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15,095
university
bird:train.json:8070
Among the universities with over 20000 students in 2011, how many of them have an international students percentage of over 25% in the same year?
SELECT COUNT(*) FROM university_year WHERE year = 2011 AND pct_international_students > 25 AND num_students > 20000
[ "Among", "the", "universities", "with", "over", "20000", "students", "in", "2011", ",", "how", "many", "of", "them", "have", "an", "international", "students", "percentage", "of", "over", "25", "%", "in", "the", "same", "year", "?" ]
[ { "id": 3, "type": "column", "value": "pct_international_students" }, { "id": 0, "type": "table", "value": "university_year" }, { "id": 5, "type": "column", "value": "num_students" }, { "id": 6, "type": "value", "value": "20000" }, { "id": 1, "type": "column", "value": "year" }, { "id": 2, "type": "value", "value": "2011" }, { "id": 4, "type": "value", "value": "25" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,096
software_company
bird:train.json:8577
What is the ratio of male and female among the age of teenager when the education is above 10?
SELECT CAST(SUM(CASE WHEN SEX = 'Male' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN SEX = 'Female' THEN 1 ELSE 0 END) FROM Customers WHERE age BETWEEN 13 AND 19 AND EDUCATIONNUM > 10
[ "What", "is", "the", "ratio", "of", "male", "and", "female", "among", "the", "age", "of", "teenager", "when", "the", "education", "is", "above", "10", "?" ]
[ { "id": 4, "type": "column", "value": "educationnum" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 9, "type": "value", "value": "Female" }, { "id": 10, "type": "value", "value": "Male" }, { "id": 1, "type": "column", "value": "age" }, { "id": 8, "type": "column", "value": "sex" }, { "id": 2, "type": "value", "value": "13" }, { "id": 3, "type": "value", "value": "19" }, { "id": 5, "type": "value", "value": "10" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
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15,097
music_platform_2
bird:train.json:7973
Which category has the most reviews?
SELECT T1.category FROM categories AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id GROUP BY T1.category ORDER BY COUNT(T2.podcast_id) DESC LIMIT 1
[ "Which", "category", "has", "the", "most", "reviews", "?" ]
[ { "id": 1, "type": "table", "value": "categories" }, { "id": 3, "type": "column", "value": "podcast_id" }, { "id": 0, "type": "column", "value": "category" }, { "id": 2, "type": "table", "value": "reviews" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
15,098
formula_1
bird:dev.json:886
Which year has the most number of races?
SELECT year FROM races GROUP BY year ORDER BY COUNT(round) DESC LIMIT 1
[ "Which", "year", "has", "the", "most", "number", "of", "races", "?" ]
[ { "id": 0, "type": "table", "value": "races" }, { "id": 2, "type": "column", "value": "round" }, { "id": 1, "type": "column", "value": "year" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,099
car_retails
bird:train.json:1625
Who is the sales representitive of Muscle Machine Inc? Please give the employee's full name.
SELECT t2.firstName, t2.lastName FROM customers AS t1 INNER JOIN employees AS t2 ON t1.salesRepEmployeeNumber = t2.employeeNumber WHERE t1.customerName = 'Muscle Machine Inc'
[ "Who", "is", "the", "sales", "representitive", "of", "Muscle", "Machine", "Inc", "?", "Please", "give", "the", "employee", "'s", "full", "name", "." ]
[ { "id": 6, "type": "column", "value": "salesrepemployeenumber" }, { "id": 5, "type": "value", "value": "Muscle Machine Inc" }, { "id": 7, "type": "column", "value": "employeenumber" }, { "id": 4, "type": "column", "value": "customername" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 3, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "lastname" } ]
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[ "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O" ]
15,100
cre_Theme_park
spider:train_spider.json:5958
Find the names of the tourist attractions that is either accessible by walk or at address 660 Shea Crescent.
SELECT T2.Name FROM Locations AS T1 JOIN Tourist_Attractions AS T2 ON T1.Location_ID = T2.Location_ID WHERE T1.Address = "660 Shea Crescent" OR T2.How_to_Get_There = "walk"
[ "Find", "the", "names", "of", "the", "tourist", "attractions", "that", "is", "either", "accessible", "by", "walk", "or", "at", "address", "660", "Shea", "Crescent", "." ]
[ { "id": 2, "type": "table", "value": "tourist_attractions" }, { "id": 5, "type": "column", "value": "660 Shea Crescent" }, { "id": 6, "type": "column", "value": "how_to_get_there" }, { "id": 3, "type": "column", "value": "location_id" }, { "id": 1, "type": "table", "value": "locations" }, { "id": 4, "type": "column", "value": "address" }, { "id": 0, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "walk" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
15,101
music_platform_2
bird:train.json:7970
List all of the two-star reviews and their categories.
SELECT T1.category FROM categories AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T2.rating = 2
[ "List", "all", "of", "the", "two", "-", "star", "reviews", "and", "their", "categories", "." ]
[ { "id": 1, "type": "table", "value": "categories" }, { "id": 5, "type": "column", "value": "podcast_id" }, { "id": 0, "type": "column", "value": "category" }, { "id": 2, "type": "table", "value": "reviews" }, { "id": 3, "type": "column", "value": "rating" }, { "id": 4, "type": "value", "value": "2" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
15,102
machine_repair
spider:train_spider.json:2262
What are the starting years shared by the technicians from the team "CLE" or "CWS"?
SELECT Starting_Year FROM technician WHERE Team = "CLE" INTERSECT SELECT Starting_Year FROM technician WHERE Team = "CWS"
[ "What", "are", "the", "starting", "years", "shared", "by", "the", "technicians", "from", "the", "team", "\"", "CLE", "\"", "or", "\"", "CWS", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "starting_year" }, { "id": 0, "type": "table", "value": "technician" }, { "id": 2, "type": "column", "value": "team" }, { "id": 3, "type": "column", "value": "CLE" }, { "id": 4, "type": "column", "value": "CWS" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,103
simpson_episodes
bird:train.json:4212
In Season 20 Episode 11, how many times was Doofus included in the credit list?
SELECT COUNT(*) FROM Person AS T1 INNER JOIN Credit AS T2 ON T1.name = T2.person WHERE T1.nickname = 'Doofus' AND T2.credited = 'true' AND T2.episode_id = 'S20-E11';
[ "In", "Season", "20", "Episode", "11", ",", "how", "many", "times", "was", "Doofus", "included", "in", "the", "credit", "list", "?" ]
[ { "id": 8, "type": "column", "value": "episode_id" }, { "id": 4, "type": "column", "value": "nickname" }, { "id": 6, "type": "column", "value": "credited" }, { "id": 9, "type": "value", "value": "S20-E11" }, { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "table", "value": "credit" }, { "id": 3, "type": "column", "value": "person" }, { "id": 5, "type": "value", "value": "Doofus" }, { "id": 2, "type": "column", "value": "name" }, { "id": 7, "type": "value", "value": "true" } ]
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[ "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "O" ]
15,104
retail_world
bird:train.json:6456
Among the USA employess, how many of them has PhD title of courtesy?
SELECT COUNT(Country) FROM Employees WHERE TitleOfCourtesy = 'Dr.' AND Country = 'USA'
[ "Among", "the", "USA", "employess", ",", "how", "many", "of", "them", "has", "PhD", "title", "of", "courtesy", "?" ]
[ { "id": 2, "type": "column", "value": "titleofcourtesy" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "country" }, { "id": 3, "type": "value", "value": "Dr." }, { "id": 4, "type": "value", "value": "USA" } ]
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[ "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
15,105
financial
bird:dev.json:96
How many customers who choose statement of weekly issuance are Owner?
SELECT COUNT(T1.account_id) FROM account AS T1 INNER JOIN disp AS T2 ON T1.account_id = T2.account_id WHERE T2.type = 'OWNER' AND T1.frequency = 'POPLATEK TYDNE'
[ "How", "many", "customers", "who", "choose", "statement", "of", "weekly", "issuance", "are", "Owner", "?" ]
[ { "id": 6, "type": "value", "value": "POPLATEK TYDNE" }, { "id": 2, "type": "column", "value": "account_id" }, { "id": 5, "type": "column", "value": "frequency" }, { "id": 0, "type": "table", "value": "account" }, { "id": 4, "type": "value", "value": "OWNER" }, { "id": 1, "type": "table", "value": "disp" }, { "id": 3, "type": "column", "value": "type" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
15,106
customers_card_transactions
spider:train_spider.json:732
How many different card types are there?
SELECT count(DISTINCT card_type_code) FROM Customers_Cards
[ "How", "many", "different", "card", "types", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "customers_cards" }, { "id": 1, "type": "column", "value": "card_type_code" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O" ]
15,107
regional_sales
bird:train.json:2708
Which store in Arizona has the most net profit?
SELECT T2.StoreID FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T2.State = 'Arizona' ORDER BY T1.`Unit Price` - T1.`Unit Cost` DESC LIMIT 1
[ "Which", "store", "in", "Arizona", "has", "the", "most", "net", "profit", "?" ]
[ { "id": 2, "type": "table", "value": "Store Locations" }, { "id": 1, "type": "table", "value": "Sales Orders" }, { "id": 6, "type": "column", "value": "Unit Price" }, { "id": 7, "type": "column", "value": "Unit Cost" }, { "id": 5, "type": "column", "value": "_storeid" }, { "id": 0, "type": "column", "value": "storeid" }, { "id": 4, "type": "value", "value": "Arizona" }, { "id": 3, "type": "column", "value": "state" } ]
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[ "O", "B-COLUMN", "B-TABLE", "B-VALUE", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O" ]
15,108
retail_world
bird:train.json:6514
Which country are the majority of the suppliers located?
SELECT Country FROM Suppliers GROUP BY Country ORDER BY COUNT(SupplierID) DESC LIMIT 1
[ "Which", "country", "are", "the", "majority", "of", "the", "suppliers", "located", "?" ]
[ { "id": 2, "type": "column", "value": "supplierid" }, { "id": 0, "type": "table", "value": "suppliers" }, { "id": 1, "type": "column", "value": "country" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O" ]
15,109
disney
bird:train.json:4662
Who is the villain in the movie "The Great Mouse Detective"?
SELECT villian FROM characters WHERE movie_title = 'The Great Mouse Detective'
[ "Who", "is", "the", "villain", "in", "the", "movie", "\"", "The", "Great", "Mouse", "Detective", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "The Great Mouse Detective" }, { "id": 2, "type": "column", "value": "movie_title" }, { "id": 0, "type": "table", "value": "characters" }, { "id": 1, "type": "column", "value": "villian" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 3, "token_idxs": [ 9, 10, 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
15,111
cars
bird:train.json:3072
Among the cars with an acceleration of over 10 miles per squared hour, how many of them cost more than $20000 and less than $30000?
SELECT COUNT(*) FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T1.acceleration > 10 AND T2.price BETWEEN 20000 AND 30000
[ "Among", "the", "cars", "with", "an", "acceleration", "of", "over", "10", "miles", "per", "squared", "hour", ",", "how", "many", "of", "them", "cost", "more", "than", "$", "20000", "and", "less", "than", "$", "30000", "?" ]
[ { "id": 3, "type": "column", "value": "acceleration" }, { "id": 1, "type": "table", "value": "price" }, { "id": 5, "type": "column", "value": "price" }, { "id": 6, "type": "value", "value": "20000" }, { "id": 7, "type": "value", "value": "30000" }, { "id": 0, "type": "table", "value": "data" }, { "id": 2, "type": "column", "value": "id" }, { "id": 4, "type": "value", "value": "10" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O" ]
15,112
e_learning
spider:train_spider.json:3793
Find the number of students who have the word "son" in their personal names.
SELECT COUNT(*) FROM Students WHERE personal_name LIKE "%son%"
[ "Find", "the", "number", "of", "students", "who", "have", "the", "word", "\"", "son", "\"", "in", "their", "personal", "names", "." ]
[ { "id": 1, "type": "column", "value": "personal_name" }, { "id": 0, "type": "table", "value": "students" }, { "id": 2, "type": "column", "value": "%son%" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 14, 15 ] }, { "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", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,114
video_games
bird:train.json:3417
What is the name of the publisher that released the most video games in 2007?
SELECT T3.publisher_name FROM game_platform AS T1 INNER JOIN game_publisher AS T2 ON T1.game_publisher_id = T2.id INNER JOIN publisher AS T3 ON T2.publisher_id = T3.id WHERE T1.release_year = 2007 GROUP BY T3.publisher_name ORDER BY COUNT(DISTINCT T2.game_id) DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "publisher", "that", "released", "the", "most", "video", "games", "in", "2007", "?" ]
[ { "id": 9, "type": "column", "value": "game_publisher_id" }, { "id": 0, "type": "column", "value": "publisher_name" }, { "id": 5, "type": "table", "value": "game_publisher" }, { "id": 4, "type": "table", "value": "game_platform" }, { "id": 2, "type": "column", "value": "release_year" }, { "id": 6, "type": "column", "value": "publisher_id" }, { "id": 1, "type": "table", "value": "publisher" }, { "id": 8, "type": "column", "value": "game_id" }, { "id": 3, "type": "value", "value": "2007" }, { "id": 7, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
15,115
video_games
bird:train.json:3476
List down the names of the games in the racing genre.
SELECT T1.game_name FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T2.genre_name = 'Racing'
[ "List", "down", "the", "names", "of", "the", "games", "in", "the", "racing", "genre", "." ]
[ { "id": 3, "type": "column", "value": "genre_name" }, { "id": 0, "type": "column", "value": "game_name" }, { "id": 5, "type": "column", "value": "genre_id" }, { "id": 4, "type": "value", "value": "Racing" }, { "id": 2, "type": "table", "value": "genre" }, { "id": 1, "type": "table", "value": "game" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "O" ]
15,116
student_assessment
spider:train_spider.json:91
Find distinct cities of addresses of people?
SELECT DISTINCT T1.city FROM addresses AS T1 JOIN people_addresses AS T2 ON T1.address_id = T2.address_id
[ "Find", "distinct", "cities", "of", "addresses", "of", "people", "?" ]
[ { "id": 2, "type": "table", "value": "people_addresses" }, { "id": 3, "type": "column", "value": "address_id" }, { "id": 1, "type": "table", "value": "addresses" }, { "id": 0, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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" ]
15,117
soccer_2016
bird:train.json:1792
Which country is the oldest player from?
SELECT T1.Country_Name FROM Country AS T1 INNER JOIN Player AS T2 ON T2.Country_Name = T1.Country_Id WHERE T2.Country_Name IS NOT NULL ORDER BY T2.DOB LIMIT 1
[ "Which", "country", "is", "the", "oldest", "player", "from", "?" ]
[ { "id": 0, "type": "column", "value": "country_name" }, { "id": 4, "type": "column", "value": "country_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 2, "type": "table", "value": "player" }, { "id": 3, "type": "column", "value": "dob" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O" ]
15,118
election
spider:train_spider.json:2756
Show all the information about election.
SELECT * FROM election
[ "Show", "all", "the", "information", "about", "election", "." ]
[ { "id": 0, "type": "table", "value": "election" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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" ]
15,119
film_rank
spider:train_spider.json:4152
Show the studios that have not produced films with director "Walter Hill".
SELECT Studio FROM film EXCEPT SELECT Studio FROM film WHERE Director = "Walter Hill"
[ "Show", "the", "studios", "that", "have", "not", "produced", "films", "with", "director", "\"", "Walter", "Hill", "\"", "." ]
[ { "id": 3, "type": "column", "value": "Walter Hill" }, { "id": 2, "type": "column", "value": "director" }, { "id": 1, "type": "column", "value": "studio" }, { "id": 0, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 11, 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", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
15,120
public_review_platform
bird:train.json:3797
How many user ids from 1 to 20 have no fan users and have low ratings?
SELECT COUNT(user_id) FROM Users WHERE user_id BETWEEN 1 AND 20 AND user_fans LIKE 'None' AND user_review_count LIKE 'Low'
[ "How", "many", "user", "ids", "from", "1", "to", "20", "have", "no", "fan", "users", "and", "have", "low", "ratings", "?" ]
[ { "id": 6, "type": "column", "value": "user_review_count" }, { "id": 4, "type": "column", "value": "user_fans" }, { "id": 1, "type": "column", "value": "user_id" }, { "id": 0, "type": "table", "value": "users" }, { "id": 5, "type": "value", "value": "None" }, { "id": 7, "type": "value", "value": "Low" }, { "id": 3, "type": "value", "value": "20" }, { "id": 2, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "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", "I-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O" ]
15,121
video_games
bird:train.json:3368
Which company published the game with the most sales in North America?
SELECT T.publisher_name FROM ( SELECT T5.publisher_name, SUM(T2.num_sales) * 100000 FROM region AS T1 INNER JOIN region_sales AS T2 ON T1.id = T2.region_id INNER JOIN game_platform AS T3 ON T2.game_platform_id = T3.id INNER JOIN game_publisher AS T4 ON T3.game_publisher_id = T4.id INNER JOIN publisher AS T5 ON T4.publisher_id = T5.id WHERE T1.region_name = 'North America' GROUP BY T5.publisher_name ORDER BY SUM(T2.num_sales) * 100000 DESC LIMIT 1 ) t
[ "Which", "company", "published", "the", "game", "with", "the", "most", "sales", "in", "North", "America", "?" ]
[ { "id": 10, "type": "column", "value": "game_publisher_id" }, { "id": 13, "type": "column", "value": "game_platform_id" }, { "id": 0, "type": "column", "value": "publisher_name" }, { "id": 5, "type": "table", "value": "game_publisher" }, { "id": 3, "type": "value", "value": "North America" }, { "id": 9, "type": "table", "value": "game_platform" }, { "id": 6, "type": "column", "value": "publisher_id" }, { "id": 12, "type": "table", "value": "region_sales" }, { "id": 2, "type": "column", "value": "region_name" }, { "id": 1, "type": "table", "value": "publisher" }, { "id": 8, "type": "column", "value": "num_sales" }, { "id": 14, "type": "column", "value": "region_id" }, { "id": 4, "type": "value", "value": "100000" }, { "id": 11, "type": "table", "value": "region" }, { "id": 7, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "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": [ 8 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
15,122
store_1
spider:train_spider.json:597
What is employee Nancy Edwards's phone number?
SELECT phone FROM employees WHERE first_name = "Nancy" AND last_name = "Edwards";
[ "What", "is", "employee", "Nancy", "Edwards", "'s", "phone", "number", "?" ]
[ { "id": 2, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 4, "type": "column", "value": "last_name" }, { "id": 5, "type": "column", "value": "Edwards" }, { "id": 1, "type": "column", "value": "phone" }, { "id": 3, "type": "column", "value": "Nancy" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 4 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "O", "O" ]
15,123
works_cycles
bird:train.json:7196
State the last name and job title of owner for document "Crank Arm and Tire Maintenance".
SELECT T1.LastName, T3.JobTitle FROM Person AS T1 INNER JOIN Document AS T2 ON T1.BusinessEntityID = T2.Owner INNER JOIN Employee AS T3 ON T1.BusinessEntityID = T3.BusinessEntityID WHERE T2.Title = 'Crank Arm and Tire Maintenance'
[ "State", "the", "last", "name", "and", "job", "title", "of", "owner", "for", "document", "\"", "Crank", "Arm", "and", "Tire", "Maintenance", "\"", "." ]
[ { "id": 4, "type": "value", "value": "Crank Arm and Tire Maintenance" }, { "id": 7, "type": "column", "value": "businessentityid" }, { "id": 0, "type": "column", "value": "lastname" }, { "id": 1, "type": "column", "value": "jobtitle" }, { "id": 2, "type": "table", "value": "employee" }, { "id": 6, "type": "table", "value": "document" }, { "id": 5, "type": "table", "value": "person" }, { "id": 3, "type": "column", "value": "title" }, { "id": 8, "type": "column", "value": "owner" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 12, 13, 14, 15, 16 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 8 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
15,124
customers_card_transactions
spider:train_spider.json:679
Show the customer id and number of accounts with most accounts.
SELECT customer_id , count(*) FROM Accounts GROUP BY customer_id ORDER BY count(*) DESC LIMIT 1
[ "Show", "the", "customer", "i", "d", "and", "number", "of", "accounts", "with", "most", "accounts", "." ]
[ { "id": 1, "type": "column", "value": "customer_id" }, { "id": 0, "type": "table", "value": "accounts" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,125
food_inspection
bird:train.json:8795
Which business had the lowest score for the unscheduled routine inspection on 2016/9/26? Give the name of the business.
SELECT T2.name FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE score = ( SELECT MIN(score) FROM inspections WHERE `date` = '2016-09-26' AND type = 'Routine - Unscheduled' ) AND T1.`date` = '2016-09-26' AND T1.type = 'Routine - Unscheduled'
[ "Which", "business", "had", "the", "lowest", "score", "for", "the", "unscheduled", "routine", "inspection", "on", "2016/9/26", "?", "Give", "the", "name", "of", "the", "business", "." ]
[ { "id": 8, "type": "value", "value": "Routine - Unscheduled" }, { "id": 1, "type": "table", "value": "inspections" }, { "id": 3, "type": "column", "value": "business_id" }, { "id": 2, "type": "table", "value": "businesses" }, { "id": 6, "type": "value", "value": "2016-09-26" }, { "id": 4, "type": "column", "value": "score" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "date" }, { "id": 7, "type": "column", "value": "type" } ]
[ { "entity_id": 0, "token_idxs": [ 16 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 19 ] }, { "entity_id": 3, "token_idxs": [ 1 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 12 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 7, 8 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
15,127
books
bird:train.json:5959
What is the name of the publisher with publisher ID 22?
SELECT publisher_name FROM publisher WHERE publisher_id = 22
[ "What", "is", "the", "name", "of", "the", "publisher", "with", "publisher", "ID", "22", "?" ]
[ { "id": 1, "type": "column", "value": "publisher_name" }, { "id": 2, "type": "column", "value": "publisher_id" }, { "id": 0, "type": "table", "value": "publisher" }, { "id": 3, "type": "value", "value": "22" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O" ]
15,128
party_host
spider:train_spider.json:2673
How many hosts does each nationality have? List the nationality and the count.
SELECT Nationality , COUNT(*) FROM HOST GROUP BY Nationality
[ "How", "many", "hosts", "does", "each", "nationality", "have", "?", "List", "the", "nationality", "and", "the", "count", "." ]
[ { "id": 1, "type": "column", "value": "nationality" }, { "id": 0, "type": "table", "value": "host" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,129
tracking_grants_for_research
spider:train_spider.json:4381
What is the description for the results whose project detail is 'sint'?
SELECT T1.outcome_description FROM Research_outcomes AS T1 JOIN Project_outcomes AS T2 ON T1.outcome_code = T2.outcome_code JOIN Projects AS T3 ON T2.project_id = T3.project_id WHERE T3.project_details = 'sint'
[ "What", "is", "the", "description", "for", "the", "results", "whose", "project", "detail", "is", "'", "sint", "'", "?" ]
[ { "id": 0, "type": "column", "value": "outcome_description" }, { "id": 4, "type": "table", "value": "research_outcomes" }, { "id": 5, "type": "table", "value": "project_outcomes" }, { "id": 2, "type": "column", "value": "project_details" }, { "id": 7, "type": "column", "value": "outcome_code" }, { "id": 6, "type": "column", "value": "project_id" }, { "id": 1, "type": "table", "value": "projects" }, { "id": 3, "type": "value", "value": "sint" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "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", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O", "O" ]
15,130
student_loan
bird:train.json:4451
Which female students had never been absent?
SELECT T2.name FROM male AS T1 INNER JOIN longest_absense_from_school AS T2 ON T1.name <> T2.name WHERE T2.month = 0
[ "Which", "female", "students", "had", "never", "been", "absent", "?" ]
[ { "id": 2, "type": "table", "value": "longest_absense_from_school" }, { "id": 3, "type": "column", "value": "month" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "table", "value": "male" }, { "id": 4, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
15,131
works_cycles
bird:train.json:7147
What is contact Type ID No.16 represent for?
SELECT Name FROM ContactType WHERE ContactTypeID = '16'
[ "What", "is", "contact", "Type", "ID", "No.16", "represent", "for", "?" ]
[ { "id": 2, "type": "column", "value": "contacttypeid" }, { "id": 0, "type": "table", "value": "contacttype" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "16" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "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", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O" ]
15,132
social_media
bird:train.json:827
Tweet with ID tw-682723090279841798 was posted from which country?
SELECT T2.Country FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID WHERE T1.TweetID = 'tw-682723090279841798'
[ "Tweet", "with", "ID", "tw-682723090279841798", "was", "posted", "from", "which", "country", "?" ]
[ { "id": 4, "type": "value", "value": "tw-682723090279841798" }, { "id": 5, "type": "column", "value": "locationid" }, { "id": 2, "type": "table", "value": "location" }, { "id": 0, "type": "column", "value": "country" }, { "id": 1, "type": "table", "value": "twitter" }, { "id": 3, "type": "column", "value": "tweetid" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 0 ] }, { "entity_id": 4, "token_idxs": [ 3 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,134
cre_Docs_and_Epenses
spider:train_spider.json:6406
What are the names and ids of documents that have the type code BK?
SELECT document_name , document_id FROM Documents WHERE document_type_code = "BK"
[ "What", "are", "the", "names", "and", "ids", "of", "documents", "that", "have", "the", "type", "code", "BK", "?" ]
[ { "id": 3, "type": "column", "value": "document_type_code" }, { "id": 1, "type": "column", "value": "document_name" }, { "id": 2, "type": "column", "value": "document_id" }, { "id": 0, "type": "table", "value": "documents" }, { "id": 4, "type": "column", "value": "BK" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,135
allergy_1
spider:train_spider.json:511
How many students have a food allergy?
SELECT count(*) FROM Has_allergy AS T1 JOIN Allergy_type AS T2 ON T1.allergy = T2.allergy WHERE T2.allergytype = "food"
[ "How", "many", "students", "have", "a", "food", "allergy", "?" ]
[ { "id": 1, "type": "table", "value": "allergy_type" }, { "id": 0, "type": "table", "value": "has_allergy" }, { "id": 2, "type": "column", "value": "allergytype" }, { "id": 4, "type": "column", "value": "allergy" }, { "id": 3, "type": "column", "value": "food" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
15,136
hockey
bird:train.json:7783
What is the percentage of American coaches among all the coaches who taught the Montreal Canadiens?
SELECT SUM(CAST(T2.W AS REAL) / T2.G) / SUM(T2.G + T2.W) FROM Teams AS T1 INNER JOIN TeamsSC AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.name = 'Montreal Canadiens'
[ "What", "is", "the", "percentage", "of", "American", "coaches", "among", "all", "the", "coaches", "who", "taught", "the", "Montreal", "Canadiens", "?" ]
[ { "id": 3, "type": "value", "value": "Montreal Canadiens" }, { "id": 1, "type": "table", "value": "teamssc" }, { "id": 0, "type": "table", "value": "teams" }, { "id": 2, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "tmid" }, { "id": 5, "type": "column", "value": "year" }, { "id": 6, "type": "column", "value": "g" }, { "id": 7, "type": "column", "value": "w" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 14, 15 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
15,137
formula_1
bird:dev.json:952
Which constructors have been ranked 1?
SELECT DISTINCT T2.name FROM results AS T1 INNER JOIN constructors AS T2 on T1.constructorId = T2.constructorId WHERE T1.rank = 1
[ "Which", "constructors", "have", "been", "ranked", "1", "?" ]
[ { "id": 5, "type": "column", "value": "constructorid" }, { "id": 2, "type": "table", "value": "constructors" }, { "id": 1, "type": "table", "value": "results" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "rank" }, { "id": 4, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 1 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
15,138
warehouse_1
bird:test.json:1739
Find the total capacity of all warehouse locations.
SELECT sum(capacity) FROM warehouses
[ "Find", "the", "total", "capacity", "of", "all", "warehouse", "locations", "." ]
[ { "id": 0, "type": "table", "value": "warehouses" }, { "id": 1, "type": "column", "value": "capacity" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "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", "B-TABLE", "O", "O" ]
15,139
superstore
bird:train.json:2443
How many orders were made by customers who live in Texas at the Central superstore?
SELECT COUNT(DISTINCT T2.`Order ID`) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T1.State = 'Texas'
[ "How", "many", "orders", "were", "made", "by", "customers", "who", "live", "in", "Texas", "at", "the", "Central", "superstore", "?" ]
[ { "id": 1, "type": "table", "value": "central_superstore" }, { "id": 5, "type": "column", "value": "Customer ID" }, { "id": 4, "type": "column", "value": "Order ID" }, { "id": 0, "type": "table", "value": "people" }, { "id": 2, "type": "column", "value": "state" }, { "id": 3, "type": "value", "value": "Texas" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 13, 14 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "B-TABLE", "I-TABLE", "O" ]
15,140
european_football_2
bird:dev.json:1113
For the team "Hannover 96", what was its defence aggression class on 2015/9/10?
SELECT t2.chanceCreationShootingClass FROM Team AS t1 INNER JOIN Team_Attributes AS t2 ON t1.team_api_id = t2.team_api_id WHERE t1.team_long_name = 'Hannover 96' AND t2.`date` LIKE '2015-09-10%'
[ "For", "the", "team", "\"", "Hannover", "96", "\"", ",", "what", "was", "its", "defence", "aggression", "class", "on", "2015/9/10", "?" ]
[ { "id": 0, "type": "column", "value": "chancecreationshootingclass" }, { "id": 2, "type": "table", "value": "team_attributes" }, { "id": 4, "type": "column", "value": "team_long_name" }, { "id": 3, "type": "column", "value": "team_api_id" }, { "id": 5, "type": "value", "value": "Hannover 96" }, { "id": 7, "type": "value", "value": "2015-09-10%" }, { "id": 1, "type": "table", "value": "team" }, { "id": 6, "type": "column", "value": "date" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 4, 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 15 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
15,141
dorm_1
spider:train_spider.json:5767
What are the amenities in the dorm that a student who has the last name of Smith lives in?
SELECT T3.amenity_name FROM dorm AS T1 JOIN has_amenity AS T2 ON T1.dormid = T2.dormid JOIN dorm_amenity AS T3 ON T2.amenid = T3.amenid JOIN lives_in AS T4 ON T4.dormid = T1.dormid JOIN student AS T5 ON T5.stuid = T4.stuid WHERE T5.lname = 'Smith'
[ "What", "are", "the", "amenities", "in", "the", "dorm", "that", "a", "student", "who", "has", "the", "last", "name", "of", "Smith", "lives", "in", "?" ]
[ { "id": 0, "type": "column", "value": "amenity_name" }, { "id": 6, "type": "table", "value": "dorm_amenity" }, { "id": 9, "type": "table", "value": "has_amenity" }, { "id": 4, "type": "table", "value": "lives_in" }, { "id": 1, "type": "table", "value": "student" }, { "id": 7, "type": "column", "value": "dormid" }, { "id": 10, "type": "column", "value": "amenid" }, { "id": 2, "type": "column", "value": "lname" }, { "id": 3, "type": "value", "value": "Smith" }, { "id": 5, "type": "column", "value": "stuid" }, { "id": 8, "type": "table", "value": "dorm" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "I-TABLE", "O" ]
15,142
social_media
bird:train.json:814
What is the day of the week that tweet with ID tw-682712873332805633 was posted?
SELECT Weekday FROM twitter WHERE TweetID = 'tw-682712873332805633'
[ "What", "is", "the", "day", "of", "the", "week", "that", "tweet", "with", "ID", "tw-682712873332805633", "was", "posted", "?" ]
[ { "id": 3, "type": "value", "value": "tw-682712873332805633" }, { "id": 0, "type": "table", "value": "twitter" }, { "id": 1, "type": "column", "value": "weekday" }, { "id": 2, "type": "column", "value": "tweetid" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O" ]
15,143
gas_company
spider:train_spider.json:2037
find the location and Representative name of the gas stations owned by the companies with top 3 Asset amounts.
SELECT T3.location , T3.Representative_Name FROM station_company AS T1 JOIN company AS T2 ON T1.company_id = T2.company_id JOIN gas_station AS T3 ON T1.station_id = T3.station_id ORDER BY T2.Assets_billion DESC LIMIT 3
[ "find", "the", "location", "and", "Representative", "name", "of", "the", "gas", "stations", "owned", "by", "the", "companies", "with", "top", "3", "Asset", "amounts", "." ]
[ { "id": 1, "type": "column", "value": "representative_name" }, { "id": 4, "type": "table", "value": "station_company" }, { "id": 3, "type": "column", "value": "assets_billion" }, { "id": 2, "type": "table", "value": "gas_station" }, { "id": 6, "type": "column", "value": "station_id" }, { "id": 7, "type": "column", "value": "company_id" }, { "id": 0, "type": "column", "value": "location" }, { "id": 5, "type": "table", "value": "company" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10, 11 ] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "B-TABLE", "I-TABLE", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
15,144
flight_1
spider:train_spider.json:435
what is the salary and name of the employee who has the most number of aircraft certificates?
SELECT T1.name , T1.salary FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid GROUP BY T1.eid ORDER BY count(*) DESC LIMIT 1
[ "what", "is", "the", "salary", "and", "name", "of", "the", "employee", "who", "has", "the", "most", "number", "of", "aircraft", "certificates", "?" ]
[ { "id": 4, "type": "table", "value": "certificate" }, { "id": 3, "type": "table", "value": "employee" }, { "id": 2, "type": "column", "value": "salary" }, { "id": 1, "type": "column", "value": "name" }, { "id": 0, "type": "column", "value": "eid" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,145
art_1
bird:test.json:1237
Give the full names of artists who have created paintings and sculptures.
SELECT T1.lname , T1.fname FROM artists AS T1 JOIN sculptures AS T2 ON T1.artistID = T2.sculptorID INTERSECT SELECT T3.lname , T3.fname FROM artists AS T3 JOIN paintings AS T4 ON T3.artistID = T4.painterID
[ "Give", "the", "full", "names", "of", "artists", "who", "have", "created", "paintings", "and", "sculptures", "." ]
[ { "id": 3, "type": "table", "value": "sculptures" }, { "id": 6, "type": "column", "value": "sculptorid" }, { "id": 4, "type": "table", "value": "paintings" }, { "id": 7, "type": "column", "value": "painterid" }, { "id": 5, "type": "column", "value": "artistid" }, { "id": 2, "type": "table", "value": "artists" }, { "id": 0, "type": "column", "value": "lname" }, { "id": 1, "type": "column", "value": "fname" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 11 ] }, { "entity_id": 7, "token_idxs": [ 9 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
15,147
college_1
spider:train_spider.json:3191
How many different locations does each school have?
SELECT count(DISTINCT dept_address) , school_code FROM department GROUP BY school_code
[ "How", "many", "different", "locations", "does", "each", "school", "have", "?" ]
[ { "id": 2, "type": "column", "value": "dept_address" }, { "id": 1, "type": "column", "value": "school_code" }, { "id": 0, "type": "table", "value": "department" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,148
college_2
spider:train_spider.json:1336
How many students have advisors?
SELECT count(DISTINCT s_id) FROM advisor
[ "How", "many", "students", "have", "advisors", "?" ]
[ { "id": 0, "type": "table", "value": "advisor" }, { "id": 1, "type": "column", "value": "s_id" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O" ]
15,149
language_corpus
bird:train.json:5779
How many times did the word "grec" occur on the page titled "Àbac"?
SELECT T2.occurrences FROM words AS T1 INNER JOIN pages_words AS T2 ON T1.wid = T2.wid INNER JOIN pages AS T3 ON T2.pid = T3.pid WHERE T3.title = 'Àbac' AND T1.word = 'grec'
[ "How", "many", "times", "did", "the", "word", "\"", "grec", "\"", "occur", "on", "the", "page", "titled", "\"", "Àbac", "\"", "?" ]
[ { "id": 0, "type": "column", "value": "occurrences" }, { "id": 3, "type": "table", "value": "pages_words" }, { "id": 1, "type": "table", "value": "pages" }, { "id": 2, "type": "table", "value": "words" }, { "id": 5, "type": "column", "value": "title" }, { "id": 6, "type": "value", "value": "Àbac" }, { "id": 7, "type": "column", "value": "word" }, { "id": 8, "type": "value", "value": "grec" }, { "id": 4, "type": "column", "value": "pid" }, { "id": 9, "type": "column", "value": "wid" } ]
[ { "entity_id": 0, "token_idxs": [ 9, 10 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 15 ] }, { "entity_id": 7, "token_idxs": [ 5 ] }, { "entity_id": 8, "token_idxs": [ 7 ] }, { "entity_id": 9, "token_idxs": [ 3 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
15,150
world_development_indicators
bird:train.json:2116
What is the short name of the country in which the "Net bilateral aid flows from DAC donors, Sweden (current US$)" indicator hit the 570,000 value in 1970?
SELECT T2.ShortName FROM Indicators AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.IndicatorName = 'Net bilateral aid flows FROM DAC donors, Sweden (current US$)' AND T1.Year = 1970 AND T1.Value = 570000
[ "What", "is", "the", "short", "name", "of", "the", "country", "in", "which", "the", "\"", "Net", "bilateral", "aid", "flows", "from", "DAC", "donors", ",", "Sweden", "(", "current", "US$", ")", "\"", "indicator", "hit", "the", "570,000", "value", "in", "1970", "?" ]
[ { "id": 5, "type": "value", "value": "Net bilateral aid flows FROM DAC donors, Sweden (current US$)" }, { "id": 4, "type": "column", "value": "indicatorname" }, { "id": 3, "type": "column", "value": "countrycode" }, { "id": 1, "type": "table", "value": "indicators" }, { "id": 0, "type": "column", "value": "shortname" }, { "id": 2, "type": "table", "value": "country" }, { "id": 9, "type": "value", "value": "570000" }, { "id": 8, "type": "column", "value": "value" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "1970" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 26 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 32 ] }, { "entity_id": 8, "token_idxs": [ 30 ] }, { "entity_id": 9, "token_idxs": [ 29 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]
15,151
social_media
bird:train.json:793
Please list the texts of all the tweets posted by male users from Buenos Aires.
SELECT T1.text FROM twitter AS T1 INNER JOIN location AS T2 ON T2.LocationID = T1.LocationID INNER JOIN user AS T2 ON T2.UserID = T1.UserID INNER JOIN user AS T3 ON T1.UserID = T3.UserID WHERE T2.City = 'Buenos Aires' AND T3.Gender = 'Male'
[ "Please", "list", "the", "texts", "of", "all", "the", "tweets", "posted", "by", "male", "users", "from", "Buenos", "Aires", "." ]
[ { "id": 3, "type": "value", "value": "Buenos Aires" }, { "id": 8, "type": "column", "value": "locationid" }, { "id": 7, "type": "table", "value": "location" }, { "id": 6, "type": "table", "value": "twitter" }, { "id": 1, "type": "column", "value": "userid" }, { "id": 4, "type": "column", "value": "gender" }, { "id": 0, "type": "column", "value": "text" }, { "id": 2, "type": "column", "value": "city" }, { "id": 5, "type": "value", "value": "Male" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 13, 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 10 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
15,152
superhero
bird:dev.json:719
Among the superheroes with the super power of "Super Strength", how many of them have a height of over 200cm?
SELECT COUNT(T1.id) FROM superhero AS T1 INNER JOIN hero_power AS T2 ON T1.id = T2.hero_id INNER JOIN superpower AS T3 ON T2.power_id = T3.id WHERE T3.power_name = 'Super Strength' AND T1.height_cm > 200
[ "Among", "the", "superheroes", "with", "the", "super", "power", "of", "\"", "Super", "Strength", "\"", ",", "how", "many", "of", "them", "have", "a", "height", "of", "over", "200", "cm", "?" ]
[ { "id": 6, "type": "value", "value": "Super Strength" }, { "id": 0, "type": "table", "value": "superpower" }, { "id": 3, "type": "table", "value": "hero_power" }, { "id": 5, "type": "column", "value": "power_name" }, { "id": 2, "type": "table", "value": "superhero" }, { "id": 7, "type": "column", "value": "height_cm" }, { "id": 4, "type": "column", "value": "power_id" }, { "id": 9, "type": "column", "value": "hero_id" }, { "id": 8, "type": "value", "value": "200" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 9, 10 ] }, { "entity_id": 7, "token_idxs": [ 19 ] }, { "entity_id": 8, "token_idxs": [ 22 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O" ]
15,153
retails
bird:train.json:6898
How many customers are in the furniture segment?
SELECT COUNT(c_custkey) FROM customer WHERE c_mktsegment = 'FURNITURE'
[ "How", "many", "customers", "are", "in", "the", "furniture", "segment", "?" ]
[ { "id": 1, "type": "column", "value": "c_mktsegment" }, { "id": 2, "type": "value", "value": "FURNITURE" }, { "id": 3, "type": "column", "value": "c_custkey" }, { "id": 0, "type": "table", "value": "customer" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,154
regional_sales
bird:train.json:2674
Indicate the procured dates for the customer whose ID is 11.
SELECT DISTINCT T FROM ( SELECT IIF(_CustomerID = 11, ProcuredDate, NULL) AS T FROM `Sales Orders` ) WHERE T IS NOT NULL
[ "Indicate", "the", "procured", "dates", "for", "the", "customer", "whose", "ID", "is", "11", "." ]
[ { "id": 1, "type": "table", "value": "Sales Orders" }, { "id": 2, "type": "column", "value": "procureddate" }, { "id": 3, "type": "column", "value": "_customerid" }, { "id": 4, "type": "value", "value": "11" }, { "id": 0, "type": "column", "value": "t" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2, 3 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
15,155
products_gen_characteristics
spider:train_spider.json:5516
How many products are there?
SELECT count(*) FROM products
[ "How", "many", "products", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "products" } ]
[ { "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" ]
15,156
aircraft
spider:train_spider.json:4808
What is the maximum and mininum number of transit passengers for all airports?
SELECT max(Transit_Passengers) , min(Transit_Passengers) FROM airport
[ "What", "is", "the", "maximum", "and", "mininum", "number", "of", "transit", "passengers", "for", "all", "airports", "?" ]
[ { "id": 1, "type": "column", "value": "transit_passengers" }, { "id": 0, "type": "table", "value": "airport" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 8, 9 ] }, { "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", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O" ]
15,157
college_completion
bird:train.json:3756
Between 2011 to 2013, what is the average number of male Hispanic degree-seeking students at 2-year institutions who graduated within 150 percent of normal/expected time in United Education Institute-Huntington Park Campus?
SELECT AVG(T2.grad_150) FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T1.chronname = 'United Education Institute-Huntington Park Campus' AND T2.year BETWEEN 2011 AND 2013 AND T2.gender = 'M' AND T2.race = 'H'
[ "Between", "2011", "to", "2013", ",", "what", "is", "the", "average", "number", "of", "male", "Hispanic", "degree", "-", "seeking", "students", "at", "2", "-", "year", "institutions", "who", "graduated", "within", "150", "percent", "of", "normal", "/", "expected", "time", "in", "United", "Education", "Institute", "-", "Huntington", "Park", "Campus", "?" ]
[ { "id": 5, "type": "value", "value": "United Education Institute-Huntington Park Campus" }, { "id": 0, "type": "table", "value": "institution_details" }, { "id": 1, "type": "table", "value": "institution_grads" }, { "id": 4, "type": "column", "value": "chronname" }, { "id": 2, "type": "column", "value": "grad_150" }, { "id": 3, "type": "column", "value": "unitid" }, { "id": 9, "type": "column", "value": "gender" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "2011" }, { "id": 8, "type": "value", "value": "2013" }, { "id": 11, "type": "column", "value": "race" }, { "id": 10, "type": "value", "value": "M" }, { "id": 12, "type": "value", "value": "H" } ]
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[ "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
15,158
professional_basketball
bird:train.json:2891
Name the teams along with the coaches that went to 'Quarter Final' round in 1946.
SELECT DISTINCT T1.coachID, T3.name FROM coaches AS T1 JOIN series_post AS T2 ON T1.tmID = T2.tmIDWinner JOIN teams AS T3 ON T3.tmID = T1.tmID WHERE T2.round = 'QF' AND T2.year = 1946
[ "Name", "the", "teams", "along", "with", "the", "coaches", "that", "went", "to", "'", "Quarter", "Final", "'", "round", "in", "1946", "." ]
[ { "id": 4, "type": "table", "value": "series_post" }, { "id": 10, "type": "column", "value": "tmidwinner" }, { "id": 0, "type": "column", "value": "coachid" }, { "id": 3, "type": "table", "value": "coaches" }, { "id": 2, "type": "table", "value": "teams" }, { "id": 6, "type": "column", "value": "round" }, { "id": 1, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "tmid" }, { "id": 8, "type": "column", "value": "year" }, { "id": 9, "type": "value", "value": "1946" }, { "id": 7, "type": "value", "value": "QF" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 0 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 14 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 16 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
15,159
address_1
bird:test.json:793
Show the number of students living in each country.
SELECT T1.country , count(*) FROM City AS T1 JOIN Student AS T2 ON T1.city_code = T2.city_code GROUP BY T1.country
[ "Show", "the", "number", "of", "students", "living", "in", "each", "country", "." ]
[ { "id": 3, "type": "column", "value": "city_code" }, { "id": 0, "type": "column", "value": "country" }, { "id": 2, "type": "table", "value": "student" }, { "id": 1, "type": "table", "value": "city" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
15,160
hr_1
spider:train_spider.json:3420
What are the full name, hire data, salary and department id for employees without the letter M in their first name, ordered by ascending department id?
SELECT first_name , last_name , hire_date , salary , department_id FROM employees WHERE first_name NOT LIKE '%M%' ORDER BY department_id
[ "What", "are", "the", "full", "name", ",", "hire", "data", ",", "salary", "and", "department", "i", "d", "for", "employees", "without", "the", "letter", "M", "in", "their", "first", "name", ",", "ordered", "by", "ascending", "department", "i", "d", "?" ]
[ { "id": 5, "type": "column", "value": "department_id" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 3, "type": "column", "value": "hire_date" }, { "id": 4, "type": "column", "value": "salary" }, { "id": 6, "type": "value", "value": "%M%" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
15,162
world
bird:train.json:7863
List all the languages used in Europe.
SELECT T2.Language FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = 'Europe'
[ "List", "all", "the", "languages", "used", "in", "Europe", "." ]
[ { "id": 2, "type": "table", "value": "countrylanguage" }, { "id": 6, "type": "column", "value": "countrycode" }, { "id": 3, "type": "column", "value": "continent" }, { "id": 0, "type": "column", "value": "language" }, { "id": 1, "type": "table", "value": "country" }, { "id": 4, "type": "value", "value": "Europe" }, { "id": 5, "type": "column", "value": "code" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
15,163
retail_world
bird:train.json:6359
How many suppliers are there in the United States of America?
SELECT COUNT(SupplierID) FROM Suppliers WHERE Country = 'USA'
[ "How", "many", "suppliers", "are", "there", "in", "the", "United", "States", "of", "America", "?" ]
[ { "id": 3, "type": "column", "value": "supplierid" }, { "id": 0, "type": "table", "value": "suppliers" }, { "id": 1, "type": "column", "value": "country" }, { "id": 2, "type": "value", "value": "USA" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,165
movie_1
spider:train_spider.json:2467
What is highest rating for the most recent movie and when was it released?
SELECT max(T1.stars) , T2.year FROM Rating AS T1 JOIN Movie AS T2 ON T1.mID = T2.mID WHERE T2.year = (SELECT max(YEAR) FROM Movie)
[ "What", "is", "highest", "rating", "for", "the", "most", "recent", "movie", "and", "when", "was", "it", "released", "?" ]
[ { "id": 1, "type": "table", "value": "rating" }, { "id": 2, "type": "table", "value": "movie" }, { "id": 3, "type": "column", "value": "stars" }, { "id": 0, "type": "column", "value": "year" }, { "id": 4, "type": "column", "value": "mid" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
15,166
bike_1
spider:train_spider.json:142
What are the ids of the stations in San Francisco that normally have more than 10 bikes available?
SELECT id FROM station WHERE city = "San Francisco" INTERSECT SELECT station_id FROM status GROUP BY station_id HAVING avg(bikes_available) > 10
[ "What", "are", "the", "ids", "of", "the", "stations", "in", "San", "Francisco", "that", "normally", "have", "more", "than", "10", "bikes", "available", "?" ]
[ { "id": 7, "type": "column", "value": "bikes_available" }, { "id": 5, "type": "column", "value": "San Francisco" }, { "id": 2, "type": "column", "value": "station_id" }, { "id": 0, "type": "table", "value": "station" }, { "id": 1, "type": "table", "value": "status" }, { "id": 4, "type": "column", "value": "city" }, { "id": 3, "type": "column", "value": "id" }, { "id": 6, "type": "value", "value": "10" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O" ]
15,168
sakila_1
spider:train_spider.json:2984
Which movies have 'Deleted Scenes' as a substring in the special feature?
SELECT title FROM film WHERE special_features LIKE '%Deleted Scenes%'
[ "Which", "movies", "have", "'", "Deleted", "Scenes", "'", "as", "a", "substring", "in", "the", "special", "feature", "?" ]
[ { "id": 2, "type": "column", "value": "special_features" }, { "id": 3, "type": "value", "value": "%Deleted Scenes%" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 12, 13 ] }, { "entity_id": 3, "token_idxs": [ 4, 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", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,169
mental_health_survey
bird:train.json:4612
How many times more for the number of users who took the "mental health survey for 2017" than "mental health survey for 2018"?
SELECT CAST(COUNT(T1.UserID) AS REAL) / ( SELECT COUNT(T1.UserID) FROM Answer AS T1 INNER JOIN Survey AS T2 ON T1.SurveyID = T2.SurveyID WHERE T2.Description = 'mental health survey for 2018' ) FROM Answer AS T1 INNER JOIN Survey AS T2 ON T1.SurveyID = T2.SurveyID WHERE T2.Description = 'mental health survey for 2017'
[ "How", "many", "times", "more", "for", "the", "number", "of", "users", "who", "took", "the", "\"", "mental", "health", "survey", "for", "2017", "\"", "than", "\"", "mental", "health", "survey", "for", "2018", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "mental health survey for 2017" }, { "id": 6, "type": "value", "value": "mental health survey for 2018" }, { "id": 2, "type": "column", "value": "description" }, { "id": 4, "type": "column", "value": "surveyid" }, { "id": 0, "type": "table", "value": "answer" }, { "id": 1, "type": "table", "value": "survey" }, { "id": 5, "type": "column", "value": "userid" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "B-VALUE", "I-VALUE", "B-TABLE", "B-VALUE", "I-VALUE", "O", "O" ]
15,170
conference
bird:test.json:1067
Show the institution name, location and founded year of all institutions.
SELECT institution_name , LOCATION , founded FROM institution
[ "Show", "the", "institution", "name", ",", "location", "and", "founded", "year", "of", "all", "institutions", "." ]
[ { "id": 1, "type": "column", "value": "institution_name" }, { "id": 0, "type": "table", "value": "institution" }, { "id": 2, "type": "column", "value": "location" }, { "id": 3, "type": "column", "value": "founded" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "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", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
15,171
world_development_indicators
bird:train.json:2243
What's the agregation method for the indicator whose value is 133 in 1960 for the Arab World?
SELECT T2.AggregationMethod FROM Indicators AS T1 INNER JOIN Series AS T2 ON T1.IndicatorName = T2.IndicatorName INNER JOIN Country AS T3 ON T1.CountryCode = T3.CountryCode WHERE T3.ShortName = 'Arab World' AND T1.Value = 133 AND T1.Year = 1960
[ "What", "'s", "the", "agregation", "method", "for", "the", "indicator", "whose", "value", "is", "133", "in", "1960", "for", "the", "Arab", "World", "?" ]
[ { "id": 0, "type": "column", "value": "aggregationmethod" }, { "id": 11, "type": "column", "value": "indicatorname" }, { "id": 4, "type": "column", "value": "countrycode" }, { "id": 2, "type": "table", "value": "indicators" }, { "id": 6, "type": "value", "value": "Arab World" }, { "id": 5, "type": "column", "value": "shortname" }, { "id": 1, "type": "table", "value": "country" }, { "id": 3, "type": "table", "value": "series" }, { "id": 7, "type": "column", "value": "value" }, { "id": 9, "type": "column", "value": "year" }, { "id": 10, "type": "value", "value": "1960" }, { "id": 8, "type": "value", "value": "133" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "B-VALUE", "I-VALUE", "O" ]
15,172
sales
bird:train.json:5373
List down all of the product names that were placed by sales person with id 10.
SELECT DISTINCT T1.Name FROM Products AS T1 INNER JOIN Sales AS T2 ON T1.ProductID = T2.ProductID WHERE T2.SalesPersonID = 10
[ "List", "down", "all", "of", "the", "product", "names", "that", "were", "placed", "by", "sales", "person", "with", "i", "d", "10", "." ]
[ { "id": 3, "type": "column", "value": "salespersonid" }, { "id": 5, "type": "column", "value": "productid" }, { "id": 1, "type": "table", "value": "products" }, { "id": 2, "type": "table", "value": "sales" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "10" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
15,173
movielens
bird:train.json:2336
What non-English American film/s has received the lowest user ratings? Mention the movie's I.D.
SELECT T2.movieid FROM movies AS T1 INNER JOIN u2base AS T2 ON T1.movieid = T2.movieid WHERE T1.isEnglish = 'F' AND T1.country = 'USA' ORDER BY T2.rating LIMIT 1
[ "What", "non", "-", "English", "American", "film", "/", "s", "has", "received", "the", "lowest", "user", "ratings", "?", "Mention", "the", "movie", "'s", "I.D." ]
[ { "id": 4, "type": "column", "value": "isenglish" }, { "id": 0, "type": "column", "value": "movieid" }, { "id": 6, "type": "column", "value": "country" }, { "id": 1, "type": "table", "value": "movies" }, { "id": 2, "type": "table", "value": "u2base" }, { "id": 3, "type": "column", "value": "rating" }, { "id": 7, "type": "value", "value": "USA" }, { "id": 5, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
15,174
flight_company
spider:train_spider.json:6372
What are the names of the airports which are not in the country 'Iceland'?
SELECT name FROM airport WHERE country != 'Iceland'
[ "What", "are", "the", "names", "of", "the", "airports", "which", "are", "not", "in", "the", "country", "'", "Iceland", "'", "?" ]
[ { "id": 0, "type": "table", "value": "airport" }, { "id": 2, "type": "column", "value": "country" }, { "id": 3, "type": "value", "value": "Iceland" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
15,175
twitter_1
spider:train_spider.json:298
Find the average number of followers for the users who do not have any tweet.
SELECT avg(followers) FROM user_profiles WHERE UID NOT IN (SELECT UID FROM tweets)
[ "Find", "the", "average", "number", "of", "followers", "for", "the", "users", "who", "do", "not", "have", "any", "tweet", "." ]
[ { "id": 0, "type": "table", "value": "user_profiles" }, { "id": 1, "type": "column", "value": "followers" }, { "id": 3, "type": "table", "value": "tweets" }, { "id": 2, "type": "column", "value": "uid" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,176
talkingdata
bird:train.json:1120
Give the number of device models for "中兴" phone brand.
SELECT COUNT(device_id) FROM phone_brand_device_model2 WHERE device_model = '中兴'
[ "Give", "the", "number", "of", "device", "models", "for", "\"", "中兴", "\"", "phone", "brand", "." ]
[ { "id": 0, "type": "table", "value": "phone_brand_device_model2" }, { "id": 1, "type": "column", "value": "device_model" }, { "id": 3, "type": "column", "value": "device_id" }, { "id": 2, "type": "value", "value": "中兴" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
15,178
restaurant_bills
bird:test.json:626
Show different nationalities of customers, along with the number of customers of each nationality.
SELECT Nationality , COUNT(*) FROM customer GROUP BY Nationality
[ "Show", "different", "nationalities", "of", "customers", ",", "along", "with", "the", "number", "of", "customers", "of", "each", "nationality", "." ]
[ { "id": 1, "type": "column", "value": "nationality" }, { "id": 0, "type": "table", "value": "customer" } ]
[ { "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" ]
15,179
movies_4
bird:train.json:419
When was the release date of the latest movie in which Dariusz Wolski worked as a crew member?
SELECT T1.release_date FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Dariusz Wolski' ORDER BY T1.release_date DESC LIMIT 1
[ "When", "was", "the", "release", "date", "of", "the", "latest", "movie", "in", "which", "Dariusz", "Wolski", "worked", "as", "a", "crew", "member", "?" ]
[ { "id": 3, "type": "value", "value": "Dariusz Wolski" }, { "id": 0, "type": "column", "value": "release_date" }, { "id": 2, "type": "column", "value": "person_name" }, { "id": 5, "type": "table", "value": "movie_crew" }, { "id": 6, "type": "column", "value": "person_id" }, { "id": 7, "type": "column", "value": "movie_id" }, { "id": 1, "type": "table", "value": "person" }, { "id": 4, "type": "table", "value": "movie" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 11, 12 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O" ]
15,181
california_schools
bird:dev.json:18
How many schools in Fresno (directly funded) have number of test takers not more than 250?
SELECT COUNT(T1.CDSCode) FROM frpm AS T1 INNER JOIN satscores AS T2 ON T1.CDSCode = T2.cds WHERE T1.`Charter Funding Type` = 'Directly funded' AND T1.`County Name` = 'Fresno' AND T2.NumTstTakr <= 250
[ "How", "many", "schools", "in", "Fresno", "(", "directly", "funded", ")", "have", "number", "of", "test", "takers", "not", "more", "than", "250", "?" ]
[ { "id": 4, "type": "column", "value": "Charter Funding Type" }, { "id": 5, "type": "value", "value": "Directly funded" }, { "id": 6, "type": "column", "value": "County Name" }, { "id": 8, "type": "column", "value": "numtsttakr" }, { "id": 1, "type": "table", "value": "satscores" }, { "id": 2, "type": "column", "value": "cdscode" }, { "id": 7, "type": "value", "value": "Fresno" }, { "id": 0, "type": "table", "value": "frpm" }, { "id": 3, "type": "column", "value": "cds" }, { "id": 9, "type": "value", "value": "250" } ]
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[ "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
15,182
sales
bird:train.json:5408
How many sales people are handling all the customers?
SELECT COUNT(EmployeeID) FROM Employees
[ "How", "many", "sales", "people", "are", "handling", "all", "the", "customers", "?" ]
[ { "id": 1, "type": "column", "value": "employeeid" }, { "id": 0, "type": "table", "value": "employees" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,183
language_corpus
bird:train.json:5788
How much higher in percentage does the word "grec" occur on the page titled "Àbac" than on the page titled "Astronomia"?
SELECT CAST((SUM(CASE WHEN T3.title = 'Àbac' THEN T2.occurrences END) - SUM(CASE WHEN T3.title = 'Astronomia' THEN T2.occurrences END)) AS REAL) * 100 / SUM(CASE WHEN T3.title = 'Astronomia' THEN T2.occurrences END) FROM words AS T1 INNER JOIN pages_words AS T2 ON T1.wid = T2.wid INNER JOIN pages AS T3 ON T2.pid = T3.pid WHERE T1.word = 'grec'
[ "How", "much", "higher", "in", "percentage", "does", "the", "word", "\"", "grec", "\"", "occur", "on", "the", "page", "titled", "\"", "Àbac", "\"", "than", "on", "the", "page", "titled", "\"", "Astronomia", "\"", "?" ]
[ { "id": 4, "type": "table", "value": "pages_words" }, { "id": 8, "type": "column", "value": "occurrences" }, { "id": 10, "type": "value", "value": "Astronomia" }, { "id": 0, "type": "table", "value": "pages" }, { "id": 3, "type": "table", "value": "words" }, { "id": 9, "type": "column", "value": "title" }, { "id": 1, "type": "column", "value": "word" }, { "id": 2, "type": "value", "value": "grec" }, { "id": 11, "type": "value", "value": "Àbac" }, { "id": 5, "type": "column", "value": "pid" }, { "id": 6, "type": "value", "value": "100" }, { "id": 7, "type": "column", "value": "wid" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
15,184
network_2
spider:train_spider.json:4412
Who is the youngest male?
SELECT name FROM Person WHERE gender = 'male' AND age = (SELECT min(age) FROM person WHERE gender = 'male' )
[ "Who", "is", "the", "youngest", "male", "?" ]
[ { "id": 0, "type": "table", "value": "person" }, { "id": 2, "type": "column", "value": "gender" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "male" }, { "id": 4, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-VALUE", "O" ]
15,185
driving_school
spider:train_spider.json:6624
How many vehicle in total?
SELECT count(*) FROM Vehicles;
[ "How", "many", "vehicle", "in", "total", "?" ]
[ { "id": 0, "type": "table", "value": "vehicles" } ]
[ { "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" ]
15,186
mondial_geo
bird:train.json:8389
For all the countries that is smaller than 100 square kilometres, which one has the most GDP?
SELECT T1.Name FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country WHERE T1.Area < 100 ORDER BY T2.GDP DESC LIMIT 1
[ "For", "all", "the", "countries", "that", "is", "smaller", "than", "100", "square", "kilometres", ",", "which", "one", "has", "the", "most", "GDP", "?" ]
[ { "id": 1, "type": "table", "value": "country" }, { "id": 2, "type": "table", "value": "economy" }, { "id": 7, "type": "column", "value": "country" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "area" }, { "id": 6, "type": "column", "value": "code" }, { "id": 4, "type": "value", "value": "100" }, { "id": 5, "type": "column", "value": "gdp" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,187
soccer_2016
bird:train.json:1970
How many matches in 2009 had win margins of less than 10?
SELECT COUNT(Match_Id) FROM `Match` WHERE Match_Date LIKE '2009%' AND Win_Margin < 10
[ "How", "many", "matches", "in", "2009", "had", "win", "margins", "of", "less", "than", "10", "?" ]
[ { "id": 2, "type": "column", "value": "match_date" }, { "id": 4, "type": "column", "value": "win_margin" }, { "id": 1, "type": "column", "value": "match_id" }, { "id": 0, "type": "table", "value": "Match" }, { "id": 3, "type": "value", "value": "2009%" }, { "id": 5, "type": "value", "value": "10" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 6, 7 ] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
15,188
product_catalog
spider:train_spider.json:340
Find the total number of catalog contents.
SELECT count(*) FROM catalog_contents
[ "Find", "the", "total", "number", "of", "catalog", "contents", "." ]
[ { "id": 0, "type": "table", "value": "catalog_contents" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "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", "I-TABLE", "O" ]
15,189
public_review_platform
bird:train.json:4018
What are the opening and closing time of business id 1 for day id 2?
SELECT opening_time, closing_time FROM Business_Hours WHERE business_id = 1 AND day_id = 2
[ "What", "are", "the", "opening", "and", "closing", "time", "of", "business", "i", "d", "1", "for", "day", "i", "d", "2", "?" ]
[ { "id": 0, "type": "table", "value": "business_hours" }, { "id": 1, "type": "column", "value": "opening_time" }, { "id": 2, "type": "column", "value": "closing_time" }, { "id": 3, "type": "column", "value": "business_id" }, { "id": 5, "type": "column", "value": "day_id" }, { "id": 4, "type": "value", "value": "1" }, { "id": 6, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 13, 14, 15 ] }, { "entity_id": 6, "token_idxs": [ 16 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
15,190
college_completion
bird:train.json:3687
Name the state with the most number of graduate cohort in 2012 from private institute for profit? List all such institutes in the mentioned state.
SELECT T1.state, T1.chronname FROM institution_details AS T1 INNER JOIN state_sector_grads AS T2 ON T1.state = T2.state WHERE T2.year = 2012 AND T1.control = 'Private for-profit' GROUP BY T2.grad_cohort ORDER BY COUNT(T2.grad_cohort) DESC LIMIT 1
[ "Name", "the", "state", "with", "the", "most", "number", "of", "graduate", "cohort", "in", "2012", "from", "private", "institute", "for", "profit", "?", "List", "all", "such", "institutes", "in", "the", "mentioned", "state", "." ]
[ { "id": 3, "type": "table", "value": "institution_details" }, { "id": 4, "type": "table", "value": "state_sector_grads" }, { "id": 8, "type": "value", "value": "Private for-profit" }, { "id": 0, "type": "column", "value": "grad_cohort" }, { "id": 2, "type": "column", "value": "chronname" }, { "id": 7, "type": "column", "value": "control" }, { "id": 1, "type": "column", "value": "state" }, { "id": 5, "type": "column", "value": "year" }, { "id": 6, "type": "value", "value": "2012" } ]
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[ "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
15,191
vehicle_rent
bird:test.json:419
What is the average age for customers with a membership credit above the average?
SELECT avg(age) FROM customers WHERE membership_credit > (SELECT avg(membership_credit) FROM customers)
[ "What", "is", "the", "average", "age", "for", "customers", "with", "a", "membership", "credit", "above", "the", "average", "?" ]
[ { "id": 1, "type": "column", "value": "membership_credit" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 9, 10 ] }, { "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", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
15,192
browser_web
spider:train_spider.json:1828
List the ids, names and market shares of all browsers.
SELECT id , name , market_share FROM browser
[ "List", "the", "ids", ",", "names", "and", "market", "shares", "of", "all", "browsers", "." ]
[ { "id": 3, "type": "column", "value": "market_share" }, { "id": 0, "type": "table", "value": "browser" }, { "id": 2, "type": "column", "value": "name" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 6, 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O" ]
15,193
twitter_1
spider:train_spider.json:284
Find the name and email of the users who have more than 1000 followers.
SELECT name , email FROM user_profiles WHERE followers > 1000
[ "Find", "the", "name", "and", "email", "of", "the", "users", "who", "have", "more", "than", "1000", "followers", "." ]
[ { "id": 0, "type": "table", "value": "user_profiles" }, { "id": 3, "type": "column", "value": "followers" }, { "id": 2, "type": "column", "value": "email" }, { "id": 1, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "1000" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 13 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,194
law_episode
bird:train.json:1248
Please list all the keywords for the episodes with a rating of over 8.
SELECT T2.keyword FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T1.rating > 8
[ "Please", "list", "all", "the", "keywords", "for", "the", "episodes", "with", "a", "rating", "of", "over", "8", "." ]
[ { "id": 5, "type": "column", "value": "episode_id" }, { "id": 0, "type": "column", "value": "keyword" }, { "id": 1, "type": "table", "value": "episode" }, { "id": 2, "type": "table", "value": "keyword" }, { "id": 3, "type": "column", "value": "rating" }, { "id": 4, "type": "value", "value": "8" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
15,195
world_development_indicators
bird:train.json:2192
What upper middle income country under East Asia & Pacific region which covers the topic about Social Protection & Labor: Migration ? Indicate the short name of the said country.
SELECT DISTINCT T1.ShortName FROM Country AS T1 INNER JOIN footnotes AS T2 ON T1.CountryCode = T2.CountryCode INNER JOIN Series AS T3 ON T2.Seriescode = T3.SeriesCode WHERE T1.IncomeGroup = 'Upper middle income' AND T1.Region = 'East Asia & Pacific' AND T3.Topic = 'Social Protection & Labor: Migration'
[ "What", "upper", "middle", "income", "country", "under", "East", "Asia", "&", "Pacific", "region", "which", "covers", "the", "topic", "about", "Social", "Protection", "&", "Labor", ":", "Migration", "\n", "?", "Indicate", "the", "short", "name", "of", "the", "said", "country", "." ]
[ { "id": 10, "type": "value", "value": "Social Protection & Labor: Migration" }, { "id": 6, "type": "value", "value": "Upper middle income" }, { "id": 8, "type": "value", "value": "East Asia & Pacific" }, { "id": 5, "type": "column", "value": "incomegroup" }, { "id": 11, "type": "column", "value": "countrycode" }, { "id": 4, "type": "column", "value": "seriescode" }, { "id": 0, "type": "column", "value": "shortname" }, { "id": 3, "type": "table", "value": "footnotes" }, { "id": 2, "type": "table", "value": "country" }, { "id": 1, "type": "table", "value": "series" }, { "id": 7, "type": "column", "value": "region" }, { "id": 9, "type": "column", "value": "topic" } ]
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[ "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
15,196
pilot_1
bird:test.json:1134
What are the names of pilots, ordered by age descending?
SELECT pilot_name FROM pilotskills ORDER BY age DESC
[ "What", "are", "the", "names", "of", "pilots", ",", "ordered", "by", "age", "descending", "?" ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "pilot_name" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,197
movie_3
bird:train.json:9184
How many films are categorized as horror?
SELECT COUNT(T1.film_id) FROM film_category AS T1 INNER JOIN category AS T2 ON T1.category_id = T2.category_id WHERE T2.name = 'Horror'
[ "How", "many", "films", "are", "categorized", "as", "horror", "?" ]
[ { "id": 0, "type": "table", "value": "film_category" }, { "id": 5, "type": "column", "value": "category_id" }, { "id": 1, "type": "table", "value": "category" }, { "id": 4, "type": "column", "value": "film_id" }, { "id": 3, "type": "value", "value": "Horror" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "B-TABLE", "O", "B-VALUE", "O" ]
15,198
book_review
bird:test.json:612
How many distinct types of book are there?
SELECT count(DISTINCT TYPE) FROM book
[ "How", "many", "distinct", "types", "of", "book", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "book" }, { "id": 1, "type": "column", "value": "type" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O" ]
15,199
disney
bird:train.json:4670
List all of Wolfgang Reitherman's movies and their voice actors.
SELECT T1.name, T2.`voice-actor` FROM director AS T1 INNER JOIN `voice-actors` AS T2 ON T1.name = T2.movie WHERE T1.director = 'Wolfgang Reitherman'
[ "List", "all", "of", "Wolfgang", "Reitherman", "'s", "movies", "and", "their", "voice", "actors", "." ]
[ { "id": 5, "type": "value", "value": "Wolfgang Reitherman" }, { "id": 3, "type": "table", "value": "voice-actors" }, { "id": 1, "type": "column", "value": "voice-actor" }, { "id": 2, "type": "table", "value": "director" }, { "id": 4, "type": "column", "value": "director" }, { "id": 6, "type": "column", "value": "movie" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9, 10 ] }, { "entity_id": 5, "token_idxs": [ 3, 4 ] }, { "entity_id": 6, "token_idxs": [ 6 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,200
books
bird:train.json:5984
Provide the number of orders by Daisey Lamball in 2021.
SELECT COUNT(*) FROM cust_order AS T1 INNER JOIN customer AS T2 ON T1.customer_id = T2.customer_id WHERE T2.first_name = 'Daisey' AND T2.last_name = 'Lamball' AND STRFTIME('%Y', T1.order_date) = '2021'
[ "Provide", "the", "number", "of", "orders", "by", "Daisey", "Lamball", "in", "2021", "." ]
[ { "id": 2, "type": "column", "value": "customer_id" }, { "id": 0, "type": "table", "value": "cust_order" }, { "id": 3, "type": "column", "value": "first_name" }, { "id": 9, "type": "column", "value": "order_date" }, { "id": 5, "type": "column", "value": "last_name" }, { "id": 1, "type": "table", "value": "customer" }, { "id": 6, "type": "value", "value": "Lamball" }, { "id": 4, "type": "value", "value": "Daisey" }, { "id": 7, "type": "value", "value": "2021" }, { "id": 8, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 7 ] }, { "entity_id": 7, "token_idxs": [ 9 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 4, 5 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "B-VALUE", "O", "B-VALUE", "O" ]
15,201
retail_world
bird:train.json:6565
Describe the ordered products which were the most overdue from required date.
SELECT DISTINCT T3.ProductName FROM Orders AS T1 INNER JOIN `Order Details` AS T2 ON T1.OrderID = T2.OrderID INNER JOIN Products AS T3 ON T2.ProductID = T3.ProductID WHERE DATEDIFF(T1.ShippedDate, T1.RequiredDate) < 0
[ "Describe", "the", "ordered", "products", "which", "were", "the", "most", "overdue", "from", "required", "date", "." ]
[ { "id": 4, "type": "table", "value": "Order Details" }, { "id": 7, "type": "column", "value": "requireddate" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 6, "type": "column", "value": "shippeddate" }, { "id": 5, "type": "column", "value": "productid" }, { "id": 1, "type": "table", "value": "products" }, { "id": 8, "type": "column", "value": "orderid" }, { "id": 3, "type": "table", "value": "orders" }, { "id": 2, "type": "value", "value": "0" } ]
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[ "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,202
hockey
bird:train.json:7804
What is the full name of players origin from Finland?
SELECT DISTINCT firstName, lastName FROM Master WHERE birthCountry = 'Finland'
[ "What", "is", "the", "full", "name", "of", "players", "origin", "from", "Finland", "?" ]
[ { "id": 3, "type": "column", "value": "birthcountry" }, { "id": 1, "type": "column", "value": "firstname" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 4, "type": "value", "value": "Finland" }, { "id": 0, "type": "table", "value": "master" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O" ]
15,203
university_basketball
spider:train_spider.json:992
Return the name of the team and the acc during the regular season for the school that was founded the earliest.
SELECT t2.team_name , t2.ACC_Regular_Season FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id ORDER BY t1.founded LIMIT 1
[ "Return", "the", "name", "of", "the", "team", "and", "the", "acc", "during", "the", "regular", "season", "for", "the", "school", "that", "was", "founded", "the", "earliest", "." ]
[ { "id": 1, "type": "column", "value": "acc_regular_season" }, { "id": 3, "type": "table", "value": "basketball_match" }, { "id": 2, "type": "table", "value": "university" }, { "id": 0, "type": "column", "value": "team_name" }, { "id": 5, "type": "column", "value": "school_id" }, { "id": 4, "type": "column", "value": "founded" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O" ]
15,204
ice_hockey_draft
bird:train.json:6943
Name the player who scored the most goals in a single game in the 2007-2008 season of WHL?
SELECT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '2007-2008' AND T1.LEAGUE = 'WHL' ORDER BY T1.G DESC LIMIT 1
[ "Name", "the", "player", "who", "scored", "the", "most", "goals", "in", "a", "single", "game", "in", "the", "2007", "-", "2008", "season", "of", "WHL", "?" ]
[ { "id": 1, "type": "table", "value": "seasonstatus" }, { "id": 0, "type": "column", "value": "playername" }, { "id": 2, "type": "table", "value": "playerinfo" }, { "id": 6, "type": "value", "value": "2007-2008" }, { "id": 4, "type": "column", "value": "eliteid" }, { "id": 5, "type": "column", "value": "season" }, { "id": 7, "type": "column", "value": "league" }, { "id": 8, "type": "value", "value": "WHL" }, { "id": 3, "type": "column", "value": "g" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]