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16,060
pilot_1
bird:test.json:1156
Count the number of entries for each plane name.
SELECT count(*) , plane_name FROM pilotskills GROUP BY plane_name
[ "Count", "the", "number", "of", "entries", "for", "each", "plane", "name", "." ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "plane_name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7, 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
16,061
book_publishing_company
bird:train.json:189
Name the publisher which has the most titles published in 1991.
SELECT T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE STRFTIME('%Y', T1.pubdate) = '1991' GROUP BY T1.pub_id, T2.pub_name ORDER BY COUNT(T1.title_id) DESC LIMIT 1
[ "Name", "the", "publisher", "which", "has", "the", "most", "titles", "published", "in", "1991", "." ]
[ { "id": 3, "type": "table", "value": "publishers" }, { "id": 1, "type": "column", "value": "pub_name" }, { "id": 7, "type": "column", "value": "title_id" }, { "id": 6, "type": "column", "value": "pubdate" }, { "id": 0, "type": "column", "value": "pub_id" }, { "id": 2, "type": "table", "value": "titles" }, { "id": 4, "type": "value", "value": "1991" }, { "id": 5, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 0 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "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": [] } ]
[ "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
16,062
european_football_1
bird:train.json:2747
How many teams playing in divisions in Greece have ever scored 4 or more goals?
SELECT COUNT(DISTINCT CASE WHEN T1.FTHG >= 4 THEN HomeTeam ELSE NULL end) + COUNT(DISTINCT CASE WHEN T1.FTAG >= 4 THEN AwayTeam ELSE NULL end) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.country = 'Greece'
[ "How", "many", "teams", "playing", "in", "divisions", "in", "Greece", "have", "ever", "scored", "4", "or", "more", "goals", "?" ]
[ { "id": 1, "type": "table", "value": "divisions" }, { "id": 5, "type": "column", "value": "division" }, { "id": 6, "type": "column", "value": "hometeam" }, { "id": 7, "type": "column", "value": "awayteam" }, { "id": 2, "type": "column", "value": "country" }, { "id": 0, "type": "table", "value": "matchs" }, { "id": 3, "type": "value", "value": "Greece" }, { "id": 8, "type": "column", "value": "fthg" }, { "id": 10, "type": "column", "value": "ftag" }, { "id": 4, "type": "column", "value": "div" }, { "id": 9, "type": "value", "value": "4" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [ 0 ] }, { "entity_id": 7, "token_idxs": [ 1, 2 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 11 ] }, { "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", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
16,063
cre_Students_Information_Systems
bird:test.json:469
How are all the achievements described? List the achievement detail and the type description.
SELECT T1.achievement_details , T2.achievement_type_description FROM Achievements AS T1 JOIN Ref_Achievement_Type AS T2 ON T1.achievement_type_code = T2.achievement_type_code
[ "How", "are", "all", "the", "achievements", "described", "?", "List", "the", "achievement", "detail", "and", "the", "type", "description", "." ]
[ { "id": 1, "type": "column", "value": "achievement_type_description" }, { "id": 4, "type": "column", "value": "achievement_type_code" }, { "id": 3, "type": "table", "value": "ref_achievement_type" }, { "id": 0, "type": "column", "value": "achievement_details" }, { "id": 2, "type": "table", "value": "achievements" } ]
[ { "entity_id": 0, "token_idxs": [ 9, 10 ] }, { "entity_id": 1, "token_idxs": [ 12, 13, 14 ] }, { "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-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
16,064
aan_1
bird:test.json:980
What are the titles and paper ids for papers written by Mckeown?
SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T3.author_id = T2.author_id WHERE T3.name LIKE "%Mckeown%"
[ "What", "are", "the", "titles", "and", "paper", "ids", "for", "papers", "written", "by", "Mckeown", "?" ]
[ { "id": 6, "type": "table", "value": "author_list" }, { "id": 4, "type": "column", "value": "%Mckeown%" }, { "id": 7, "type": "column", "value": "author_id" }, { "id": 1, "type": "column", "value": "paper_id" }, { "id": 2, "type": "table", "value": "author" }, { "id": 0, "type": "column", "value": "title" }, { "id": 5, "type": "table", "value": "paper" }, { "id": 3, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O" ]
16,065
chicago_crime
bird:train.json:8666
What is the total number of crimes that happened in Bridgeport with beat less than 1000?
SELECT SUM(CASE WHEN T2.beat < 1000 THEN 1 ELSE 0 END) FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T2.community_area_no = T1.community_area_no WHERE T1.community_area_name = 'Bridgeport'
[ "What", "is", "the", "total", "number", "of", "crimes", "that", "happened", "in", "Bridgeport", "with", "beat", "less", "than", "1000", "?" ]
[ { "id": 2, "type": "column", "value": "community_area_name" }, { "id": 4, "type": "column", "value": "community_area_no" }, { "id": 0, "type": "table", "value": "community_area" }, { "id": 3, "type": "value", "value": "Bridgeport" }, { "id": 1, "type": "table", "value": "crime" }, { "id": 7, "type": "column", "value": "beat" }, { "id": 8, "type": "value", "value": "1000" }, { "id": 5, "type": "value", "value": "0" }, { "id": 6, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 12 ] }, { "entity_id": 8, "token_idxs": [ 15 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
16,066
retail_world
bird:train.json:6396
Which supplier supplies the most amount of products?
SELECT T2.CompanyName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID GROUP BY T2.SupplierID, T2.CompanyName ORDER BY COUNT(T1.ProductName) DESC LIMIT 1
[ "Which", "supplier", "supplies", "the", "most", "amount", "of", "products", "?" ]
[ { "id": 1, "type": "column", "value": "companyname" }, { "id": 4, "type": "column", "value": "productname" }, { "id": 0, "type": "column", "value": "supplierid" }, { "id": 3, "type": "table", "value": "suppliers" }, { "id": 2, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O" ]
16,067
movie_2
bird:test.json:1807
Find the title of the movie that is played in the Odeon theater.
SELECT T1.title FROM movies AS T1 JOIN movietheaters AS T2 ON T1.code = T2.movie WHERE T2.name = 'Odeon'
[ "Find", "the", "title", "of", "the", "movie", "that", "is", "played", "in", "the", "Odeon", "theater", "." ]
[ { "id": 2, "type": "table", "value": "movietheaters" }, { "id": 1, "type": "table", "value": "movies" }, { "id": 0, "type": "column", "value": "title" }, { "id": 4, "type": "value", "value": "Odeon" }, { "id": 6, "type": "column", "value": "movie" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
16,068
train_station
spider:train_spider.json:6606
Show all locations that have train stations with at least 15 platforms and train stations with more than 25 total passengers.
SELECT DISTINCT LOCATION FROM station WHERE number_of_platforms >= 15 AND total_passengers > 25
[ "Show", "all", "locations", "that", "have", "train", "stations", "with", "at", "least", "15", "platforms", "and", "train", "stations", "with", "more", "than", "25", "total", "passengers", "." ]
[ { "id": 2, "type": "column", "value": "number_of_platforms" }, { "id": 4, "type": "column", "value": "total_passengers" }, { "id": 1, "type": "column", "value": "location" }, { "id": 0, "type": "table", "value": "station" }, { "id": 3, "type": "value", "value": "15" }, { "id": 5, "type": "value", "value": "25" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 19, 20 ] }, { "entity_id": 5, "token_idxs": [ 18 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O" ]
16,069
retail_world
bird:train.json:6420
How many owners are located in Mexico?
SELECT COUNT(ContactTitle) FROM Customers WHERE Country = 'Mexico' AND ContactTitle = 'Owner'
[ "How", "many", "owners", "are", "located", "in", "Mexico", "?" ]
[ { "id": 1, "type": "column", "value": "contacttitle" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 2, "type": "column", "value": "country" }, { "id": 3, "type": "value", "value": "Mexico" }, { "id": 4, "type": "value", "value": "Owner" } ]
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[ "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O" ]
16,071
beer_factory
bird:train.json:5311
What credit card is the most used in the purchase of non-alcoholic beer?
SELECT T2.CreditCardType FROM rootbeer AS T1 INNER JOIN `transaction` AS T2 ON T1.RootBeerID = T2.RootBeerID INNER JOIN rootbeerbrand AS T3 ON T1.BrandID = T3.BrandID WHERE T3.Alcoholic = 'FALSE' GROUP BY T2.CreditCardType ORDER BY COUNT(T2.CreditCardType) DESC LIMIT 1
[ "What", "credit", "card", "is", "the", "most", "used", "in", "the", "purchase", "of", "non", "-", "alcoholic", "beer", "?" ]
[ { "id": 0, "type": "column", "value": "creditcardtype" }, { "id": 1, "type": "table", "value": "rootbeerbrand" }, { "id": 5, "type": "table", "value": "transaction" }, { "id": 7, "type": "column", "value": "rootbeerid" }, { "id": 2, "type": "column", "value": "alcoholic" }, { "id": 4, "type": "table", "value": "rootbeer" }, { "id": 6, "type": "column", "value": "brandid" }, { "id": 3, "type": "value", "value": "FALSE" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O" ]
16,072
superstore
bird:train.json:2433
What is the profit from selling the "O'Sullivan Living Dimensions 2-Shelf Bookcases"?
SELECT DISTINCT T1.Profit FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.`Product Name` = 'O''Sullivan Living Dimensions 2-Shelf Bookcases'
[ "What", "is", "the", "profit", "from", "selling", "the", "\"", "O'Sullivan", "Living", "Dimensions", "2", "-", "Shelf", "Bookcases", "\"", "?" ]
[ { "id": 4, "type": "value", "value": "O'Sullivan Living Dimensions 2-Shelf Bookcases" }, { "id": 1, "type": "table", "value": "central_superstore" }, { "id": 3, "type": "column", "value": "Product Name" }, { "id": 5, "type": "column", "value": "Product ID" }, { "id": 2, "type": "table", "value": "product" }, { "id": 0, "type": "column", "value": "profit" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
16,073
movie
bird:train.json:769
Among the actors starred in Die Hard 2, list their net worth and birth date of actors with a height between 60 to 65.
SELECT T3.NetWorth, T3.`Date of Birth` FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE T1.Title = 'Die Hard 2' AND T3.`Height (Inches)` BETWEEN 60 AND 65
[ "Among", "the", "actors", "starred", "in", "Die", "Hard", "2", ",", "list", "their", "net", "worth", "and", "birth", "date", "of", "actors", "with", "a", "height", "between", "60", "to", "65", "." ]
[ { "id": 8, "type": "column", "value": "Height (Inches)" }, { "id": 1, "type": "column", "value": "Date of Birth" }, { "id": 4, "type": "table", "value": "characters" }, { "id": 7, "type": "value", "value": "Die Hard 2" }, { "id": 0, "type": "column", "value": "networth" }, { "id": 5, "type": "column", "value": "actorid" }, { "id": 11, "type": "column", "value": "movieid" }, { "id": 2, "type": "table", "value": "actor" }, { "id": 3, "type": "table", "value": "movie" }, { "id": 6, "type": "column", "value": "title" }, { "id": 9, "type": "value", "value": "60" }, { "id": 10, "type": "value", "value": "65" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
16,074
restaurant
bird:train.json:1685
List all counties where there is no Bakers Square Restaurant & Pie Shop.
SELECT DISTINCT T2.county FROM generalinfo AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T1.label != 'bakers square restaurant & pie shop'
[ "List", "all", "counties", "where", "there", "is", "no", "Bakers", "Square", "Restaurant", "&", "Pie", "Shop", "." ]
[ { "id": 4, "type": "value", "value": "bakers square restaurant & pie shop" }, { "id": 1, "type": "table", "value": "generalinfo" }, { "id": 2, "type": "table", "value": "geographic" }, { "id": 0, "type": "column", "value": "county" }, { "id": 3, "type": "column", "value": "label" }, { "id": 5, "type": "column", "value": "city" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
16,075
mondial_geo
bird:train.json:8322
List all islands that are greater than the island on which Warwickshire is located.
SELECT DISTINCT Name FROM island WHERE Area > ( SELECT DISTINCT T3.Area FROM city AS T1 INNER JOIN locatedOn AS T2 ON T1.Name = T2.City INNER JOIN island AS T3 ON T3.Name = T2.Island WHERE T1.Province = 'Warwickshire' )
[ "List", "all", "islands", "that", "are", "greater", "than", "the", "island", "on", "which", "Warwickshire", "is", "located", "." ]
[ { "id": 4, "type": "value", "value": "Warwickshire" }, { "id": 6, "type": "table", "value": "locatedon" }, { "id": 3, "type": "column", "value": "province" }, { "id": 0, "type": "table", "value": "island" }, { "id": 7, "type": "column", "value": "island" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "area" }, { "id": 5, "type": "table", "value": "city" }, { "id": 8, "type": "column", "value": "city" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-TABLE", "O" ]
16,076
device
spider:train_spider.json:5061
Return the names and locations of shops, ordered by name in alphabetical order.
SELECT Shop_Name , LOCATION FROM shop ORDER BY Shop_Name ASC
[ "Return", "the", "names", "and", "locations", "of", "shops", ",", "ordered", "by", "name", "in", "alphabetical", "order", "." ]
[ { "id": 1, "type": "column", "value": "shop_name" }, { "id": 2, "type": "column", "value": "location" }, { "id": 0, "type": "table", "value": "shop" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
16,077
flight_1
spider:train_spider.json:401
What is the average distance and average price for flights from Los Angeles.
SELECT avg(distance) , avg(price) FROM Flight WHERE origin = "Los Angeles"
[ "What", "is", "the", "average", "distance", "and", "average", "price", "for", "flights", "from", "Los", "Angeles", "." ]
[ { "id": 2, "type": "column", "value": "Los Angeles" }, { "id": 3, "type": "column", "value": "distance" }, { "id": 0, "type": "table", "value": "flight" }, { "id": 1, "type": "column", "value": "origin" }, { "id": 4, "type": "column", "value": "price" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O" ]
16,078
hr_1
spider:train_spider.json:3461
Find employee with ID and name of the country presently where (s)he is working.
SELECT T1.employee_id , T4.country_name FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id JOIN locations AS T3 ON T2.location_id = T3.location_id JOIN countries AS T4 ON T3.country_id = T4.country_id
[ "Find", "employee", "with", "ID", "and", "name", "of", "the", "country", "presently", "where", "(", "s)he", "is", "working", "." ]
[ { "id": 8, "type": "column", "value": "department_id" }, { "id": 1, "type": "column", "value": "country_name" }, { "id": 0, "type": "column", "value": "employee_id" }, { "id": 6, "type": "table", "value": "departments" }, { "id": 7, "type": "column", "value": "location_id" }, { "id": 4, "type": "column", "value": "country_id" }, { "id": 2, "type": "table", "value": "countries" }, { "id": 3, "type": "table", "value": "locations" }, { "id": 5, "type": "table", "value": "employees" } ]
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[ "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O" ]
16,079
student_loan
bird:train.json:4426
State the number of students do not have payment due.
SELECT COUNT(name) FROM no_payment_due WHERE bool = 'neg'
[ "State", "the", "number", "of", "students", "do", "not", "have", "payment", "due", "." ]
[ { "id": 0, "type": "table", "value": "no_payment_due" }, { "id": 1, "type": "column", "value": "bool" }, { "id": 3, "type": "column", "value": "name" }, { "id": 2, "type": "value", "value": "neg" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
16,080
cre_Theme_park
spider:train_spider.json:5888
Tell me the price ranges for all the hotels.
SELECT price_range FROM HOTELS
[ "Tell", "me", "the", "price", "ranges", "for", "all", "the", "hotels", "." ]
[ { "id": 1, "type": "column", "value": "price_range" }, { "id": 0, "type": "table", "value": "hotels" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 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", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
16,081
coinmarketcap
bird:train.json:6265
Which crytocurrency was not opened on 2013/5/3?
SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.date = '2013-05-03' AND T2.open IS NULL
[ "Which", "crytocurrency", "was", "not", "opened", "on", "2013/5/3", "?" ]
[ { "id": 2, "type": "table", "value": "historical" }, { "id": 6, "type": "value", "value": "2013-05-03" }, { "id": 4, "type": "column", "value": "coin_id" }, { "id": 1, "type": "table", "value": "coins" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "date" }, { "id": 7, "type": "column", "value": "open" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
16,082
product_catalog
spider:train_spider.json:322
Give me the average and minimum price (in Euro) of the products.
SELECT avg(price_in_euros) , min(price_in_euros) FROM catalog_contents
[ "Give", "me", "the", "average", "and", "minimum", "price", "(", "in", "Euro", ")", "of", "the", "products", "." ]
[ { "id": 0, "type": "table", "value": "catalog_contents" }, { "id": 1, "type": "column", "value": "price_in_euros" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6, 7, 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", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
16,083
university_basketball
spider:train_spider.json:1002
What are the total enrollments of universities of each affiliation type?
SELECT sum(enrollment) , affiliation FROM university GROUP BY affiliation
[ "What", "are", "the", "total", "enrollments", "of", "universities", "of", "each", "affiliation", "type", "?" ]
[ { "id": 1, "type": "column", "value": "affiliation" }, { "id": 0, "type": "table", "value": "university" }, { "id": 2, "type": "column", "value": "enrollment" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O" ]
16,084
sales
bird:train.json:5390
Calculate the total quantity of products purchased by customer called Adrian.
SELECT SUM(T2.Quantity) FROM Customers AS T1 INNER JOIN Sales AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.FirstName = 'Adam'
[ "Calculate", "the", "total", "quantity", "of", "products", "purchased", "by", "customer", "called", "Adrian", "." ]
[ { "id": 5, "type": "column", "value": "customerid" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 2, "type": "column", "value": "firstname" }, { "id": 4, "type": "column", "value": "quantity" }, { "id": 1, "type": "table", "value": "sales" }, { "id": 3, "type": "value", "value": "Adam" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
16,085
cs_semester
bird:train.json:860
Please list the full names of all the students who are research assistants with the highest research capability.
SELECT T1.f_name, T1.l_name FROM student AS T1 INNER JOIN RA AS T2 ON T1.student_id = T2.student_id WHERE T2.capability = 5
[ "Please", "list", "the", "full", "names", "of", "all", "the", "students", "who", "are", "research", "assistants", "with", "the", "highest", "research", "capability", "." ]
[ { "id": 4, "type": "column", "value": "capability" }, { "id": 6, "type": "column", "value": "student_id" }, { "id": 2, "type": "table", "value": "student" }, { "id": 0, "type": "column", "value": "f_name" }, { "id": 1, "type": "column", "value": "l_name" }, { "id": 3, "type": "table", "value": "ra" }, { "id": 5, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
16,086
aircraft
spider:train_spider.json:4833
Show the names of aircrafts that are associated with both an airport named "London Heathrow" and an airport named "London Gatwick"
SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Heathrow" INTERSECT SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick"
[ "Show", "the", "names", "of", "aircrafts", "that", "are", "associated", "with", "both", "an", "airport", "named", "\"", "London", "Heathrow", "\"", "and", "an", "airport", "named", "\"", "London", "Gatwick", "\"" ]
[ { "id": 6, "type": "table", "value": "airport_aircraft" }, { "id": 3, "type": "column", "value": "London Heathrow" }, { "id": 4, "type": "column", "value": "London Gatwick" }, { "id": 2, "type": "column", "value": "airport_name" }, { "id": 8, "type": "column", "value": "aircraft_id" }, { "id": 7, "type": "column", "value": "airport_id" }, { "id": 0, "type": "column", "value": "aircraft" }, { "id": 5, "type": "table", "value": "aircraft" }, { "id": 1, "type": "table", "value": "airport" } ]
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[ "O", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]