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soccer_2
spider:train_spider.json:5044
What is the total number of enrollment of schools that do not have any goalie player?
SELECT sum(enr) FROM college WHERE cName NOT IN (SELECT cName FROM tryout WHERE pPos = "goalie")
[ "What", "is", "the", "total", "number", "of", "enrollment", "of", "schools", "that", "do", "not", "have", "any", "goalie", "player", "?" ]
[ { "id": 0, "type": "table", "value": "college" }, { "id": 3, "type": "table", "value": "tryout" }, { "id": 5, "type": "column", "value": "goalie" }, { "id": 2, "type": "column", "value": "cname" }, { "id": 4, "type": "column", "value": "ppos" }, { "id": 1, "type": "column", "value": "enr" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
1
sales
bird:train.json:5394
What is the full name of employee who sold 1000 units?
SELECT DISTINCT T2.FirstName, T2.MiddleInitial, T2.LastName FROM Sales AS T1 INNER JOIN Employees AS T2 ON T1.SalesPersonID = T2.EmployeeID WHERE T1.Quantity = 1000
[ "What", "is", "the", "full", "name", "of", "employee", "who", "sold", "1000", "units", "?" ]
[ { "id": 1, "type": "column", "value": "middleinitial" }, { "id": 7, "type": "column", "value": "salespersonid" }, { "id": 8, "type": "column", "value": "employeeid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 4, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 5, "type": "column", "value": "quantity" }, { "id": 3, "type": "table", "value": "sales" }, { "id": 6, "type": "value", "value": "1000" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2
ship_1
spider:train_spider.json:6266
Find the name of the ships that are steered by both a captain with Midshipman rank and a captain with Lieutenant rank.
SELECT t1.name FROM ship AS t1 JOIN captain AS t2 ON t1.ship_id = t2.ship_id WHERE t2.rank = 'Midshipman' INTERSECT SELECT t1.name FROM ship AS t1 JOIN captain AS t2 ON t1.ship_id = t2.ship_id WHERE t2.rank = 'Lieutenant'
[ "Find", "the", "name", "of", "the", "ships", "that", "are", "steered", "by", "both", "a", "captain", "with", "Midshipman", "rank", "and", "a", "captain", "with", "Lieutenant", "rank", "." ]
[ { "id": 4, "type": "value", "value": "Midshipman" }, { "id": 5, "type": "value", "value": "Lieutenant" }, { "id": 2, "type": "table", "value": "captain" }, { "id": 6, "type": "column", "value": "ship_id" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "table", "value": "ship" }, { "id": 3, "type": "column", "value": "rank" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
3
bike_share_1
bird:train.json:9102
Calculate the average duration travelled by subscribers that both started and ended their trip in Mountain View City Hall and indicate the date when the station was first installed.
SELECT AVG(T1.duration), T2.installation_date FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.start_station_name = 'Mountain View City Hall' AND T1.subscription_type = 'Subscriber' AND T1.end_station_name = 'Mountain View City Hall'
[ "Calculate", "the", "average", "duration", "travelled", "by", "subscribers", "that", "both", "started", "and", "ended", "their", "trip", "in", "Mountain", "View", "City", "Hall", "and", "indicate", "the", "date", "when", "the", "station", "was", "first", "installed", "." ]
[ { "id": 6, "type": "value", "value": "Mountain View City Hall" }, { "id": 5, "type": "column", "value": "start_station_name" }, { "id": 0, "type": "column", "value": "installation_date" }, { "id": 7, "type": "column", "value": "subscription_type" }, { "id": 9, "type": "column", "value": "end_station_name" }, { "id": 8, "type": "value", "value": "Subscriber" }, { "id": 3, "type": "column", "value": "duration" }, { "id": 2, "type": "table", "value": "station" }, { "id": 1, "type": "table", "value": "trip" }, { "id": 4, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
4
customers_card_transactions
spider:train_spider.json:689
How many customers have an account?
SELECT count(DISTINCT customer_id) FROM Accounts
[ "How", "many", "customers", "have", "an", "account", "?" ]
[ { "id": 1, "type": "column", "value": "customer_id" }, { "id": 0, "type": "table", "value": "accounts" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
5
restaurant
bird:train.json:1694
Indicate the street numbers where Aux Delices Vietnamese Restaurant are located.
SELECT DISTINCT T1.street_num FROM location AS T1 INNER JOIN generalinfo AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T2.label = 'aux delices vietnamese restaurant'
[ "Indicate", "the", "street", "numbers", "where", "Aux", "Delices", "Vietnamese", "Restaurant", "are", "located", "." ]
[ { "id": 4, "type": "value", "value": "aux delices vietnamese restaurant" }, { "id": 5, "type": "column", "value": "id_restaurant" }, { "id": 2, "type": "table", "value": "generalinfo" }, { "id": 0, "type": "column", "value": "street_num" }, { "id": 1, "type": "table", "value": "location" }, { "id": 3, "type": "column", "value": "label" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "B-TABLE", "O" ]
7
talkingdata
bird:train.json:1065
Describe the device user gender and age of the event ID of 15251.
SELECT T1.gender, T1.age FROM gender_age AS T1 INNER JOIN events AS T2 ON T2.device_id = T1.device_id WHERE T2.event_id = 15251
[ "Describe", "the", "device", "user", "gender", "and", "age", "of", "the", "event", "ID", "of", "15251", "." ]
[ { "id": 2, "type": "table", "value": "gender_age" }, { "id": 6, "type": "column", "value": "device_id" }, { "id": 4, "type": "column", "value": "event_id" }, { "id": 0, "type": "column", "value": "gender" }, { "id": 3, "type": "table", "value": "events" }, { "id": 5, "type": "value", "value": "15251" }, { "id": 1, "type": "column", "value": "age" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
8
solvency_ii
spider:train_spider.json:4597
List the names of products that are not in any event.
SELECT Product_Name FROM Products WHERE Product_ID NOT IN (SELECT Product_ID FROM Products_in_Events)
[ "List", "the", "names", "of", "products", "that", "are", "not", "in", "any", "event", "." ]
[ { "id": 3, "type": "table", "value": "products_in_events" }, { "id": 1, "type": "column", "value": "product_name" }, { "id": 2, "type": "column", "value": "product_id" }, { "id": 0, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O" ]
10
food_inspection
bird:train.json:8843
List owner's name of businesses with a 100 score.
SELECT DISTINCT T2.owner_name FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.score = 100
[ "List", "owner", "'s", "name", "of", "businesses", "with", "a", "100", "score", "." ]
[ { "id": 1, "type": "table", "value": "inspections" }, { "id": 5, "type": "column", "value": "business_id" }, { "id": 0, "type": "column", "value": "owner_name" }, { "id": 2, "type": "table", "value": "businesses" }, { "id": 3, "type": "column", "value": "score" }, { "id": 4, "type": "value", "value": "100" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
11
aan_1
bird:test.json:1033
Who has the most papers co-authored with Mckeown , Kathleen ?
select t4.name from author_list as t1 join author_list as t2 on t1.paper_id = t2.paper_id and t1.author_id != t2.author_id join author as t3 on t1.author_id = t3.author_id join author as t4 on t2.author_id = t4.author_id where t3.name = "mckeown , kathleen" group by t2.author_id order by count(*) desc limit 1
[ "Who", "has", "the", "most", "papers", "co", "-", "authored", "with", "Mckeown", ",", "Kathleen", "?" ]
[ { "id": 3, "type": "column", "value": "mckeown , kathleen" }, { "id": 4, "type": "table", "value": "author_list" }, { "id": 0, "type": "column", "value": "author_id" }, { "id": 5, "type": "column", "value": "paper_id" }, { "id": 2, "type": "table", "value": "author" }, { "id": 1, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
12
app_store
bird:train.json:2522
How many of the users hold neutral attitude on "10 Best Foods for You" app and what category is this app?
SELECT COUNT(T2.App), T1.Category FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = '10 Best Foods for You' AND T2.Sentiment = 'Neutral'
[ "How", "many", "of", "the", "users", "hold", "neutral", "attitude", "on", "\"", "10", "Best", "Foods", "for", "You", "\"", "app", "and", "what", "category", "is", "this", "app", "?" ]
[ { "id": 4, "type": "value", "value": "10 Best Foods for You" }, { "id": 2, "type": "table", "value": "user_reviews" }, { "id": 1, "type": "table", "value": "playstore" }, { "id": 5, "type": "column", "value": "sentiment" }, { "id": 0, "type": "column", "value": "category" }, { "id": 6, "type": "value", "value": "Neutral" }, { "id": 3, "type": "column", "value": "app" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
13
activity_1
spider:train_spider.json:6764
What are the ids of the faculty members who do not advise any student.
SELECT FacID FROM Faculty EXCEPT SELECT advisor FROM Student
[ "What", "are", "the", "ids", "of", "the", "faculty", "members", "who", "do", "not", "advise", "any", "student", "." ]
[ { "id": 0, "type": "table", "value": "faculty" }, { "id": 1, "type": "table", "value": "student" }, { "id": 3, "type": "column", "value": "advisor" }, { "id": 2, "type": "column", "value": "facid" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
14
game_1
spider:train_spider.json:5992
What are the ids of all students who have advisor number 1121?
SELECT StuID FROM Student WHERE Advisor = 1121
[ "What", "are", "the", "ids", "of", "all", "students", "who", "have", "advisor", "number", "1121", "?" ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 2, "type": "column", "value": "advisor" }, { "id": 1, "type": "column", "value": "stuid" }, { "id": 3, "type": "value", "value": "1121" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
15
movies_4
bird:train.json:518
What is the average number of crews for a movie?
SELECT CAST(SUM(CD) AS REAL) / COUNT(movie_id) FROM ( SELECT movie_id, COUNT(person_id) AS CD FROM movie_crew GROUP BY movie_id )
[ "What", "is", "the", "average", "number", "of", "crews", "for", "a", "movie", "?" ]
[ { "id": 0, "type": "table", "value": "movie_crew" }, { "id": 3, "type": "column", "value": "person_id" }, { "id": 1, "type": "column", "value": "movie_id" }, { "id": 2, "type": "column", "value": "cd" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
16
video_games
bird:train.json:3479
Find out the platform of the game "Final Fantasy XIII-2".
SELECT T4.platform_name FROM game AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.game_id INNER JOIN game_platform AS T3 ON T2.id = T3.game_publisher_id INNER JOIN platform AS T4 ON T3.platform_id = T4.id WHERE T1.game_name = 'Final Fantasy XIII-2'
[ "Find", "out", "the", "platform", "of", "the", "game", "\"", "Final", "Fantasy", "XIII-2", "\"", "." ]
[ { "id": 3, "type": "value", "value": "Final Fantasy XIII-2" }, { "id": 9, "type": "column", "value": "game_publisher_id" }, { "id": 8, "type": "table", "value": "game_publisher" }, { "id": 0, "type": "column", "value": "platform_name" }, { "id": 4, "type": "table", "value": "game_platform" }, { "id": 5, "type": "column", "value": "platform_id" }, { "id": 2, "type": "column", "value": "game_name" }, { "id": 1, "type": "table", "value": "platform" }, { "id": 10, "type": "column", "value": "game_id" }, { "id": 7, "type": "table", "value": "game" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
17
party_host
spider:train_spider.json:2668
What is the average number of hosts for parties?
SELECT avg(Number_of_hosts) FROM party
[ "What", "is", "the", "average", "number", "of", "hosts", "for", "parties", "?" ]
[ { "id": 1, "type": "column", "value": "number_of_hosts" }, { "id": 0, "type": "table", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-TABLE", "O" ]
18
cookbook
bird:train.json:8870
How many ingredients must be rationed in the recipe "Raspberry Chiffon Pie"?
SELECT COUNT(*) FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Raspberry Chiffon Pie' AND T2.max_qty = T2.min_qty
[ "How", "many", "ingredients", "must", "be", "rationed", "in", "the", "recipe", "\"", "Raspberry", "Chiffon", "Pie", "\"", "?" ]
[ { "id": 4, "type": "value", "value": "Raspberry Chiffon Pie" }, { "id": 2, "type": "column", "value": "recipe_id" }, { "id": 1, "type": "table", "value": "quantity" }, { "id": 5, "type": "column", "value": "max_qty" }, { "id": 6, "type": "column", "value": "min_qty" }, { "id": 0, "type": "table", "value": "recipe" }, { "id": 3, "type": "column", "value": "title" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
19
trains
bird:train.json:720
Among the trains running west, how many trains have no more than one car with an open roof?
SELECT SUM(CASE WHEN T1.direction = 'west' THEN 1 ELSE 0 END)as count FROM trains AS T1 INNER JOIN ( SELECT train_id, COUNT(id) FROM cars WHERE roof = 'none' GROUP BY train_id HAVING COUNT(id) = 1 ) AS T2 ON T1.id = T2.train_id
[ "Among", "the", "trains", "running", "west", ",", "how", "many", "trains", "have", "no", "more", "than", "one", "car", "with", "an", "open", "roof", "?" ]
[ { "id": 8, "type": "column", "value": "direction" }, { "id": 2, "type": "column", "value": "train_id" }, { "id": 0, "type": "table", "value": "trains" }, { "id": 4, "type": "table", "value": "cars" }, { "id": 6, "type": "column", "value": "roof" }, { "id": 7, "type": "value", "value": "none" }, { "id": 9, "type": "value", "value": "west" }, { "id": 1, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
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[ "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
20
music_2
spider:train_spider.json:5205
What instruments did the musician with the last name "Heilo" play in the song "Le Pop"?
SELECT T4.instrument FROM Performance AS T1 JOIN Band AS T2 ON T1.bandmate = T2.id JOIN Songs AS T3 ON T3.SongId = T1.SongId JOIN Instruments AS T4 ON T4.songid = T3.songid AND T4.bandmateid = T2.id WHERE T2.lastname = "Heilo" AND T3.title = "Le Pop"
[ "What", "instruments", "did", "the", "musician", "with", "the", "last", "name", "\"", "Heilo", "\"", "play", "in", "the", "song", "\"", "Le", "Pop", "\"", "?" ]
[ { "id": 1, "type": "table", "value": "instruments" }, { "id": 7, "type": "table", "value": "performance" }, { "id": 0, "type": "column", "value": "instrument" }, { "id": 10, "type": "column", "value": "bandmateid" }, { "id": 3, "type": "column", "value": "lastname" }, { "id": 12, "type": "column", "value": "bandmate" }, { "id": 6, "type": "column", "value": "Le Pop" }, { "id": 9, "type": "column", "value": "songid" }, { "id": 2, "type": "table", "value": "songs" }, { "id": 4, "type": "column", "value": "Heilo" }, { "id": 5, "type": "column", "value": "title" }, { "id": 8, "type": "table", "value": "band" }, { "id": 11, "type": "column", "value": "id" } ]
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[ "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
21
movie_platform
bird:train.json:34
Which year has the least number of movies that was released and what is the title of the movie in that year that has the highest number of rating score of 1?
SELECT DISTINCT T1.movie_release_year, T1.movie_title FROM movies AS T1 INNER JOIN ratings AS T2 ON T1.movie_id = T2.movie_id WHERE T1.movie_release_year = ( SELECT movie_release_year FROM movies GROUP BY movie_release_year ORDER BY COUNT(movie_id) DESC LIMIT 1 ) AND T2.rating_score = 1
[ "Which", "year", "has", "the", "least", "number", "of", "movies", "that", "was", "released", "and", "what", "is", "the", "title", "of", "the", "movie", "in", "that", "year", "that", "has", "the", "highest", "number", "of", "rating", "score", "of", "1", "?" ]
[ { "id": 0, "type": "column", "value": "movie_release_year" }, { "id": 5, "type": "column", "value": "rating_score" }, { "id": 1, "type": "column", "value": "movie_title" }, { "id": 4, "type": "column", "value": "movie_id" }, { "id": 3, "type": "table", "value": "ratings" }, { "id": 2, "type": "table", "value": "movies" }, { "id": 6, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
22
college_2
spider:train_spider.json:1440
Find the name of instructors who didn't teach any courses?
SELECT name FROM instructor WHERE id NOT IN (SELECT id FROM teaches)
[ "Find", "the", "name", "of", "instructors", "who", "did", "n't", "teach", "any", "courses", "?" ]
[ { "id": 0, "type": "table", "value": "instructor" }, { "id": 3, "type": "table", "value": "teaches" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O" ]
23
candidate_poll
spider:train_spider.json:2399
Return the top 3 greatest support rates.
SELECT support_rate FROM candidate ORDER BY support_rate DESC LIMIT 3
[ "Return", "the", "top", "3", "greatest", "support", "rates", "." ]
[ { "id": 1, "type": "column", "value": "support_rate" }, { "id": 0, "type": "table", "value": "candidate" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
24
superstore
bird:train.json:2358
What was the total cost of Xerox 1952 ordered by Aimee Bixby on 2014/9/10?
SELECT DISTINCT (T2.Sales / (1 - T2.discount)) * T2.Quantity - Profit FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T2.`Product ID` WHERE T1.`Customer Name` = 'Aimee Bixby' AND T3.`Product Name` = 'Xerox 1952' AND T2.`Order Date` = '2014-09-10'
[ "What", "was", "the", "total", "cost", "of", "Xerox", "1952", "ordered", "by", "Aimee", "Bixby", "on", "2014/9/10", "?" ]
[ { "id": 3, "type": "table", "value": "central_superstore" }, { "id": 5, "type": "column", "value": "Customer Name" }, { "id": 7, "type": "column", "value": "Product Name" }, { "id": 6, "type": "value", "value": "Aimee Bixby" }, { "id": 12, "type": "column", "value": "Customer ID" }, { "id": 4, "type": "column", "value": "Product ID" }, { "id": 8, "type": "value", "value": "Xerox 1952" }, { "id": 9, "type": "column", "value": "Order Date" }, { "id": 10, "type": "value", "value": "2014-09-10" }, { "id": 11, "type": "column", "value": "quantity" }, { "id": 15, "type": "column", "value": "discount" }, { "id": 0, "type": "table", "value": "product" }, { "id": 1, "type": "column", "value": "profit" }, { "id": 2, "type": "table", "value": "people" }, { "id": 13, "type": "column", "value": "sales" }, { "id": 14, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O" ]
25
simpson_episodes
bird:train.json:4351
List down the names of person born in California, USA.
SELECT name FROM Person WHERE birth_region = 'California' AND birth_country = 'USA';
[ "List", "down", "the", "names", "of", "person", "born", "in", "California", ",", "USA", "." ]
[ { "id": 4, "type": "column", "value": "birth_country" }, { "id": 2, "type": "column", "value": "birth_region" }, { "id": 3, "type": "value", "value": "California" }, { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "USA" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
26
tracking_grants_for_research
spider:train_spider.json:4360
Which organisation hired the most number of research staff? List the organisation id, type and detail.
SELECT T1.organisation_id , T1.organisation_type , T1.organisation_details FROM Organisations AS T1 JOIN Research_Staff AS T2 ON T1.organisation_id = T2.employer_organisation_id GROUP BY T1.organisation_id ORDER BY count(*) DESC LIMIT 1
[ "Which", "organisation", "hired", "the", "most", "number", "of", "research", "staff", "?", "List", "the", "organisation", "i", "d", ",", "type", "and", "detail", "." ]
[ { "id": 5, "type": "column", "value": "employer_organisation_id" }, { "id": 2, "type": "column", "value": "organisation_details" }, { "id": 1, "type": "column", "value": "organisation_type" }, { "id": 0, "type": "column", "value": "organisation_id" }, { "id": 4, "type": "table", "value": "research_staff" }, { "id": 3, "type": "table", "value": "organisations" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O" ]
28
professional_basketball
bird:train.json:2893
From which college was the player who won the most award in 1970.
SELECT college FROM players WHERE playerID = ( SELECT playerID FROM awards_players WHERE year = 1970 GROUP BY playerID ORDER BY COUNT(award) DESC LIMIT 1 )
[ "From", "which", "college", "was", "the", "player", "who", "won", "the", "most", "award", "in", "1970", "." ]
[ { "id": 3, "type": "table", "value": "awards_players" }, { "id": 2, "type": "column", "value": "playerid" }, { "id": 0, "type": "table", "value": "players" }, { "id": 1, "type": "column", "value": "college" }, { "id": 6, "type": "column", "value": "award" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "1970" } ]
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[ "O", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
29
regional_sales
bird:train.json:2608
State the full name of state code "GA".
SELECT T FROM ( SELECT IIF(StateCode = 'GA', State, NULL) AS T FROM Regions ) WHERE T IS NOT NULL
[ "State", "the", "full", "name", "of", "state", "code", "\"", "GA", "\"", "." ]
[ { "id": 3, "type": "column", "value": "statecode" }, { "id": 1, "type": "table", "value": "regions" }, { "id": 2, "type": "column", "value": "state" }, { "id": 4, "type": "value", "value": "GA" }, { "id": 0, "type": "column", "value": "t" } ]
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[ "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O" ]
30
retail_world
bird:train.json:6442
How many of the orders are shipped to France?
SELECT COUNT(ShipCountry) FROM Orders WHERE ShipCountry = 'France'
[ "How", "many", "of", "the", "orders", "are", "shipped", "to", "France", "?" ]
[ { "id": 1, "type": "column", "value": "shipcountry" }, { "id": 0, "type": "table", "value": "orders" }, { "id": 2, "type": "value", "value": "France" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
31
cs_semester
bird:train.json:937
What is the capability on research of the student named Alvera McQuillin?
SELECT T2.capability FROM student AS T1 INNER JOIN RA AS T2 ON T1.student_id = T2.student_id WHERE T1.f_name = 'Alvera' AND T1.l_name = 'McQuillin'
[ "What", "is", "the", "capability", "on", "research", "of", "the", "student", "named", "Alvera", "McQuillin", "?" ]
[ { "id": 0, "type": "column", "value": "capability" }, { "id": 3, "type": "column", "value": "student_id" }, { "id": 7, "type": "value", "value": "McQuillin" }, { "id": 1, "type": "table", "value": "student" }, { "id": 4, "type": "column", "value": "f_name" }, { "id": 5, "type": "value", "value": "Alvera" }, { "id": 6, "type": "column", "value": "l_name" }, { "id": 2, "type": "table", "value": "ra" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "B-VALUE", "O" ]
32
retail_complains
bird:train.json:396
Among the complaints received in year 2015, what is total number of complaints timely response and closed with an explanation?
SELECT COUNT(T1.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE strftime('%Y', T1.`Date received`) = '2015' AND T2.`Timely response?` = 'Yes' AND T2.`Company response to consumer` = 'Closed with explanation'
[ "Among", "the", "complaints", "received", "in", "year", "2015", ",", "what", "is", "total", "number", "of", "complaints", "timely", "response", "and", "closed", "with", "an", "explanation", "?" ]
[ { "id": 6, "type": "column", "value": "Company response to consumer" }, { "id": 7, "type": "value", "value": "Closed with explanation" }, { "id": 4, "type": "column", "value": "Timely response?" }, { "id": 0, "type": "table", "value": "callcenterlogs" }, { "id": 9, "type": "column", "value": "Date received" }, { "id": 2, "type": "column", "value": "Complaint ID" }, { "id": 1, "type": "table", "value": "events" }, { "id": 3, "type": "value", "value": "2015" }, { "id": 5, "type": "value", "value": "Yes" }, { "id": 8, "type": "value", "value": "%Y" } ]
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[ "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
33
formula_1
spider:train_spider.json:2204
What are the names of all races held between 2009 and 2011?
SELECT name FROM races WHERE YEAR BETWEEN 2009 AND 2011
[ "What", "are", "the", "names", "of", "all", "races", "held", "between", "2009", "and", "2011", "?" ]
[ { "id": 0, "type": "table", "value": "races" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "2009" }, { "id": 4, "type": "value", "value": "2011" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
34
region_building
bird:test.json:324
Compute the average population of a region.
SELECT avg(Population) FROM region
[ "Compute", "the", "average", "population", "of", "a", "region", "." ]
[ { "id": 1, "type": "column", "value": "population" }, { "id": 0, "type": "table", "value": "region" } ]
[ { "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" ]
36
legislator
bird:train.json:4745
Please list the current official YouTube usernames of all the current female legislators.
SELECT T2.youtube FROM current AS T1 INNER JOIN `social-media` AS T2 ON T2.bioguide = T1.bioguide_id WHERE T1.gender_bio = 'F'
[ "Please", "list", "the", "current", "official", "YouTube", "usernames", "of", "all", "the", "current", "female", "legislators", "." ]
[ { "id": 2, "type": "table", "value": "social-media" }, { "id": 6, "type": "column", "value": "bioguide_id" }, { "id": 3, "type": "column", "value": "gender_bio" }, { "id": 5, "type": "column", "value": "bioguide" }, { "id": 0, "type": "column", "value": "youtube" }, { "id": 1, "type": "table", "value": "current" }, { "id": 4, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "B-TABLE", "O", "O", "O" ]
37
tracking_grants_for_research
spider:train_spider.json:4337
What is the response received date for the document described as Regular that was granted more than 100 dollars?
SELECT T1.response_received_date FROM Documents AS T1 JOIN Document_Types AS T2 ON T1.document_type_code = T2.document_type_code JOIN Grants AS T3 ON T1.grant_id = T3.grant_id WHERE T2.document_description = 'Regular' OR T3.grant_amount > 100
[ "What", "is", "the", "response", "received", "date", "for", "the", "document", "described", "as", "Regular", "that", "was", "granted", "more", "than", "100", "dollars", "?" ]
[ { "id": 0, "type": "column", "value": "response_received_date" }, { "id": 5, "type": "column", "value": "document_description" }, { "id": 9, "type": "column", "value": "document_type_code" }, { "id": 3, "type": "table", "value": "document_types" }, { "id": 7, "type": "column", "value": "grant_amount" }, { "id": 2, "type": "table", "value": "documents" }, { "id": 4, "type": "column", "value": "grant_id" }, { "id": 6, "type": "value", "value": "Regular" }, { "id": 1, "type": "table", "value": "grants" }, { "id": 8, "type": "value", "value": "100" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
38
image_and_language
bird:train.json:7603
What is the most common object class of image ID 56?
SELECT T2.OBJ_CLASS FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T1.IMG_ID = 56 GROUP BY T2.OBJ_CLASS ORDER BY COUNT(T2.OBJ_CLASS_ID) DESC LIMIT 1
[ "What", "is", "the", "most", "common", "object", "class", "of", "image", "ID", "56", "?" ]
[ { "id": 5, "type": "column", "value": "obj_class_id" }, { "id": 2, "type": "table", "value": "obj_classes" }, { "id": 0, "type": "column", "value": "obj_class" }, { "id": 1, "type": "table", "value": "img_obj" }, { "id": 3, "type": "column", "value": "img_id" }, { "id": 4, "type": "value", "value": "56" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
39
world_development_indicators
bird:train.json:2134
How many annual indicators use the Sum aggregation method from 2001 to 2003?
SELECT COUNT(DISTINCT T2.SeriesCode) FROM Footnotes AS T1 INNER JOIN Series AS T2 ON T1.Seriescode = T2.SeriesCode WHERE T1.Year IN ('YR2001', 'YR2002', 'YR2003') AND T2.Periodicity = 'Annual' AND T2.AggregationMethod = 'Sum'
[ "How", "many", "annual", "indicators", "use", "the", "Sum", "aggregation", "method", "from", "2001", "to", "2003", "?" ]
[ { "id": 9, "type": "column", "value": "aggregationmethod" }, { "id": 7, "type": "column", "value": "periodicity" }, { "id": 2, "type": "column", "value": "seriescode" }, { "id": 0, "type": "table", "value": "footnotes" }, { "id": 1, "type": "table", "value": "series" }, { "id": 4, "type": "value", "value": "YR2001" }, { "id": 5, "type": "value", "value": "YR2002" }, { "id": 6, "type": "value", "value": "YR2003" }, { "id": 8, "type": "value", "value": "Annual" }, { "id": 3, "type": "column", "value": "year" }, { "id": 10, "type": "value", "value": "Sum" } ]
[ { "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": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 12 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 2 ] }, { "entity_id": 9, "token_idxs": [ 7, 8 ] }, { "entity_id": 10, "token_idxs": [ 6 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O" ]
40
retail_world
bird:train.json:6350
Give the number of territories in the "Northern" region.
SELECT COUNT(T1.TerritoryID) FROM Territories AS T1 INNER JOIN Region AS T2 ON T1.RegionID = T2.RegionID WHERE T2.RegionDescription = 'Northern'
[ "Give", "the", "number", "of", "territories", "in", "the", "\"", "Northern", "\"", "region", "." ]
[ { "id": 2, "type": "column", "value": "regiondescription" }, { "id": 0, "type": "table", "value": "territories" }, { "id": 4, "type": "column", "value": "territoryid" }, { "id": 3, "type": "value", "value": "Northern" }, { "id": 5, "type": "column", "value": "regionid" }, { "id": 1, "type": "table", "value": "region" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "B-TABLE", "O" ]
41
baseball_1
spider:train_spider.json:3692
Find the number of games taken place in city Atlanta in 2000.
SELECT count(*) FROM home_game AS T1 JOIN park AS T2 ON T1.park_id = T2.park_id WHERE T1.year = 2000 AND T2.city = 'Atlanta';
[ "Find", "the", "number", "of", "games", "taken", "place", "in", "city", "Atlanta", "in", "2000", "." ]
[ { "id": 0, "type": "table", "value": "home_game" }, { "id": 2, "type": "column", "value": "park_id" }, { "id": 6, "type": "value", "value": "Atlanta" }, { "id": 1, "type": "table", "value": "park" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "2000" }, { "id": 5, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 8 ] }, { "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", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "B-VALUE", "O" ]
42
mental_health_survey
bird:train.json:4610
For which question did the user No.2183 gave the answer "Mood Disorder (Depression, Bipolar Disorder, etc)"?
SELECT T1.AnswerText FROM Answer AS T1 INNER JOIN Question AS T2 ON T1.QuestionID = T2.questionid WHERE T2.questionid = 2183 AND T1.AnswerText = 'Mood Disorder (Depression, Bipolar Disorder, etc)'
[ "For", "which", "question", "did", "the", "user", "No.2183", "gave", "the", "answer", "\"", "Mood", "Disorder", "(", "Depression", ",", "Bipolar", "Disorder", ",", "etc", ")", "\"", "?" ]
[ { "id": 5, "type": "value", "value": "Mood Disorder (Depression, Bipolar Disorder, etc)" }, { "id": 0, "type": "column", "value": "answertext" }, { "id": 3, "type": "column", "value": "questionid" }, { "id": 2, "type": "table", "value": "question" }, { "id": 1, "type": "table", "value": "answer" }, { "id": 4, "type": "value", "value": "2183" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [ 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
43
works_cycles
bird:train.json:7275
How many salespersons haven't met quota?
SELECT COUNT(BusinessEntityID) FROM SalesPerson WHERE Bonus = 0
[ "How", "many", "salespersons", "have", "n't", "met", "quota", "?" ]
[ { "id": 3, "type": "column", "value": "businessentityid" }, { "id": 0, "type": "table", "value": "salesperson" }, { "id": 1, "type": "column", "value": "bonus" }, { "id": 2, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
44
works_cycles
bird:train.json:7159
What is the size of the photo of product id No.1?
SELECT T1.ThumbNailPhoto FROM ProductPhoto AS T1 INNER JOIN ProductProductPhoto AS T2 ON T1.ProductPhotoID = T2.ProductPhotoID WHERE T2.ProductID = 1
[ "What", "is", "the", "size", "of", "the", "photo", "of", "product", "i", "d", "No.1", "?" ]
[ { "id": 2, "type": "table", "value": "productproductphoto" }, { "id": 0, "type": "column", "value": "thumbnailphoto" }, { "id": 5, "type": "column", "value": "productphotoid" }, { "id": 1, "type": "table", "value": "productphoto" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 4, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
45
advertising_agencies
bird:test.json:2138
Count the number of staff who did not attend any meeting.
SELECT count(*) FROM Staff WHERE staff_id NOT IN ( SELECT staff_id FROM Staff_in_meetings )
[ "Count", "the", "number", "of", "staff", "who", "did", "not", "attend", "any", "meeting", "." ]
[ { "id": 2, "type": "table", "value": "staff_in_meetings" }, { "id": 1, "type": "column", "value": "staff_id" }, { "id": 0, "type": "table", "value": "staff" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9, 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", "B-TABLE", "I-TABLE", "O" ]
46
cre_Doc_Workflow
bird:test.json:2044
List the codes and descriptions for all staff roles.
SELECT staff_role_code , staff_role_description FROM Ref_staff_roles
[ "List", "the", "codes", "and", "descriptions", "for", "all", "staff", "roles", "." ]
[ { "id": 2, "type": "column", "value": "staff_role_description" }, { "id": 0, "type": "table", "value": "ref_staff_roles" }, { "id": 1, "type": "column", "value": "staff_role_code" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7, 8 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
47
cars
bird:train.json:3119
Among the cars from Asia, list the IDs of cars that were introduced in 1979.
SELECT T1.ID FROM production AS T1 INNER JOIN country AS T2 ON T1.country = T2.origin WHERE T2.country = 'Japan' AND T1.model_year = 1979
[ "Among", "the", "cars", "from", "Asia", ",", "list", "the", "IDs", "of", "cars", "that", "were", "introduced", "in", "1979", "." ]
[ { "id": 1, "type": "table", "value": "production" }, { "id": 6, "type": "column", "value": "model_year" }, { "id": 2, "type": "table", "value": "country" }, { "id": 3, "type": "column", "value": "country" }, { "id": 4, "type": "column", "value": "origin" }, { "id": 5, "type": "value", "value": "Japan" }, { "id": 7, "type": "value", "value": "1979" }, { "id": 0, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 13, 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": [ 15 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-VALUE", "O" ]
48
icfp_1
spider:train_spider.json:2902
Find the name of the organization that has published the largest number of papers.
SELECT t1.name FROM inst AS t1 JOIN authorship AS t2 ON t1.instid = t2.instid JOIN papers AS t3 ON t2.paperid = t3.paperid GROUP BY t1.name ORDER BY count(*) DESC LIMIT 1
[ "Find", "the", "name", "of", "the", "organization", "that", "has", "published", "the", "largest", "number", "of", "papers", "." ]
[ { "id": 3, "type": "table", "value": "authorship" }, { "id": 4, "type": "column", "value": "paperid" }, { "id": 1, "type": "table", "value": "papers" }, { "id": 5, "type": "column", "value": "instid" }, { "id": 0, "type": "column", "value": "name" }, { "id": 2, "type": "table", "value": "inst" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 13 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 0 ] }, { "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-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
49
match_season
spider:train_spider.json:1093
How many players are from each country?
SELECT Country_name , COUNT(*) FROM country AS T1 JOIN match_season AS T2 ON T1.Country_id = T2.Country GROUP BY T1.Country_name
[ "How", "many", "players", "are", "from", "each", "country", "?" ]
[ { "id": 0, "type": "column", "value": "country_name" }, { "id": 2, "type": "table", "value": "match_season" }, { "id": 3, "type": "column", "value": "country_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 4, "type": "column", "value": "country" } ]
[ { "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": [] }, { "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" ]
50
talkingdata
bird:train.json:1210
How many women have apps from the game-Finding fault category installed on their device?
SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id INNER JOIN app_events_relevant AS T3 ON T2.event_id = T3.event_id WHERE T1.age < 23 AND T1.gender = 'F' AND T3.is_active = 0 AND T3.is_installed = 1
[ "How", "many", "women", "have", "apps", "from", "the", "game", "-", "Finding", "fault", "category", "installed", "on", "their", "device", "?" ]
[ { "id": 0, "type": "table", "value": "app_events_relevant" }, { "id": 3, "type": "table", "value": "events_relevant" }, { "id": 11, "type": "column", "value": "is_installed" }, { "id": 2, "type": "table", "value": "gender_age" }, { "id": 1, "type": "column", "value": "device_id" }, { "id": 9, "type": "column", "value": "is_active" }, { "id": 4, "type": "column", "value": "event_id" }, { "id": 7, "type": "column", "value": "gender" }, { "id": 5, "type": "column", "value": "age" }, { "id": 6, "type": "value", "value": "23" }, { "id": 8, "type": "value", "value": "F" }, { "id": 10, "type": "value", "value": "0" }, { "id": 12, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
51
inn_1
spider:train_spider.json:2609
How many rooms have a king bed?
SELECT count(*) FROM Rooms WHERE bedType = "King";
[ "How", "many", "rooms", "have", "a", "king", "bed", "?" ]
[ { "id": 1, "type": "column", "value": "bedtype" }, { "id": 0, "type": "table", "value": "rooms" }, { "id": 2, "type": "column", "value": "King" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
52
cre_Docs_and_Epenses
spider:train_spider.json:6396
What are the different statement ids on accounts, and the number of accounts for each?
SELECT STATEMENT_ID , count(*) FROM Accounts GROUP BY STATEMENT_ID
[ "What", "are", "the", "different", "statement", "ids", "on", "accounts", ",", "and", "the", "number", "of", "accounts", "for", "each", "?" ]
[ { "id": 1, "type": "column", "value": "statement_id" }, { "id": 0, "type": "table", "value": "accounts" } ]
[ { "entity_id": 0, "token_idxs": [ 13 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
54
talkingdata
bird:train.json:1085
How many app users belong to the category of Securities?
SELECT COUNT(T1.app_id) FROM app_labels AS T1 INNER JOIN label_categories AS T2 ON T2.label_id = T1.label_id WHERE T2.category = 'Securities'
[ "How", "many", "app", "users", "belong", "to", "the", "category", "of", "Securities", "?" ]
[ { "id": 1, "type": "table", "value": "label_categories" }, { "id": 0, "type": "table", "value": "app_labels" }, { "id": 3, "type": "value", "value": "Securities" }, { "id": 2, "type": "column", "value": "category" }, { "id": 5, "type": "column", "value": "label_id" }, { "id": 4, "type": "column", "value": "app_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "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", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
55
retail_world
bird:train.json:6661
What is the region where the customer who placed the order id 10276 located?
SELECT T1.Region FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.OrderID = 10276
[ "What", "is", "the", "region", "where", "the", "customer", "who", "placed", "the", "order", "i", "d", "10276", "located", "?" ]
[ { "id": 5, "type": "column", "value": "customerid" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 3, "type": "column", "value": "orderid" }, { "id": 0, "type": "column", "value": "region" }, { "id": 2, "type": "table", "value": "orders" }, { "id": 4, "type": "value", "value": "10276" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 11, 12 ] }, { "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", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-VALUE", "O", "O" ]
56
cre_Doc_Control_Systems
spider:train_spider.json:2116
How many documents were shipped by USPS?
SELECT count(*) FROM Ref_Shipping_Agents JOIN Documents ON Documents.shipping_agent_code = Ref_Shipping_Agents.shipping_agent_code WHERE Ref_Shipping_Agents.shipping_agent_name = "USPS";
[ "How", "many", "documents", "were", "shipped", "by", "USPS", "?" ]
[ { "id": 0, "type": "table", "value": "ref_shipping_agents" }, { "id": 2, "type": "column", "value": "shipping_agent_name" }, { "id": 4, "type": "column", "value": "shipping_agent_code" }, { "id": 1, "type": "table", "value": "documents" }, { "id": 3, "type": "column", "value": "USPS" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
57
sales
bird:train.json:5371
How many customer ids have purchased Hex Nut 9?
SELECT COUNT(T1.CustomerID) FROM Sales AS T1 INNER JOIN Products AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Name = 'Hex Nut 9'
[ "How", "many", "customer", "ids", "have", "purchased", "Hex", "Nut", "9", "?" ]
[ { "id": 4, "type": "column", "value": "customerid" }, { "id": 3, "type": "value", "value": "Hex Nut 9" }, { "id": 5, "type": "column", "value": "productid" }, { "id": 1, "type": "table", "value": "products" }, { "id": 0, "type": "table", "value": "sales" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 4, "token_idxs": [ 2, 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": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
59
hospital_1
spider:train_spider.json:3914
Find the names of all physicians and their primary affiliated departments' names.
SELECT T1.name , T3.name FROM physician AS T1 JOIN affiliated_with AS T2 ON T1.EmployeeID = T2.physician JOIN department AS T3 ON T2.department = T3.DepartmentID WHERE T2.PrimaryAffiliation = 1
[ "Find", "the", "names", "of", "all", "physicians", "and", "their", "primary", "affiliated", "departments", "'", "names", "." ]
[ { "id": 2, "type": "column", "value": "primaryaffiliation" }, { "id": 5, "type": "table", "value": "affiliated_with" }, { "id": 7, "type": "column", "value": "departmentid" }, { "id": 1, "type": "table", "value": "department" }, { "id": 6, "type": "column", "value": "department" }, { "id": 8, "type": "column", "value": "employeeid" }, { "id": 4, "type": "table", "value": "physician" }, { "id": 9, "type": "column", "value": "physician" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "O" ]
60
tracking_software_problems
spider:train_spider.json:5367
Which product has the most problems? Give me the number of problems and the product name.
SELECT count(*) , T1.product_name FROM product AS T1 JOIN problems AS T2 ON T1.product_id = T2.product_id GROUP BY T1.product_name ORDER BY count(*) DESC LIMIT 1
[ "Which", "product", "has", "the", "most", "problems", "?", "Give", "me", "the", "number", "of", "problems", "and", "the", "product", "name", "." ]
[ { "id": 0, "type": "column", "value": "product_name" }, { "id": 3, "type": "column", "value": "product_id" }, { "id": 2, "type": "table", "value": "problems" }, { "id": 1, "type": "table", "value": "product" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
61
cre_Doc_Tracking_DB
spider:train_spider.json:4177
Return the day Number and stored date for all the documents.
SELECT T2.day_Number , T1.Date_Stored FROM All_documents AS T1 JOIN Ref_calendar AS T2 ON T1.date_stored = T2.calendar_date
[ "Return", "the", "day", "Number", "and", "stored", "date", "for", "all", "the", "documents", "." ]
[ { "id": 2, "type": "table", "value": "all_documents" }, { "id": 4, "type": "column", "value": "calendar_date" }, { "id": 3, "type": "table", "value": "ref_calendar" }, { "id": 1, "type": "column", "value": "date_stored" }, { "id": 0, "type": "column", "value": "day_number" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
62
wine_1
spider:train_spider.json:6575
What are the maximum price and score of wines in each year?
SELECT max(Price) , max(Score) , YEAR FROM WINE GROUP BY YEAR
[ "What", "are", "the", "maximum", "price", "and", "score", "of", "wines", "in", "each", "year", "?" ]
[ { "id": 2, "type": "column", "value": "price" }, { "id": 3, "type": "column", "value": "score" }, { "id": 0, "type": "table", "value": "wine" }, { "id": 1, "type": "column", "value": "year" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
63
european_football_2
bird:dev.json:1076
What is the difference of the average ball control score between Abdou Diallo and Aaron Appindangoye ?
SELECT CAST(SUM(CASE WHEN t1.player_name = 'Abdou Diallo' THEN t2.ball_control ELSE 0 END) AS REAL) / COUNT(CASE WHEN t1.player_name = 'Abdou Diallo' THEN t2.id ELSE NULL END) - CAST(SUM(CASE WHEN t1.player_name = 'Aaron Appindangoye' THEN t2.ball_control ELSE 0 END) AS REAL) / COUNT(CASE WHEN t1.player_name = 'Aaron Appindangoye' THEN t2.id ELSE NULL END) FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id
[ "What", "is", "the", "difference", "of", "the", "average", "ball", "control", "score", "between", "Abdou", "Diallo", "and", "Aaron", "Appindangoye", "\n", "?" ]
[ { "id": 8, "type": "value", "value": "Aaron Appindangoye" }, { "id": 1, "type": "table", "value": "player_attributes" }, { "id": 2, "type": "column", "value": "player_api_id" }, { "id": 5, "type": "column", "value": "ball_control" }, { "id": 7, "type": "value", "value": "Abdou Diallo" }, { "id": 6, "type": "column", "value": "player_name" }, { "id": 0, "type": "table", "value": "player" }, { "id": 4, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "I-VALUE", "O", "O" ]
64
company_office
spider:train_spider.json:4543
How many companies are there?
SELECT count(*) FROM Companies
[ "How", "many", "companies", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "companies" } ]
[ { "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" ]
65
mondial_geo
bird:train.json:8373
What is the proportion of English-speaking citizens in the countries that rely on the United States compared to the total number of citizens in those countries?
SELECT T2.Percentage * T1.Population FROM country AS T1 INNER JOIN language AS T2 ON T1.Code = T2.Country INNER JOIN politics AS T3 ON T3.Country = T2.Country WHERE T3.Dependent = 'USA' AND T2.Name = 'English'
[ "What", "is", "the", "proportion", "of", "English", "-", "speaking", "citizens", "in", "the", "countries", "that", "rely", "on", "the", "United", "States", "compared", "to", "the", "total", "number", "of", "citizens", "in", "those", "countries", "?" ]
[ { "id": 1, "type": "column", "value": "percentage" }, { "id": 2, "type": "column", "value": "population" }, { "id": 6, "type": "column", "value": "dependent" }, { "id": 0, "type": "table", "value": "politics" }, { "id": 4, "type": "table", "value": "language" }, { "id": 3, "type": "table", "value": "country" }, { "id": 5, "type": "column", "value": "country" }, { "id": 9, "type": "value", "value": "English" }, { "id": 8, "type": "column", "value": "name" }, { "id": 10, "type": "column", "value": "code" }, { "id": 7, "type": "value", "value": "USA" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
66
art_1
bird:test.json:1310
Find the first and last name of artists who have painting but no sculpture work.
SELECT T1.lname , T1.fname FROM artists AS T1 JOIN paintings AS T2 ON T1.artistID = T2.painterID EXCEPT SELECT T3.lname , T3.fname FROM artists AS T3 JOIN sculptures AS T4 ON T3.artistID = T4.sculptorID
[ "Find", "the", "first", "and", "last", "name", "of", "artists", "who", "have", "painting", "but", "no", "sculpture", "work", "." ]
[ { "id": 4, "type": "table", "value": "sculptures" }, { "id": 7, "type": "column", "value": "sculptorid" }, { "id": 3, "type": "table", "value": "paintings" }, { "id": 6, "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" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
67
hockey
bird:train.json:7672
Please list the awards the players who died in Arlington have won.
SELECT T2.award FROM Master AS T1 INNER JOIN AwardsPlayers AS T2 ON T1.playerID = T2.playerID WHERE T1.deathCity = 'Kemptville'
[ "Please", "list", "the", "awards", "the", "players", "who", "died", "in", "Arlington", "have", "won", "." ]
[ { "id": 2, "type": "table", "value": "awardsplayers" }, { "id": 4, "type": "value", "value": "Kemptville" }, { "id": 3, "type": "column", "value": "deathcity" }, { "id": 5, "type": "column", "value": "playerid" }, { "id": 1, "type": "table", "value": "master" }, { "id": 0, "type": "column", "value": "award" } ]
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[ "O", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
68
video_games
bird:train.json:3379
Provide the genre name of the genre ID 3.
SELECT T.genre_name FROM genre AS T WHERE T.id = 3
[ "Provide", "the", "genre", "name", "of", "the", "genre", "ID", "3", "." ]
[ { "id": 1, "type": "column", "value": "genre_name" }, { "id": 0, "type": "table", "value": "genre" }, { "id": 2, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "3" } ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
69
regional_sales
bird:train.json:2635
Which sales team id has the highest number of orders in 2018?
SELECT _SalesTeamID FROM `Sales Orders` WHERE OrderDate LIKE '%/%/18' GROUP BY _SalesTeamID ORDER BY COUNT(_SalesTeamID) DESC LIMIT 1
[ "Which", "sales", "team", "i", "d", "has", "the", "highest", "number", "of", "orders", "in", "2018", "?" ]
[ { "id": 0, "type": "table", "value": "Sales Orders" }, { "id": 1, "type": "column", "value": "_salesteamid" }, { "id": 2, "type": "column", "value": "orderdate" }, { "id": 3, "type": "value", "value": "%/%/18" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O" ]
70
thrombosis_prediction
bird:dev.json:1172
How many male patients have elevated total bilirubin count?
SELECT COUNT(DISTINCT T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.`T-BIL` >= 2.0 AND T1.SEX = 'M'
[ "How", "many", "male", "patients", "have", "elevated", "total", "bilirubin", "count", "?" ]
[ { "id": 1, "type": "table", "value": "laboratory" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 3, "type": "column", "value": "T-BIL" }, { "id": 4, "type": "value", "value": "2.0" }, { "id": 5, "type": "column", "value": "sex" }, { "id": 2, "type": "column", "value": "id" }, { "id": 6, "type": "value", "value": "M" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
71
synthea
bird:train.json:1458
What percentage of patients born in 'Pembroke MA US' have 'allergy to grass pollen'?
SELECT CAST(SUM(CASE WHEN T2.DESCRIPTION = 'Allergy to grass pollen' THEN 1 ELSE 0 END) AS REL) * 100 / COUNT(T1.patient) FROM patients AS T1 INNER JOIN allergies AS T2 ON T1.patient = T2.PATIENT WHERE T1.birthplace = 'Pembroke MA US'
[ "What", "percentage", "of", "patients", "born", "in", "'", "Pembroke", "MA", "US", "'", "have", "'", "allergy", "to", "grass", "pollen", "'", "?" ]
[ { "id": 9, "type": "value", "value": "Allergy to grass pollen" }, { "id": 3, "type": "value", "value": "Pembroke MA US" }, { "id": 8, "type": "column", "value": "description" }, { "id": 2, "type": "column", "value": "birthplace" }, { "id": 1, "type": "table", "value": "allergies" }, { "id": 0, "type": "table", "value": "patients" }, { "id": 4, "type": "column", "value": "patient" }, { "id": 5, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
72
activity_1
spider:train_spider.json:6786
Which activity has the most faculty members participating in? Find the activity name.
SELECT T1.activity_name FROM Activity AS T1 JOIN Faculty_participates_in AS T2 ON T1.actID = T2.actID GROUP BY T1.actID ORDER BY count(*) DESC LIMIT 1
[ "Which", "activity", "has", "the", "most", "faculty", "members", "participating", "in", "?", "Find", "the", "activity", "name", "." ]
[ { "id": 3, "type": "table", "value": "faculty_participates_in" }, { "id": 1, "type": "column", "value": "activity_name" }, { "id": 2, "type": "table", "value": "activity" }, { "id": 0, "type": "column", "value": "actid" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
73
law_episode
bird:train.json:1318
How many 6-star votes did episode 12 get? Please include the air date and rating.
SELECT T2.air_date, T2.rating FROM Vote AS T1 INNER JOIN Episode AS T2 ON T2.episode_id = T1.episode_id WHERE T1.stars = 6 AND T2.episode = 12
[ "How", "many", "6", "-", "star", "votes", "did", "episode", "12", "get", "?", "Please", "include", "the", "air", "date", "and", "rating", "." ]
[ { "id": 4, "type": "column", "value": "episode_id" }, { "id": 0, "type": "column", "value": "air_date" }, { "id": 3, "type": "table", "value": "episode" }, { "id": 7, "type": "column", "value": "episode" }, { "id": 1, "type": "column", "value": "rating" }, { "id": 5, "type": "column", "value": "stars" }, { "id": 2, "type": "table", "value": "vote" }, { "id": 8, "type": "value", "value": "12" }, { "id": 6, "type": "value", "value": "6" } ]
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[ "O", "O", "B-VALUE", "O", "B-COLUMN", "B-TABLE", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O" ]
75
company_office
spider:train_spider.json:4581
Show the headquarters shared by more than two companies.
SELECT Headquarters FROM Companies GROUP BY Headquarters HAVING COUNT(*) > 2
[ "Show", "the", "headquarters", "shared", "by", "more", "than", "two", "companies", "." ]
[ { "id": 1, "type": "column", "value": "headquarters" }, { "id": 0, "type": "table", "value": "companies" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
76
human_resources
bird:train.json:8962
How many employees whose performance is poor have a salary of over $50,000 per year?
SELECT COUNT(*) FROM employee WHERE performance = 'Poor' AND CAST(REPLACE(SUBSTR(salary, 4), ',', '') AS REAL) > 50000
[ "How", "many", "employees", "whose", "performance", "is", "poor", "have", "a", "salary", "of", "over", "$", "50,000", "per", "year", "?" ]
[ { "id": 1, "type": "column", "value": "performance" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 5, "type": "column", "value": "salary" }, { "id": 3, "type": "value", "value": "50000" }, { "id": 2, "type": "value", "value": "Poor" }, { "id": 4, "type": "value", "value": "," }, { "id": 6, "type": "value", "value": "4" } ]
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[ "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
77
conference
bird:test.json:1076
What is the name of the institution with no staff in the records?
SELECT institution_name FROM institution WHERE institution_id NOT IN (SELECT institution_id FROM staff)
[ "What", "is", "the", "name", "of", "the", "institution", "with", "no", "staff", "in", "the", "records", "?" ]
[ { "id": 1, "type": "column", "value": "institution_name" }, { "id": 2, "type": "column", "value": "institution_id" }, { "id": 0, "type": "table", "value": "institution" }, { "id": 3, "type": "table", "value": "staff" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
78
chicago_crime
bird:train.json:8670
What is the district address associated with the case JB107731?
SELECT T1.address FROM District AS T1 INNER JOIN Crime AS T2 ON T2.district_no = T1.district_no WHERE T2.case_number = 'JB107731'
[ "What", "is", "the", "district", "address", "associated", "with", "the", "case", "JB107731", "?" ]
[ { "id": 3, "type": "column", "value": "case_number" }, { "id": 5, "type": "column", "value": "district_no" }, { "id": 1, "type": "table", "value": "district" }, { "id": 4, "type": "value", "value": "JB107731" }, { "id": 0, "type": "column", "value": "address" }, { "id": 2, "type": "table", "value": "crime" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O" ]
79
authors
bird:train.json:3562
List down all paper name that were published in conference "International Conference on Internet Computing".
SELECT T1.Title FROM Paper AS T1 INNER JOIN Conference AS T2 ON T1.ConferenceId = T2.Id WHERE T2.FullName = 'International Conference on Internet Computing' AND T1.Title <> ''
[ "List", "down", "all", "paper", "name", "that", "were", "published", "in", "conference", "\"", "International", "Conference", "on", "Internet", "Computing", "\"", "." ]
[ { "id": 6, "type": "value", "value": "International Conference on Internet Computing" }, { "id": 3, "type": "column", "value": "conferenceid" }, { "id": 2, "type": "table", "value": "conference" }, { "id": 5, "type": "column", "value": "fullname" }, { "id": 0, "type": "column", "value": "title" }, { "id": 1, "type": "table", "value": "paper" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
80
movie_platform
bird:train.json:130
From all the movies that got more than 13000 popularity number, which one had the least ratings.
SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_popularity > 13000 ORDER BY T1.rating_score LIMIT 1
[ "From", "all", "the", "movies", "that", "got", "more", "than", "13000", "popularity", "number", ",", "which", "one", "had", "the", "least", "ratings", "." ]
[ { "id": 3, "type": "column", "value": "movie_popularity" }, { "id": 5, "type": "column", "value": "rating_score" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 6, "type": "column", "value": "movie_id" }, { "id": 1, "type": "table", "value": "ratings" }, { "id": 2, "type": "table", "value": "movies" }, { "id": 4, "type": "value", "value": "13000" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
81
chicago_crime
bird:train.json:8727
Please list any three community areas with a population of more than 50,000.
SELECT community_area_name FROM Community_Area WHERE population > 50000 LIMIT 3
[ "Please", "list", "any", "three", "community", "areas", "with", "a", "population", "of", "more", "than", "50,000", "." ]
[ { "id": 1, "type": "column", "value": "community_area_name" }, { "id": 0, "type": "table", "value": "community_area" }, { "id": 2, "type": "column", "value": "population" }, { "id": 3, "type": "value", "value": "50000" } ]
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[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
82
software_company
bird:train.json:8525
What is the number of inhabitants of the place the most customers are from?
SELECT DISTINCT T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T2.INHABITANTS_K DESC
[ "What", "is", "the", "number", "of", "inhabitants", "of", "the", "place", "the", "most", "customers", "are", "from", "?" ]
[ { "id": 0, "type": "column", "value": "inhabitants_k" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "demog" }, { "id": 3, "type": "column", "value": "geoid" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
83
mountain_photos
spider:train_spider.json:3712
Find the brand and name for each camera lens, and sort in descending order of maximum aperture.
SELECT brand , name FROM camera_lens ORDER BY max_aperture DESC
[ "Find", "the", "brand", "and", "name", "for", "each", "camera", "lens", ",", "and", "sort", "in", "descending", "order", "of", "maximum", "aperture", "." ]
[ { "id": 3, "type": "column", "value": "max_aperture" }, { "id": 0, "type": "table", "value": "camera_lens" }, { "id": 1, "type": "column", "value": "brand" }, { "id": 2, "type": "column", "value": "name" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
84
party_host
spider:train_spider.json:2681
For each party, find its location and the name of its host. Sort the result in ascending order of the age of the host.
SELECT T3.Location , T2.Name FROM party_host AS T1 JOIN HOST AS T2 ON T1.Host_ID = T2.Host_ID JOIN party AS T3 ON T1.Party_ID = T3.Party_ID ORDER BY T2.Age
[ "For", "each", "party", ",", "find", "its", "location", "and", "the", "name", "of", "its", "host", ".", "Sort", "the", "result", "in", "ascending", "order", "of", "the", "age", "of", "the", "host", "." ]
[ { "id": 4, "type": "table", "value": "party_host" }, { "id": 0, "type": "column", "value": "location" }, { "id": 6, "type": "column", "value": "party_id" }, { "id": 7, "type": "column", "value": "host_id" }, { "id": 2, "type": "table", "value": "party" }, { "id": 1, "type": "column", "value": "name" }, { "id": 5, "type": "table", "value": "host" }, { "id": 3, "type": "column", "value": "age" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
85
ice_hockey_draft
bird:train.json:6935
Who is the most valuable player in QMJHL league during the 2004-2005 season?
SELECT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON BETWEEN '2004' AND '2005' AND T1.LEAGUE = 'QMJHL' ORDER BY T1.P DESC LIMIT 1
[ "Who", "is", "the", "most", "valuable", "player", "in", "QMJHL", "league", "during", "the", "2004", "-", "2005", "season", "?" ]
[ { "id": 1, "type": "table", "value": "seasonstatus" }, { "id": 0, "type": "column", "value": "playername" }, { "id": 2, "type": "table", "value": "playerinfo" }, { "id": 4, "type": "column", "value": "eliteid" }, { "id": 5, "type": "column", "value": "season" }, { "id": 8, "type": "column", "value": "league" }, { "id": 9, "type": "value", "value": "QMJHL" }, { "id": 6, "type": "value", "value": "2004" }, { "id": 7, "type": "value", "value": "2005" }, { "id": 3, "type": "column", "value": "p" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-VALUE", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-VALUE", "B-COLUMN", "O" ]
86
csu_1
spider:train_spider.json:2354
What is the average fee on a CSU campus in 2005?
SELECT avg(campusfee) FROM csu_fees WHERE YEAR = 2005
[ "What", "is", "the", "average", "fee", "on", "a", "CSU", "campus", "in", "2005", "?" ]
[ { "id": 3, "type": "column", "value": "campusfee" }, { "id": 0, "type": "table", "value": "csu_fees" }, { "id": 1, "type": "column", "value": "year" }, { "id": 2, "type": "value", "value": "2005" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
87
soccer_2016
bird:train.json:1825
How many matches were played in Season 7?
SELECT COUNT(Match_Id) FROM `Match` WHERE Season_Id = 7
[ "How", "many", "matches", "were", "played", "in", "Season", "7", "?" ]
[ { "id": 1, "type": "column", "value": "season_id" }, { "id": 3, "type": "column", "value": "match_id" }, { "id": 0, "type": "table", "value": "Match" }, { "id": 2, "type": "value", "value": "7" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
88
customer_complaints
spider:train_spider.json:5793
Return the average price of products that have each category code.
SELECT avg(product_price) , product_category_code FROM products GROUP BY product_category_code
[ "Return", "the", "average", "price", "of", "products", "that", "have", "each", "category", "code", "." ]
[ { "id": 1, "type": "column", "value": "product_category_code" }, { "id": 2, "type": "column", "value": "product_price" }, { "id": 0, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
89
movie_3
bird:train.json:9422
What is the total amount of money Mary Smith has spent on film rentals?
SELECT SUM(T1.amount) FROM payment AS T1 INNER JOIN customer AS T2 ON T1.customer_id = T2.customer_id WHERE T2.first_name = 'MARY' AND T2.last_name = 'SMITH'
[ "What", "is", "the", "total", "amount", "of", "money", "Mary", "Smith", "has", "spent", "on", "film", "rentals", "?" ]
[ { "id": 3, "type": "column", "value": "customer_id" }, { "id": 4, "type": "column", "value": "first_name" }, { "id": 6, "type": "column", "value": "last_name" }, { "id": 1, "type": "table", "value": "customer" }, { "id": 0, "type": "table", "value": "payment" }, { "id": 2, "type": "column", "value": "amount" }, { "id": 7, "type": "value", "value": "SMITH" }, { "id": 5, "type": "value", "value": "MARY" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "B-VALUE", "O", "B-TABLE", "O", "O", "O", "O" ]
91
news_report
spider:train_spider.json:2804
What are the nationalities and ages of journalists?
SELECT Nationality , Age FROM journalist
[ "What", "are", "the", "nationalities", "and", "ages", "of", "journalists", "?" ]
[ { "id": 1, "type": "column", "value": "nationality" }, { "id": 0, "type": "table", "value": "journalist" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "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": [] }, { "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", "B-TABLE", "O" ]
92
university_rank
bird:test.json:1800
What is the name and citation point of the unversities with the top 3 reputation points?
SELECT T1.University_Name , T2.Citation_point FROM University AS T1 JOIN Overall_ranking AS T2 ON T1.university_id = T2.university_id ORDER BY T2.Reputation_point DESC LIMIT 3
[ "What", "is", "the", "name", "and", "citation", "point", "of", "the", "unversities", "with", "the", "top", "3", "reputation", "points", "?" ]
[ { "id": 4, "type": "column", "value": "reputation_point" }, { "id": 0, "type": "column", "value": "university_name" }, { "id": 3, "type": "table", "value": "overall_ranking" }, { "id": 1, "type": "column", "value": "citation_point" }, { "id": 5, "type": "column", "value": "university_id" }, { "id": 2, "type": "table", "value": "university" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
93
bike_1
spider:train_spider.json:140
What is the latitude, longitude, and city of the station from which the trip with smallest duration started?
SELECT T1.lat , T1.long , T1.city FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id ORDER BY T2.duration LIMIT 1
[ "What", "is", "the", "latitude", ",", "longitude", ",", "and", "city", "of", "the", "station", "from", "which", "the", "trip", "with", "smallest", "duration", "started", "?" ]
[ { "id": 7, "type": "column", "value": "start_station_id" }, { "id": 5, "type": "column", "value": "duration" }, { "id": 3, "type": "table", "value": "station" }, { "id": 1, "type": "column", "value": "long" }, { "id": 2, "type": "column", "value": "city" }, { "id": 4, "type": "table", "value": "trip" }, { "id": 0, "type": "column", "value": "lat" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O" ]
94
card_games
bird:dev.json:387
What are the cards for set OGW? State the colour for these cards.
SELECT id, colors FROM cards WHERE id IN ( SELECT id FROM set_translations WHERE setCode = 'OGW' )
[ "What", "are", "the", "cards", "for", "set", "OGW", "?", "State", "the", "colour", "for", "these", "cards", "." ]
[ { "id": 3, "type": "table", "value": "set_translations" }, { "id": 4, "type": "column", "value": "setcode" }, { "id": 2, "type": "column", "value": "colors" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 5, "type": "value", "value": "OGW" }, { "id": 1, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
95
card_games
bird:dev.json:407
Lists all types of cards in German.
SELECT T1.subtypes, T1.supertypes FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'German' AND T1.subtypes IS NOT NULL AND T1.supertypes IS NOT NULL
[ "Lists", "all", "types", "of", "cards", "in", "German", "." ]
[ { "id": 3, "type": "table", "value": "foreign_data" }, { "id": 1, "type": "column", "value": "supertypes" }, { "id": 0, "type": "column", "value": "subtypes" }, { "id": 5, "type": "column", "value": "language" }, { "id": 6, "type": "value", "value": "German" }, { "id": 2, "type": "table", "value": "cards" }, { "id": 4, "type": "column", "value": "uuid" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "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": [ 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", "B-COLUMN", "O", "B-TABLE", "O", "B-VALUE", "O" ]
97
shakespeare
bird:train.json:2995
What are the descriptions of the short chapters?
SELECT DISTINCT T2.Description FROM paragraphs AS T1 INNER JOIN chapters AS T2 ON T1.chapter_id = T2.id WHERE T1.ParagraphNum < 150
[ "What", "are", "the", "descriptions", "of", "the", "short", "chapters", "?" ]
[ { "id": 3, "type": "column", "value": "paragraphnum" }, { "id": 0, "type": "column", "value": "description" }, { "id": 1, "type": "table", "value": "paragraphs" }, { "id": 5, "type": "column", "value": "chapter_id" }, { "id": 2, "type": "table", "value": "chapters" }, { "id": 4, "type": "value", "value": "150" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
98
tracking_grants_for_research
spider:train_spider.json:4321
What are the different grant amounts for documents sent before '1986-08-26 20:49:27' and after the grant ended on '1989-03-16 18:27:16'?
SELECT T1.grant_amount FROM Grants AS T1 JOIN Documents AS T2 ON T1.grant_id = T2.grant_id WHERE T2.sent_date < '1986-08-26 20:49:27' INTERSECT SELECT grant_amount FROM grants WHERE grant_end_date > '1989-03-16 18:27:16'
[ "What", "are", "the", "different", "grant", "amounts", "for", "documents", "sent", "before", "'", "1986", "-", "08", "-", "26", "20:49:27", "'", "and", "after", "the", "grant", "ended", "on", "'", "1989", "-", "03", "-", "16", "18:27:16", "'", "?" ]
[ { "id": 4, "type": "value", "value": "1986-08-26 20:49:27" }, { "id": 6, "type": "value", "value": "1989-03-16 18:27:16" }, { "id": 5, "type": "column", "value": "grant_end_date" }, { "id": 1, "type": "column", "value": "grant_amount" }, { "id": 2, "type": "table", "value": "documents" }, { "id": 3, "type": "column", "value": "sent_date" }, { "id": 7, "type": "column", "value": "grant_id" }, { "id": 0, "type": "table", "value": "grants" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
99
retails
bird:train.json:6698
Customer No.129301 made an order on 1996/7/27, what was the delivery time for the first part of that order?
SELECT JULIANDAY(T2.l_receiptdate) - JULIANDAY(T2.l_commitdate) FROM orders AS T1 INNER JOIN lineitem AS T2 ON T1.o_orderkey = T2.l_orderkey WHERE T1.o_custkey = '129301' AND T1.o_orderdate = '1996-07-27'
[ "Customer", "No.129301", "made", "an", "order", "on", "1996/7/27", ",", "what", "was", "the", "delivery", "time", "for", "the", "first", "part", "of", "that", "order", "?" ]
[ { "id": 8, "type": "column", "value": "l_receiptdate" }, { "id": 9, "type": "column", "value": "l_commitdate" }, { "id": 6, "type": "column", "value": "o_orderdate" }, { "id": 2, "type": "column", "value": "o_orderkey" }, { "id": 3, "type": "column", "value": "l_orderkey" }, { "id": 7, "type": "value", "value": "1996-07-27" }, { "id": 4, "type": "column", "value": "o_custkey" }, { "id": 1, "type": "table", "value": "lineitem" }, { "id": 0, "type": "table", "value": "orders" }, { "id": 5, "type": "value", "value": "129301" } ]
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[ "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
100
culture_company
spider:train_spider.json:6974
Show all book categories and the number of books in each category.
SELECT category , count(*) FROM book_club GROUP BY category
[ "Show", "all", "book", "categories", "and", "the", "number", "of", "books", "in", "each", "category", "." ]
[ { "id": 0, "type": "table", "value": "book_club" }, { "id": 1, "type": "column", "value": "category" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
101
european_football_2
bird:dev.json:1047
What is the football player Francois Affolter header's finishing rate on 18/09/2014?
SELECT t2.heading_accuracy FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id WHERE t1.player_name = 'Francois Affolter' AND SUBSTR(t2.`date`, 1, 10) = '2014-09-18'
[ "What", "is", "the", "football", "player", "Francois", "Affolter", "header", "'s", "finishing", "rate", "on", "18/09/2014", "?" ]
[ { "id": 2, "type": "table", "value": "player_attributes" }, { "id": 5, "type": "value", "value": "Francois Affolter" }, { "id": 0, "type": "column", "value": "heading_accuracy" }, { "id": 3, "type": "column", "value": "player_api_id" }, { "id": 4, "type": "column", "value": "player_name" }, { "id": 6, "type": "value", "value": "2014-09-18" }, { "id": 1, "type": "table", "value": "player" }, { "id": 7, "type": "column", "value": "date" }, { "id": 9, "type": "value", "value": "10" }, { "id": 8, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
102
art_1
bird:test.json:1281
What are the locations that have paintings in the mediums of on panels and on canvas?
SELECT DISTINCT LOCATION FROM paintings WHERE mediumOn = "panel" INTERSECT SELECT DISTINCT LOCATION FROM paintings WHERE mediumOn = "canvas"
[ "What", "are", "the", "locations", "that", "have", "paintings", "in", "the", "mediums", "of", "on", "panels", "and", "on", "canvas", "?" ]
[ { "id": 0, "type": "table", "value": "paintings" }, { "id": 1, "type": "column", "value": "location" }, { "id": 2, "type": "column", "value": "mediumon" }, { "id": 4, "type": "column", "value": "canvas" }, { "id": 3, "type": "column", "value": "panel" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
103
planet_1
bird:test.json:1860
What position does Amy Wong have?
SELECT POSITION FROM Employee WHERE Name = "Amy Wong";
[ "What", "position", "does", "Amy", "Wong", "have", "?" ]
[ { "id": 0, "type": "table", "value": "employee" }, { "id": 1, "type": "column", "value": "position" }, { "id": 3, "type": "column", "value": "Amy Wong" }, { "id": 2, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3, 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", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
104
candidate_poll
spider:train_spider.json:2420
what are the names of people who did not participate in the candidate election.
SELECT name FROM people WHERE people_id NOT IN (SELECT people_id FROM candidate)
[ "what", "are", "the", "names", "of", "people", "who", "did", "not", "participate", "in", "the", "candidate", "election", "." ]
[ { "id": 2, "type": "column", "value": "people_id" }, { "id": 3, "type": "table", "value": "candidate" }, { "id": 0, "type": "table", "value": "people" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O" ]
105
student_assessment
spider:train_spider.json:63
What are the ids of every student who has never attended a course?
SELECT student_id FROM students WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance)
[ "What", "are", "the", " ", "ids", "of", "every", "student", "who", "has", "never", "attended", "a", "course", "?" ]
[ { "id": 2, "type": "table", "value": "student_course_attendance" }, { "id": 1, "type": "column", "value": "student_id" }, { "id": 0, "type": "table", "value": "students" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8, 9, 10, 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "I-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O" ]
107
customer_complaints
spider:train_spider.json:5807
What are lines 1 and 2 of the addressed of the customer with the email "[email protected]"?
SELECT address_line_1 , address_line_2 FROM customers WHERE email_address = "[email protected]"
[ "What", "are", "lines", "1", "and", "2", "of", "the", "addressed", "of", "the", "customer", "with", "the", "email", "\"", "[email protected]", "\"", "?" ]
[ { "id": 4, "type": "column", "value": "[email protected]" }, { "id": 1, "type": "column", "value": "address_line_1" }, { "id": 2, "type": "column", "value": "address_line_2" }, { "id": 3, "type": "column", "value": "email_address" }, { "id": 0, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "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", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
108
county_public_safety
spider:train_spider.json:2533
Count the number of countries.
SELECT count(*) FROM county_public_safety
[ "Count", "the", "number", "of", "countries", "." ]
[ { "id": 0, "type": "table", "value": "county_public_safety" } ]
[ { "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" ]
109
world
bird:train.json:7839
Who is the head of the state where the most crowded city belongs?
SELECT T1.HeadOfState FROM Country AS T1 INNER JOIN City AS T2 ON T1.Code = T2.CountryCode ORDER BY T2.Population DESC LIMIT 1
[ "Who", "is", "the", "head", "of", "the", "state", "where", "the", "most", "crowded", "city", "belongs", "?" ]
[ { "id": 0, "type": "column", "value": "headofstate" }, { "id": 5, "type": "column", "value": "countrycode" }, { "id": 3, "type": "column", "value": "population" }, { "id": 1, "type": "table", "value": "country" }, { "id": 2, "type": "table", "value": "city" }, { "id": 4, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4, 5, 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O" ]