOT IN ( SELECT customer_id FROM Customer_orders)
[ "How", "many", "customers", "do", "not", "have", "an", "order", "?" ]
[ { "id": 2, "type": "table", "value": "customer_orders" }, { "id": 1, "type": "column", "value": "customer_id" }, { "id": 0, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
1,179
toxicology
bird:dev.json:240
List all the elements of the toxicology of the molecule "TR004".
SELECT DISTINCT T.element FROM atom AS T WHERE T.molecule_id = 'TR004'
[ "List", "all", "the", "elements", "of", "the", "toxicology", "of", "the", "molecule", "\"", "TR004", "\"", "." ]
[ { "id": 2, "type": "column", "value": "molecule_id" }, { "id": 1, "type": "column", "value": "element" }, { "id": 3, "type": "value", "value": "TR004" }, { "id": 0, "type": "table", "value": "atom" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "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", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
1,180
mondial_geo
bird:train.json:8406
In countries where there is more than one ethnic group, name the ethnic group with the greatest presence in each country and the country to which it corresponds.
SELECT Country, Name FROM ethnicGroup AS T1 WHERE Percentage < 100 AND Percentage = ( SELECT MAX(Percentage) FROM ethnicGroup AS T2 WHERE T1.Country = T2.Country )
[ "In", "countries", "where", "there", "is", "more", "than", "one", "ethnic", "group", ",", "name", "the", "ethnic", "group", "with", "the", "greatest", "presence", "in", "each", "country", "and", "the", "country", "to", "which", "it", "corresponds", "." ]
[ { "id": 0, "type": "table", "value": "ethnicgroup" }, { "id": 3, "type": "column", "value": "percentage" }, { "id": 1, "type": "column", "value": "country" }, { "id": 2, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "100" } ]
[ { "entity_id": 0, "token_idxs": [ 13, 14 ] }, { "entity_id": 1, "token_idxs": [ 24 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
1,181
public_review_platform
bird:train.json:3824
What are the attribute numbers that are related to payment?
SELECT attribute_id FROM Attributes WHERE attribute_name LIKE '%payment%'
[ "What", "are", "the", "attribute", "numbers", "that", "are", "related", "to", "payment", "?" ]
[ { "id": 2, "type": "column", "value": "attribute_name" }, { "id": 1, "type": "column", "value": "attribute_id" }, { "id": 0, "type": "table", "value": "attributes" }, { "id": 3, "type": "value", "value": "%payment%" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O" ]