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15,205
california_schools
bird:dev.json:82
What is the grade span offered in the school with the highest longitude?
SELECT GSoffered FROM schools ORDER BY ABS(longitude) DESC LIMIT 1
[ "What", "is", "the", "grade", "span", "offered", "in", "the", "school", "with", "the", "highest", "longitude", "?" ]
[ { "id": 1, "type": "column", "value": "gsoffered" }, { "id": 2, "type": "column", "value": "longitude" }, { "id": 0, "type": "table", "value": "schools" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
15,206
european_football_2
bird:dev.json:1107
When was the first time did Kevin Constant have his highest crossing score? Give the date.
SELECT `date` FROM ( SELECT t2.crossing, t2.`date` FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_fifa_api_id = t2.player_fifa_api_id WHERE t1.player_name = 'Kevin Constant' ORDER BY t2.crossing DESC) ORDER BY date DESC LIMIT 1
[ "When", "was", "the", "first", "time", "did", "Kevin", "Constant", "have", "his", "highest", "crossing", "score", "?", "Give", "the", "date", "." ]
[ { "id": 6, "type": "column", "value": "player_fifa_api_id" }, { "id": 3, "type": "table", "value": "player_attributes" }, { "id": 5, "type": "value", "value": "Kevin Constant" }, { "id": 4, "type": "column", "value": "player_name" }, { "id": 1, "type": "column", "value": "crossing" }, { "id": 2, "type": "table", "value": "player" }, { "id": 0, "type": "column", "value": "date" } ]
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[ "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,207
book_1
bird:test.json:558
What are the names of clients who have never made an order?
SELECT name FROM Client EXCEPT SELECT T1.name FROM Client AS T1 JOIN Orders AS T2 ON T1.idClient = T2.idClient
[ "What", "are", "the", "names", "of", "clients", "who", "have", "never", "made", "an", "order", "?" ]
[ { "id": 3, "type": "column", "value": "idclient" }, { "id": 0, "type": "table", "value": "client" }, { "id": 2, "type": "table", "value": "orders" }, { "id": 1, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,208
scientist_1
spider:train_spider.json:6487
Find the total hours of the projects that scientists named Michael Rogers or Carol Smith are assigned to.
SELECT sum(T2.hours) FROM assignedto AS T1 JOIN projects AS T2 ON T1.project = T2.code JOIN scientists AS T3 ON T1.scientist = T3.SSN WHERE T3.name = 'Michael Rogers' OR T3.name = 'Carol Smith'
[ "Find", "the", "total", "hours", "of", "the", "projects", "that", "scientists", "named", "Michael", "Rogers", "or", "Carol", "Smith", "are", "assigned", "to", "." ]
[ { "id": 7, "type": "value", "value": "Michael Rogers" }, { "id": 8, "type": "value", "value": "Carol Smith" }, { "id": 0, "type": "table", "value": "scientists" }, { "id": 2, "type": "table", "value": "assignedto" }, { "id": 4, "type": "column", "value": "scientist" }, { "id": 3, "type": "table", "value": "projects" }, { "id": 9, "type": "column", "value": "project" }, { "id": 1, "type": "column", "value": "hours" }, { "id": 6, "type": "column", "value": "name" }, { "id": 10, "type": "column", "value": "code" }, { "id": 5, "type": "column", "value": "ssn" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "B-VALUE", "I-VALUE", "O", "B-VALUE", "I-VALUE", "O", "B-TABLE", "I-TABLE", "O" ]
15,209
behavior_monitoring
spider:train_spider.json:3098
Find the maximum and minimum monthly rental for all student addresses.
SELECT max(monthly_rental) , min(monthly_rental) FROM Student_Addresses
[ "Find", "the", "maximum", "and", "minimum", "monthly", "rental", "for", "all", "student", "addresses", "." ]
[ { "id": 0, "type": "table", "value": "student_addresses" }, { "id": 1, "type": "column", "value": "monthly_rental" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "O" ]
15,210
game_1
spider:train_spider.json:6022
What are the ids of all students who don't play sports?
SELECT StuID FROM Student EXCEPT SELECT StuID FROM Sportsinfo
[ "What", "are", "the", "ids", "of", "all", "students", "who", "do", "n't", "play", "sports", "?" ]
[ { "id": 1, "type": "table", "value": "sportsinfo" }, { "id": 0, "type": "table", "value": "student" }, { "id": 2, "type": "column", "value": "stuid" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
15,211
image_and_language
bird:train.json:7577
Based on image 5, what is the percentage of images that belong windows object class?
SELECT CAST(COUNT(T1.OBJ_SAMPLE_ID) AS REAL) * 100 / COUNT(CASE WHEN T1.IMG_ID = 5 THEN 1 ELSE 0 END) FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T2.OBJ_CLASS = 'windows'
[ "Based", "on", "image", "5", ",", "what", "is", "the", "percentage", "of", "images", "that", "belong", "windows", "object", "class", "?" ]
[ { "id": 7, "type": "column", "value": "obj_sample_id" }, { "id": 4, "type": "column", "value": "obj_class_id" }, { "id": 1, "type": "table", "value": "obj_classes" }, { "id": 2, "type": "column", "value": "obj_class" }, { "id": 0, "type": "table", "value": "img_obj" }, { "id": 3, "type": "value", "value": "windows" }, { "id": 9, "type": "column", "value": "img_id" }, { "id": 5, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" }, { "id": 10, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O" ]
15,212
movie_platform
bird:train.json:77
Among the users who are trailists when rating the movie "When Will I Be Loved", how many of them have rated "1" on the movie?
SELECT COUNT(T1.user_id) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_title = 'When Will I Be Loved' AND T1.rating_score = 1 AND T1.user_trialist = 1
[ "Among", "the", "users", "who", "are", "trailists", "when", "rating", "the", "movie", "\"", "When", "Will", "I", "Be", "Loved", "\"", ",", "how", "many", "of", "them", "have", "rated", "\"", "1", "\"", "on", "the", "movie", "?" ]
[ { "id": 5, "type": "value", "value": "When Will I Be Loved" }, { "id": 8, "type": "column", "value": "user_trialist" }, { "id": 6, "type": "column", "value": "rating_score" }, { "id": 4, "type": "column", "value": "movie_title" }, { "id": 3, "type": "column", "value": "movie_id" }, { "id": 0, "type": "table", "value": "ratings" }, { "id": 2, "type": "column", "value": "user_id" }, { "id": 1, "type": "table", "value": "movies" }, { "id": 7, "type": "value", "value": "1" } ]
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15,213
company_office
spider:train_spider.json:4562
For each company, return the company name and the name of the building its office is located in.
SELECT T3.name , T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id
[ "For", "each", "company", ",", "return", "the", "company", "name", "and", "the", "name", "of", "the", "building", "its", "office", "is", "located", "in", "." ]
[ { "id": 2, "type": "table", "value": "office_locations" }, { "id": 6, "type": "column", "value": "building_id" }, { "id": 4, "type": "column", "value": "company_id" }, { "id": 1, "type": "table", "value": "companies" }, { "id": 3, "type": "table", "value": "buildings" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "I-TABLE", "I-TABLE", "I-TABLE", "O" ]
15,214
bike_share_1
bird:train.json:9064
Please list the starting stations of the bike trips made on a day with a max humidity over 80 in 2013 in the area where the zip code is 94107.
SELECT DISTINCT T1.start_station_name FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE SUBSTR(CAST(T2.date AS TEXT), -4) = '2013' AND T2.zip_code = 94107 AND T2.max_temperature_f > 80
[ "Please", "list", "the", "starting", "stations", "of", "the", "bike", "trips", "made", "on", "a", "day", "with", "a", "max", "humidity", "over", "80", "in", "2013", "in", "the", "area", "where", "the", "zip", "code", "is", "94107", "." ]
[ { "id": 0, "type": "column", "value": "start_station_name" }, { "id": 6, "type": "column", "value": "max_temperature_f" }, { "id": 3, "type": "column", "value": "zip_code" }, { "id": 2, "type": "table", "value": "weather" }, { "id": 5, "type": "value", "value": "94107" }, { "id": 1, "type": "table", "value": "trip" }, { "id": 4, "type": "value", "value": "2013" }, { "id": 9, "type": "column", "value": "date" }, { "id": 7, "type": "value", "value": "80" }, { "id": 8, "type": "value", "value": "-4" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
15,215
university
bird:train.json:8007
What is the university ID of the university with the largest student staff ratio?
SELECT university_id FROM university_year ORDER BY student_staff_ratio DESC LIMIT 1
[ "What", "is", "the", "university", "ID", "of", "the", "university", "with", "the", "largest", "student", "staff", "ratio", "?" ]
[ { "id": 2, "type": "column", "value": "student_staff_ratio" }, { "id": 0, "type": "table", "value": "university_year" }, { "id": 1, "type": "column", "value": "university_id" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
15,216
books
bird:train.json:5951
How many orders were delivered in 2021?
SELECT COUNT(*) FROM order_status AS T1 INNER JOIN order_history AS T2 ON T1.status_id = T2.status_id WHERE T1.status_value = 'Delivered' AND STRFTIME('%Y', T2.status_date) = '2021'
[ "How", "many", "orders", "were", "delivered", "in", "2021", "?" ]
[ { "id": 1, "type": "table", "value": "order_history" }, { "id": 0, "type": "table", "value": "order_status" }, { "id": 3, "type": "column", "value": "status_value" }, { "id": 7, "type": "column", "value": "status_date" }, { "id": 2, "type": "column", "value": "status_id" }, { "id": 4, "type": "value", "value": "Delivered" }, { "id": 5, "type": "value", "value": "2021" }, { "id": 6, "type": "value", "value": "%Y" } ]
[ { "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": [ 4 ] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
15,217
bike_1
spider:train_spider.json:195
Find all the zip codes in which the max dew point have never reached 70.
SELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70
[ "Find", "all", "the", "zip", "codes", "in", "which", "the", "max", "dew", "point", "have", "never", "reached", "70", "." ]
[ { "id": 2, "type": "column", "value": "max_dew_point_f" }, { "id": 1, "type": "column", "value": "zip_code" }, { "id": 0, "type": "table", "value": "weather" }, { "id": 3, "type": "value", "value": "70" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
15,218
video_games
bird:train.json:3391
Mention the genre of the 2Xtreme.
SELECT T2.id FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T1.game_name = '2Xtreme'
[ "Mention", "the", "genre", "of", "the", "2Xtreme", "." ]
[ { "id": 3, "type": "column", "value": "game_name" }, { "id": 5, "type": "column", "value": "genre_id" }, { "id": 4, "type": "value", "value": "2Xtreme" }, { "id": 2, "type": "table", "value": "genre" }, { "id": 1, "type": "table", "value": "game" }, { "id": 0, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
15,220
aan_1
bird:test.json:982
What are the titles and paper ids for papers which were affiliated with both Stanford and Columbia University?
SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T3.name LIKE "Stanford University" INTERSECT SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T3.name LIKE "Columbia University"
[ "What", "are", "the", "titles", "and", "paper", "ids", "for", "papers", "which", "were", "affiliated", "with", "both", "Stanford", "and", "Columbia", "University", "?" ]
[ { "id": 4, "type": "column", "value": "Stanford University" }, { "id": 5, "type": "column", "value": "Columbia University" }, { "id": 8, "type": "column", "value": "affiliation_id" }, { "id": 2, "type": "table", "value": "affiliation" }, { "id": 7, "type": "table", "value": "author_list" }, { "id": 1, "type": "column", "value": "paper_id" }, { "id": 0, "type": "column", "value": "title" }, { "id": 6, "type": "table", "value": "paper" }, { "id": 3, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 14, 15 ] }, { "entity_id": 5, "token_idxs": [ 16, 17 ] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O" ]
15,223
beer_factory
bird:train.json:5256
Which city does the customer who finished transaction no.103545 live in?
SELECT T1.City FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.TransactionID = 103545
[ "Which", "city", "does", "the", "customer", "who", "finished", "transaction", "no.103545", "live", "in", "?" ]
[ { "id": 3, "type": "column", "value": "transactionid" }, { "id": 2, "type": "table", "value": "transaction" }, { "id": 5, "type": "column", "value": "customerid" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 4, "type": "value", "value": "103545" }, { "id": 0, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-VALUE", "O", "O", "O" ]
15,224
authors
bird:train.json:3530
In year 1999, list the titles and conference's short name of paper authored by someone named "Philip".
SELECT T1.Title, T3.ShortName FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId INNER JOIN Conference AS T3 ON T1.ConferenceId = T3.Id WHERE T1.Year = 1999 AND T2.Name LIKE 'Philip%'
[ "In", "year", "1999", ",", "list", "the", "titles", "and", "conference", "'s", "short", "name", "of", "paper", "authored", "by", "someone", "named", "\"", "Philip", "\"", "." ]
[ { "id": 5, "type": "column", "value": "conferenceid" }, { "id": 4, "type": "table", "value": "paperauthor" }, { "id": 2, "type": "table", "value": "conference" }, { "id": 1, "type": "column", "value": "shortname" }, { "id": 10, "type": "value", "value": "Philip%" }, { "id": 11, "type": "column", "value": "paperid" }, { "id": 0, "type": "column", "value": "title" }, { "id": 3, "type": "table", "value": "paper" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "1999" }, { "id": 9, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 13 ] }, { "entity_id": 4, "token_idxs": [ 14 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 1 ] }, { "entity_id": 8, "token_idxs": [ 2 ] }, { "entity_id": 9, "token_idxs": [ 11 ] }, { "entity_id": 10, "token_idxs": [ 19 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "B-COLUMN", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,225
software_company
bird:train.json:8567
List the level of education and income of customers ages from 30 to 55 with a true response.
SELECT T1.EDUCATIONNUM, T3.INCOME_K FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.age >= 30 AND T1.age <= 55 AND T2.RESPONSE = 'true'
[ "List", "the", "level", "of", "education", "and", "income", "of", "customers", "ages", "from", "30", "to", "55", "with", "a", "true", "response", "." ]
[ { "id": 0, "type": "column", "value": "educationnum" }, { "id": 4, "type": "table", "value": "mailings1_2" }, { "id": 3, "type": "table", "value": "customers" }, { "id": 1, "type": "column", "value": "income_k" }, { "id": 9, "type": "column", "value": "response" }, { "id": 2, "type": "table", "value": "demog" }, { "id": 5, "type": "column", "value": "geoid" }, { "id": 12, "type": "column", "value": "refid" }, { "id": 10, "type": "value", "value": "true" }, { "id": 6, "type": "column", "value": "age" }, { "id": 7, "type": "value", "value": "30" }, { "id": 8, "type": "value", "value": "55" }, { "id": 11, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 9 ] }, { "entity_id": 7, "token_idxs": [ 11 ] }, { "entity_id": 8, "token_idxs": [ 13 ] }, { "entity_id": 9, "token_idxs": [ 17 ] }, { "entity_id": 10, "token_idxs": [ 16 ] }, { "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", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,227
real_estate_rentals
bird:test.json:1442
List the first name, middle name and last name, and log in name of all the seller users, whose seller value is 1.
SELECT first_name , middle_name , last_name , login_name FROM Users WHERE is_seller = 1;
[ "List", "the", "first", "name", ",", "middle", "name", "and", "last", "name", ",", "and", "log", "in", "name", "of", "all", "the", "seller", "users", ",", "whose", "seller", "value", "is", "1", "." ]
[ { "id": 2, "type": "column", "value": "middle_name" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 4, "type": "column", "value": "login_name" }, { "id": 3, "type": "column", "value": "last_name" }, { "id": 5, "type": "column", "value": "is_seller" }, { "id": 0, "type": "table", "value": "users" }, { "id": 6, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 19 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 8, 9 ] }, { "entity_id": 4, "token_idxs": [ 12, 13, 14 ] }, { "entity_id": 5, "token_idxs": [ 18 ] }, { "entity_id": 6, "token_idxs": [ 25 ] }, { "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", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
15,228
book_publishing_company
bird:train.json:235
Find the difference between the average royalty of titles published by US and non US publishers?
SELECT (CAST(SUM(CASE WHEN T2.country = 'USA' THEN T1.royalty ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.country = 'USA' THEN 1 ELSE 0 END)) - (CAST(SUM(CASE WHEN T2.country != 'USA' THEN T1.royalty ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.country != 'USA' THEN 1 ELSE 0 END)) FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN roysched AS T3 ON T1.title_id = T3.title_id
[ "Find", "the", "difference", "between", "the", "average", "royalty", "of", "titles", "published", "by", "US", "and", "non", "US", "publishers", "?" ]
[ { "id": 2, "type": "table", "value": "publishers" }, { "id": 0, "type": "table", "value": "roysched" }, { "id": 3, "type": "column", "value": "title_id" }, { "id": 7, "type": "column", "value": "royalty" }, { "id": 8, "type": "column", "value": "country" }, { "id": 1, "type": "table", "value": "titles" }, { "id": 4, "type": "column", "value": "pub_id" }, { "id": 9, "type": "value", "value": "USA" }, { "id": 5, "type": "value", "value": "0" }, { "id": 6, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 6 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 11 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O" ]
15,229
apartment_rentals
spider:train_spider.json:1257
What are the top three apartment types in terms of the average room count? Give me the
SELECT apt_type_code FROM Apartments GROUP BY apt_type_code ORDER BY avg(room_count) DESC LIMIT 3
[ "What", "are", "the", "top", "three", "apartment", "types", "in", "terms", "of", "the", "average", "room", "count", "?", "Give", "me", "the" ]
[ { "id": 1, "type": "column", "value": "apt_type_code" }, { "id": 0, "type": "table", "value": "apartments" }, { "id": 2, "type": "column", "value": "room_count" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 12, 13 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
15,230
soccer_3
bird:test.json:26
Please show the most common manufacturer of clubs.
SELECT Manufacturer FROM club GROUP BY Manufacturer ORDER BY COUNT(*) DESC LIMIT 1
[ "Please", "show", "the", "most", "common", "manufacturer", "of", "clubs", "." ]
[ { "id": 1, "type": "column", "value": "manufacturer" }, { "id": 0, "type": "table", "value": "club" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
15,231
music_platform_2
bird:train.json:7984
Please list the titles of the podcasts for which the author whose ID is F7E5A318989779D has written a review.
SELECT T2.title FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T2.author_id = 'F7E5A318989779D'
[ "Please", "list", "the", "titles", "of", "the", "podcasts", "for", "which", "the", "author", "whose", "ID", "is", "F7E5A318989779D", "has", "written", "a", "review", "." ]
[ { "id": 4, "type": "value", "value": "F7E5A318989779D" }, { "id": 5, "type": "column", "value": "podcast_id" }, { "id": 3, "type": "column", "value": "author_id" }, { "id": 1, "type": "table", "value": "podcasts" }, { "id": 2, "type": "table", "value": "reviews" }, { "id": 0, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 18 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 14 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O" ]
15,232
movie_3
bird:train.json:9310
Who is the manager of the store with the largest collection of films?
SELECT T.first_name, T.last_name FROM ( SELECT T3.first_name, T3.last_name, COUNT(T1.film_id) AS num FROM inventory AS T1 INNER JOIN store AS T2 ON T1.store_id = T2.store_id INNER JOIN staff AS T3 ON T2.manager_staff_id = T3.staff_id GROUP BY T3.first_name, T3.last_name ) AS T ORDER BY T.num DESC LIMIT 1
[ "Who", "is", "the", "manager", "of", "the", "store", "with", "the", "largest", "collection", "of", "films", "?" ]
[ { "id": 7, "type": "column", "value": "manager_staff_id" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 5, "type": "table", "value": "inventory" }, { "id": 8, "type": "column", "value": "staff_id" }, { "id": 9, "type": "column", "value": "store_id" }, { "id": 4, "type": "column", "value": "film_id" }, { "id": 3, "type": "table", "value": "staff" }, { "id": 6, "type": "table", "value": "store" }, { "id": 2, "type": "column", "value": "num" } ]
[ { "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": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 6 ] }, { "entity_id": 7, "token_idxs": [ 3, 4 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,233
video_games
bird:train.json:3490
What is the name of the company that produced the game titled Adventure Time: Explore the Dungeon Because I Don't Know!?
SELECT T3.publisher_name FROM game AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.game_id INNER JOIN publisher AS T3 ON T2.publisher_id = T3.id WHERE T1.game_name = 'Adventure Time: Explore the Dungeon Because I Don''t Know!'
[ "What", "is", "the", "name", "of", "the", "company", "that", "produced", "the", "game", "titled", "Adventure", "Time", ":", "Explore", "the", "Dungeon", "Because", "I", "Do", "n't", "Know", "!", "?" ]
[ { "id": 3, "type": "value", "value": "Adventure Time: Explore the Dungeon Because I Don't Know!" }, { "id": 0, "type": "column", "value": "publisher_name" }, { "id": 5, "type": "table", "value": "game_publisher" }, { "id": 6, "type": "column", "value": "publisher_id" }, { "id": 1, "type": "table", "value": "publisher" }, { "id": 2, "type": "column", "value": "game_name" }, { "id": 8, "type": "column", "value": "game_id" }, { "id": 4, "type": "table", "value": "game" }, { "id": 7, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 1, 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23 ] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 19 ] }, { "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", "I-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
15,234
college_1
spider:train_spider.json:3269
What is the name of department where has the smallest number of professors?
SELECT T2.dept_name FROM professor AS T1 JOIN department AS T2 ON T1.dept_code = T2.dept_code GROUP BY T1.dept_code ORDER BY count(*) LIMIT 1
[ "What", "is", "the", "name", "of", "department", "where", "has", "the", "smallest", "number", "of", "professors", "?" ]
[ { "id": 3, "type": "table", "value": "department" }, { "id": 0, "type": "column", "value": "dept_code" }, { "id": 1, "type": "column", "value": "dept_name" }, { "id": 2, "type": "table", "value": "professor" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,236
art_1
bird:test.json:1246
What are the average height of paintings for different medium types?
SELECT avg(height_mm) , medium FROM paintings GROUP BY medium
[ "What", "are", "the", "average", "height", "of", "paintings", "for", "different", "medium", "types", "?" ]
[ { "id": 0, "type": "table", "value": "paintings" }, { "id": 2, "type": "column", "value": "height_mm" }, { "id": 1, "type": "column", "value": "medium" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O" ]
15,237
real_estate_rentals
bird:test.json:1468
List the last names and ids of users who have at least 2 properties and searched at most twice.
SELECT T1.last_name , T1.user_id FROM Users AS T1 JOIN User_Searches AS T2 ON T1.user_id = T2.user_id GROUP BY T1.user_id HAVING count(*) <= 2 INTERSECT SELECT T3.last_name , T3.user_id FROM Users AS T3 JOIN Properties AS T4 ON T3.user_id = T4.owner_user_id GROUP BY T3.user_id HAVING count(*) >= 2;
[ "List", "the", "last", "names", "and", "ids", "of", "users", "who", "have", "at", "least", "2", "properties", "and", "searched", "at", "most", "twice", "." ]
[ { "id": 3, "type": "table", "value": "user_searches" }, { "id": 6, "type": "column", "value": "owner_user_id" }, { "id": 5, "type": "table", "value": "properties" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 0, "type": "column", "value": "user_id" }, { "id": 2, "type": "table", "value": "users" }, { "id": 4, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O", "B-TABLE", "O", "O", "O", "O" ]
15,238
european_football_2
bird:dev.json:1140
What are Alexis Blin's sprint speed, agility, and acceleration scores?
SELECT sprint_speed, agility, acceleration FROM Player_Attributes WHERE player_api_id IN ( SELECT player_api_id FROM Player WHERE player_name = 'Alexis Blin' )
[ "What", "are", "Alexis", "Blin", "'s", "sprint", "speed", ",", "agility", ",", "and", "acceleration", "scores", "?" ]
[ { "id": 0, "type": "table", "value": "player_attributes" }, { "id": 4, "type": "column", "value": "player_api_id" }, { "id": 1, "type": "column", "value": "sprint_speed" }, { "id": 3, "type": "column", "value": "acceleration" }, { "id": 6, "type": "column", "value": "player_name" }, { "id": 7, "type": "value", "value": "Alexis Blin" }, { "id": 2, "type": "column", "value": "agility" }, { "id": 5, "type": "table", "value": "player" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 2, 3 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "I-VALUE", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
15,239
law_episode
bird:train.json:1342
What is the episode that has mafia keyword?
SELECT T1.episode FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T2.Keyword = 'mafia'
[ "What", "is", "the", "episode", "that", "has", "mafia", "keyword", "?" ]
[ { "id": 5, "type": "column", "value": "episode_id" }, { "id": 0, "type": "column", "value": "episode" }, { "id": 1, "type": "table", "value": "episode" }, { "id": 2, "type": "table", "value": "keyword" }, { "id": 3, "type": "column", "value": "keyword" }, { "id": 4, "type": "value", "value": "mafia" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 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", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,240
software_company
bird:train.json:8512
Please list the occupations of the customers with an education level of 11.
SELECT DISTINCT OCCUPATION FROM Customers WHERE EDUCATIONNUM = 11
[ "Please", "list", "the", "occupations", "of", "the", "customers", "with", "an", "education", "level", "of", "11", "." ]
[ { "id": 2, "type": "column", "value": "educationnum" }, { "id": 1, "type": "column", "value": "occupation" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 3, "type": "value", "value": "11" } ]
[ { "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": [] }, { "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-VALUE", "O" ]
15,241
car_retails
bird:train.json:1619
If Dragon Souveniers, Ltd. aren't satisfied with their order and want to send a complain e-mail, which e-mail address should they send to?
SELECT t2.email FROM customers AS t1 INNER JOIN employees AS t2 ON t1.salesRepEmployeeNumber = t2.employeeNumber WHERE t1.customerName = 'Dragon Souveniers, Ltd.'
[ "If", "Dragon", "Souveniers", ",", "Ltd.", "are", "n't", "satisfied", "with", "their", "order", "and", "want", "to", "send", "a", "complain", "e", "-", "mail", ",", "which", "e", "-", "mail", "address", "should", "they", "send", "to", "?" ]
[ { "id": 4, "type": "value", "value": "Dragon Souveniers, Ltd." }, { "id": 5, "type": "column", "value": "salesrepemployeenumber" }, { "id": 6, "type": "column", "value": "employeenumber" }, { "id": 3, "type": "column", "value": "customername" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "employees" }, { "id": 0, "type": "column", "value": "email" } ]
[ { "entity_id": 0, "token_idxs": [ 17, 18, 19 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 1, 2, 3, 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", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,242
beer_factory
bird:train.json:5287
Among the root beer purchased in 2014, what percentage were sold in cans?
SELECT CAST(COUNT(CASE WHEN ContainerType = 'Can' THEN RootBeerID ELSE NULL END) AS REAL) * 100 / COUNT(RootBeerID) FROM rootbeer WHERE PurchaseDate LIKE '2014%'
[ "Among", "the", "root", "beer", "purchased", "in", "2014", ",", "what", "percentage", "were", "sold", "in", "cans", "?" ]
[ { "id": 5, "type": "column", "value": "containertype" }, { "id": 1, "type": "column", "value": "purchasedate" }, { "id": 4, "type": "column", "value": "rootbeerid" }, { "id": 0, "type": "table", "value": "rootbeer" }, { "id": 2, "type": "value", "value": "2014%" }, { "id": 3, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "Can" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 13 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
15,243
cre_Students_Information_Systems
bird:test.json:482
What are the pairs of teachers and students who are in the same class? Give me the pairs of their details.
SELECT T1.teacher_details , T3.student_details FROM Teachers AS T1 JOIN Classes AS T2 ON T1.teacher_id = T2.teacher_id JOIN Students AS T3 ON T2.student_id = T3.student_id
[ "What", "are", "the", "pairs", "of", "teachers", "and", "students", "who", "are", "in", "the", "same", "class", "?", "Give", "me", "the", "pairs", "of", "their", "details", "." ]
[ { "id": 0, "type": "column", "value": "teacher_details" }, { "id": 1, "type": "column", "value": "student_details" }, { "id": 5, "type": "column", "value": "student_id" }, { "id": 6, "type": "column", "value": "teacher_id" }, { "id": 2, "type": "table", "value": "students" }, { "id": 3, "type": "table", "value": "teachers" }, { "id": 4, "type": "table", "value": "classes" } ]
[ { "entity_id": 0, "token_idxs": [ 20, 21 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,244
works_cycles
bird:train.json:7041
Which job title has the lowest pay?
SELECT T1.JobTitle FROM Employee AS T1 INNER JOIN EmployeePayHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID ORDER BY T2.Rate ASC LIMIT 1
[ "Which", "job", "title", "has", "the", "lowest", "pay", "?" ]
[ { "id": 2, "type": "table", "value": "employeepayhistory" }, { "id": 4, "type": "column", "value": "businessentityid" }, { "id": 0, "type": "column", "value": "jobtitle" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 3, "type": "column", "value": "rate" } ]
[ { "entity_id": 0, "token_idxs": [ 1, 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", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
15,245
world_development_indicators
bird:train.json:2219
What is the name of the country with the highest percentage of rural population in the overall total population? Indicate the rural population percentage of total population.
SELECT countryname, MAX(value) FROM indicators WHERE indicatorname = 'Rural population (% of total population)'
[ "What", "is", "the", "name", "of", "the", "country", "with", "the", "highest", "percentage", "of", "rural", "population", "in", "the", "overall", "total", "population", "?", "Indicate", "the", "rural", "population", "percentage", "of", "total", "population", "." ]
[ { "id": 3, "type": "value", "value": "Rural population (% of total population)" }, { "id": 2, "type": "column", "value": "indicatorname" }, { "id": 1, "type": "column", "value": "countryname" }, { "id": 0, "type": "table", "value": "indicators" }, { "id": 4, "type": "column", "value": "value" } ]
[ { "entity_id": 0, "token_idxs": [ 20 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 22, 23, 24, 25, 26, 27 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
15,246
card_games
bird:dev.json:437
Among black card borders, which card has full artwork?
SELECT id FROM cards WHERE borderColor = 'black' AND isFullArt = 1
[ "Among", "black", "card", "borders", ",", "which", "card", "has", "full", "artwork", "?" ]
[ { "id": 2, "type": "column", "value": "bordercolor" }, { "id": 4, "type": "column", "value": "isfullart" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 3, "type": "value", "value": "black" }, { "id": 1, "type": "column", "value": "id" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 1 ] }, { "entity_id": 4, "token_idxs": [ 8, 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,247
dorm_1
spider:train_spider.json:5682
Find the total capacity of all dorms.
SELECT sum(student_capacity) FROM dorm
[ "Find", "the", "total", "capacity", "of", "all", "dorms", "." ]
[ { "id": 1, "type": "column", "value": "student_capacity" }, { "id": 0, "type": "table", "value": "dorm" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 2, 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", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O" ]
15,248
bakery_1
bird:test.json:1545
Find all receipts which has the latest date. Also tell me that date.
SELECT ReceiptNumber , date FROM receipts WHERE date = (SELECT date FROM receipts ORDER BY date DESC LIMIT 1)
[ "Find", "all", "receipts", "which", "has", "the", "latest", "date", ".", "Also", "tell", "me", "that", "date", "." ]
[ { "id": 1, "type": "column", "value": "receiptnumber" }, { "id": 0, "type": "table", "value": "receipts" }, { "id": 2, "type": "column", "value": "date" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,249
gas_company
spider:train_spider.json:2015
How many gas station are opened between 2000 and 2005?
SELECT count(*) FROM gas_station WHERE open_year BETWEEN 2000 AND 2005
[ "How", "many", "gas", "station", "are", "opened", "between", "2000", "and", "2005", "?" ]
[ { "id": 0, "type": "table", "value": "gas_station" }, { "id": 1, "type": "column", "value": "open_year" }, { "id": 2, "type": "value", "value": "2000" }, { "id": 3, "type": "value", "value": "2005" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O" ]
15,251
cre_Students_Information_Systems
bird:test.json:448
List the amount and date of loan for the students who have two or more achievements.
SELECT amount_of_loan , date_of_loan FROM Student_Loans WHERE student_id IN ( SELECT student_id FROM Achievements GROUP BY student_id HAVING count(*) >= 2 )
[ "List", "the", "amount", "and", "date", "of", "loan", "for", "the", "students", "who", "have", "two", "or", "more", "achievements", "." ]
[ { "id": 1, "type": "column", "value": "amount_of_loan" }, { "id": 0, "type": "table", "value": "student_loans" }, { "id": 2, "type": "column", "value": "date_of_loan" }, { "id": 4, "type": "table", "value": "achievements" }, { "id": 3, "type": "column", "value": "student_id" }, { "id": 5, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "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", "B-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,252
ice_hockey_draft
bird:train.json:6988
What team did Niklas Eckerblom play in the 1997-1998 season?
SELECT T2.TEAM FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T2.SEASON = '1997-1998' AND T1.PlayerName = 'Niko Kapanen'
[ "What", "team", "did", "Niklas", "Eckerblom", "play", "in", "the", "1997", "-", "1998", "season", "?" ]
[ { "id": 2, "type": "table", "value": "seasonstatus" }, { "id": 7, "type": "value", "value": "Niko Kapanen" }, { "id": 1, "type": "table", "value": "playerinfo" }, { "id": 6, "type": "column", "value": "playername" }, { "id": 5, "type": "value", "value": "1997-1998" }, { "id": 3, "type": "column", "value": "eliteid" }, { "id": 4, "type": "column", "value": "season" }, { "id": 0, "type": "column", "value": "team" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "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, 9, 10 ] }, { "entity_id": 6, "token_idxs": [ 5, 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", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O" ]
15,253
soccer_2016
bird:train.json:1917
In what year did SP Narine win the Orange Cap?
SELECT T4.Season_Year, T4.Orange_Cap FROM Player AS T1 INNER JOIN Player_Match AS T2 ON T1.Player_Id = T2.Player_Id INNER JOIN Match AS T3 ON T2.Match_Id = T3.Match_Id INNER JOIN Season AS T4 ON T3.Season_Id = T4.Season_Id WHERE T1.Player_Name = 'SP Narine' GROUP BY T4.Season_Year, T4.Orange_Cap
[ "In", "what", "year", "did", "SP", "Narine", "win", "the", "Orange", "Cap", "?" ]
[ { "id": 8, "type": "table", "value": "player_match" }, { "id": 0, "type": "column", "value": "season_year" }, { "id": 3, "type": "column", "value": "player_name" }, { "id": 1, "type": "column", "value": "orange_cap" }, { "id": 4, "type": "value", "value": "SP Narine" }, { "id": 6, "type": "column", "value": "season_id" }, { "id": 10, "type": "column", "value": "player_id" }, { "id": 9, "type": "column", "value": "match_id" }, { "id": 2, "type": "table", "value": "season" }, { "id": 7, "type": "table", "value": "player" }, { "id": 5, "type": "table", "value": "match" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8, 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 4, 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 2 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 3 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "I-VALUE", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,254
soccer_2016
bird:train.json:1828
In which country do the majority of the players are from?
SELECT T1.Country_Name FROM Country AS T1 INNER JOIN Player AS T2 ON T1.Country_Id = T2.Country_Name GROUP BY T2.Country_Name ORDER BY COUNT(T2.Country_Name) DESC LIMIT 1
[ "In", "which", "country", "do", "the", "majority", "of", "the", "players", "are", "from", "?" ]
[ { "id": 0, "type": "column", "value": "country_name" }, { "id": 3, "type": "column", "value": "country_id" }, { "id": 1, "type": "table", "value": "country" }, { "id": 2, "type": "table", "value": "player" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
15,255
toxicology
bird:dev.json:337
List the element and bond type included in the molecule with molecule ID of TR002.
SELECT DISTINCT T1.element, T2.bond_type FROM atom AS T1 INNER JOIN bond AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.molecule_id = 'TR002'
[ "List", "the", "element", "and", "bond", "type", "included", "in", "the", "molecule", "with", "molecule", "ID", "of", "TR002", "." ]
[ { "id": 4, "type": "column", "value": "molecule_id" }, { "id": 1, "type": "column", "value": "bond_type" }, { "id": 0, "type": "column", "value": "element" }, { "id": 5, "type": "value", "value": "TR002" }, { "id": 2, "type": "table", "value": "atom" }, { "id": 3, "type": "table", "value": "bond" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 11, 12 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
15,256
wedding
spider:train_spider.json:1645
How many weddings are there in year 2016?
SELECT count(*) FROM wedding WHERE YEAR = 2016
[ "How", "many", "weddings", "are", "there", "in", "year", "2016", "?" ]
[ { "id": 0, "type": "table", "value": "wedding" }, { "id": 1, "type": "column", "value": "year" }, { "id": 2, "type": "value", "value": "2016" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
15,257
phone_market
spider:train_spider.json:1979
List the names of phones in ascending order of price.
SELECT Name FROM phone ORDER BY Price ASC
[ "List", "the", "names", "of", "phones", "in", "ascending", "order", "of", "price", "." ]
[ { "id": 0, "type": "table", "value": "phone" }, { "id": 2, "type": "column", "value": "price" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,258
food_inspection_2
bird:train.json:6233
How many restaurants failed the inspection in April 2010?
SELECT COUNT(DISTINCT T1.license_no) FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no WHERE strftime('%Y-%m', T2.inspection_date) = '2010-04' AND T1.facility_type = 'Restaurant' AND T2.results = 'Fail'
[ "How", "many", "restaurants", "failed", "the", "inspection", "in", "April", "2010", "?" ]
[ { "id": 9, "type": "column", "value": "inspection_date" }, { "id": 0, "type": "table", "value": "establishment" }, { "id": 4, "type": "column", "value": "facility_type" }, { "id": 1, "type": "table", "value": "inspection" }, { "id": 2, "type": "column", "value": "license_no" }, { "id": 5, "type": "value", "value": "Restaurant" }, { "id": 3, "type": "value", "value": "2010-04" }, { "id": 6, "type": "column", "value": "results" }, { "id": 8, "type": "value", "value": "%Y-%m" }, { "id": 7, "type": "value", "value": "Fail" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 2 ] }, { "entity_id": 7, "token_idxs": [ 3 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-VALUE", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
15,259
bakery_1
bird:test.json:1513
Find all the receipt numbers in which customer with last name LOGAN purchased Croissant.
SELECT T1.ReceiptNumber FROM receipts AS T1 JOIN items AS T2 ON T1.ReceiptNumber = T2.receipt JOIN goods AS T3 ON T2.item = T3.id JOIN customers AS T4 ON T4.Id = T1.CustomerId WHERE T3.food = "Croissant" AND T4.LastName = 'LOGAN'
[ "Find", "all", "the", "receipt", "numbers", "in", "which", "customer", "with", "last", "name", "LOGAN", "purchased", "Croissant", "." ]
[ { "id": 0, "type": "column", "value": "receiptnumber" }, { "id": 4, "type": "column", "value": "customerid" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 6, "type": "column", "value": "Croissant" }, { "id": 7, "type": "column", "value": "lastname" }, { "id": 9, "type": "table", "value": "receipts" }, { "id": 12, "type": "column", "value": "receipt" }, { "id": 2, "type": "table", "value": "goods" }, { "id": 8, "type": "value", "value": "LOGAN" }, { "id": 10, "type": "table", "value": "items" }, { "id": 5, "type": "column", "value": "food" }, { "id": 11, "type": "column", "value": "item" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "B-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O", "B-COLUMN", "O" ]
15,260
coinmarketcap
bird:train.json:6283
What is the name of the coin with the highest price?
SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.price = ( SELECT MAX(price) FROM historical )
[ "What", "is", "the", "name", "of", "the", "coin", "with", "the", "highest", "price", "?" ]
[ { "id": 2, "type": "table", "value": "historical" }, { "id": 5, "type": "column", "value": "coin_id" }, { "id": 1, "type": "table", "value": "coins" }, { "id": 3, "type": "column", "value": "price" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
15,261
simpson_episodes
bird:train.json:4208
What is the birth place of the cast or crew member who won the Best Voice-Over Performance in Online Film & Television Association in 2009?
SELECT T1.birth_place FROM Person AS T1 INNER JOIN Award AS T2 ON T1.name = T2.person WHERE T2.award = 'Best Voice-Over Performance' AND T2.organization = 'Online Film & Television Association' AND T2.year = 2009;
[ "What", "is", "the", "birth", "place", "of", "the", "cast", "or", "crew", "member", "who", "won", "the", "Best", "Voice", "-", "Over", "Performance", "in", "Online", "Film", "&", "Television", "Association", "in", "2009", "?" ]
[ { "id": 8, "type": "value", "value": "Online Film & Television Association" }, { "id": 6, "type": "value", "value": "Best Voice-Over Performance" }, { "id": 7, "type": "column", "value": "organization" }, { "id": 0, "type": "column", "value": "birth_place" }, { "id": 1, "type": "table", "value": "person" }, { "id": 4, "type": "column", "value": "person" }, { "id": 2, "type": "table", "value": "award" }, { "id": 5, "type": "column", "value": "award" }, { "id": 3, "type": "column", "value": "name" }, { "id": 9, "type": "column", "value": "year" }, { "id": 10, "type": "value", "value": "2009" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]
15,262
wrestler
spider:train_spider.json:1857
Give the names of wrestlers and their elimination moves.
SELECT T2.Name , T1.Elimination_Move FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID
[ "Give", "the", "names", "of", "wrestlers", "and", "their", "elimination", "moves", "." ]
[ { "id": 1, "type": "column", "value": "elimination_move" }, { "id": 2, "type": "table", "value": "elimination" }, { "id": 4, "type": "column", "value": "wrestler_id" }, { "id": 3, "type": "table", "value": "wrestler" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
15,263
railway
spider:train_spider.json:5646
Show different locations of railways along with the corresponding number of railways at each location.
SELECT LOCATION , COUNT(*) FROM railway GROUP BY LOCATION
[ "Show", "different", "locations", "of", "railways", "along", "with", "the", "corresponding", "number", "of", "railways", "at", "each", "location", "." ]
[ { "id": 1, "type": "column", "value": "location" }, { "id": 0, "type": "table", "value": "railway" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 14 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,264
movie_3
bird:train.json:9333
Which movie title has the lowest movie rental in the horror category?
SELECT T1.title FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T2.category_id = T3.category_id WHERE T3.`name` = 'Horror' ORDER BY T1.rental_rate LIMIT 1
[ "Which", "movie", "title", "has", "the", "lowest", "movie", "rental", "in", "the", "horror", "category", "?" ]
[ { "id": 6, "type": "table", "value": "film_category" }, { "id": 4, "type": "column", "value": "rental_rate" }, { "id": 7, "type": "column", "value": "category_id" }, { "id": 1, "type": "table", "value": "category" }, { "id": 8, "type": "column", "value": "film_id" }, { "id": 3, "type": "value", "value": "Horror" }, { "id": 0, "type": "column", "value": "title" }, { "id": 2, "type": "column", "value": "name" }, { "id": 5, "type": "table", "value": "film" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "B-TABLE", "O" ]
15,266
election
spider:train_spider.json:2784
Show the 3 counties with the smallest population.
SELECT County_name FROM county ORDER BY Population ASC LIMIT 3
[ "Show", "the", "3", "counties", "with", "the", "smallest", "population", "." ]
[ { "id": 1, "type": "column", "value": "county_name" }, { "id": 2, "type": "column", "value": "population" }, { "id": 0, "type": "table", "value": "county" } ]
[ { "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-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
15,267
network_2
spider:train_spider.json:4423
How old is the average person for each job?
SELECT avg(age) , job FROM Person GROUP BY job
[ "How", "old", "is", "the", "average", "person", "for", "each", "job", "?" ]
[ { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "job" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 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", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
15,268
election
spider:train_spider.json:2741
What are the maximum and minimum population of the counties?
SELECT max(Population) , min(Population) FROM county
[ "What", "are", "the", "maximum", "and", "minimum", "population", "of", "the", "counties", "?" ]
[ { "id": 1, "type": "column", "value": "population" }, { "id": 0, "type": "table", "value": "county" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
15,269
debit_card_specializing
bird:dev.json:1526
For the customer who paid 634.8 in 2012/8/25, what was the consumption decrease rate from Year 2012 to 2013?
SELECT CAST(SUM(IIF(SUBSTR(Date, 1, 4) = '2012', Consumption, 0)) - SUM(IIF(SUBSTR(Date, 1, 4) = '2013', Consumption, 0)) AS FLOAT) / SUM(IIF(SUBSTR(Date, 1, 4) = '2012', Consumption, 0)) FROM yearmonth WHERE CustomerID = ( SELECT T1.CustomerID FROM transactions_1k AS T1 INNER JOIN gasstations AS T2 ON T1.GasStationID = T2.GasStationID WHERE T1.Date = '2012-08-25' AND T1.Price = 634.8 )
[ "For", "the", "customer", "who", "paid", "634.8", "in", "2012/8/25", ",", "what", "was", "the", "consumption", "decrease", "rate", "from", "Year", "2012", "to", "2013", "?" ]
[ { "id": 4, "type": "table", "value": "transactions_1k" }, { "id": 7, "type": "column", "value": "gasstationid" }, { "id": 2, "type": "column", "value": "consumption" }, { "id": 5, "type": "table", "value": "gasstations" }, { "id": 1, "type": "column", "value": "customerid" }, { "id": 9, "type": "value", "value": "2012-08-25" }, { "id": 0, "type": "table", "value": "yearmonth" }, { "id": 10, "type": "column", "value": "price" }, { "id": 11, "type": "value", "value": "634.8" }, { "id": 6, "type": "value", "value": "2012" }, { "id": 8, "type": "column", "value": "date" }, { "id": 14, "type": "value", "value": "2013" }, { "id": 3, "type": "value", "value": "0" }, { "id": 12, "type": "value", "value": "1" }, { "id": 13, "type": "value", "value": "4" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "B-VALUE", "O", "B-VALUE", "O" ]
15,270
social_media
bird:train.json:846
From which city was the tweet with the most number of retweets posted?
SELECT T2.City FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID ORDER BY T1.RetweetCount DESC LIMIT 1
[ "From", "which", "city", "was", "the", "tweet", "with", "the", "most", "number", "of", "retweets", "posted", "?" ]
[ { "id": 3, "type": "column", "value": "retweetcount" }, { "id": 4, "type": "column", "value": "locationid" }, { "id": 2, "type": "table", "value": "location" }, { "id": 1, "type": "table", "value": "twitter" }, { "id": 0, "type": "column", "value": "city" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,271
menu
bird:train.json:5560
Among the menus with over 10 pages, how many of them have over 20 dishes?
SELECT COUNT(*) FROM Menu WHERE page_count > 10 AND dish_count > 20
[ "Among", "the", "menus", "with", "over", "10", "pages", ",", "how", "many", "of", "them", "have", "over", "20", "dishes", "?" ]
[ { "id": 1, "type": "column", "value": "page_count" }, { "id": 3, "type": "column", "value": "dish_count" }, { "id": 0, "type": "table", "value": "menu" }, { "id": 2, "type": "value", "value": "10" }, { "id": 4, "type": "value", "value": "20" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 14 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,272
entrepreneur
spider:train_spider.json:2272
Return the names of people, ordered by weight ascending.
SELECT Name FROM People ORDER BY Weight ASC
[ "Return", "the", "names", "of", "people", ",", "ordered", "by", "weight", "ascending", "." ]
[ { "id": 0, "type": "table", "value": "people" }, { "id": 2, "type": "column", "value": "weight" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,273
sports_competition
spider:train_spider.json:3347
What are the maximum and minimum number of silver medals for clubs.
SELECT max(Silver) , min(Silver) FROM club_rank
[ "What", "are", "the", "maximum", "and", "minimum", "number", "of", "silver", "medals", "for", "clubs", "." ]
[ { "id": 0, "type": "table", "value": "club_rank" }, { "id": 1, "type": "column", "value": "silver" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
15,274
aan_1
bird:test.json:973
List names and addresses for all affiliations.
SELECT DISTINCT name , address FROM Affiliation
[ "List", "names", "and", "addresses", "for", "all", "affiliations", "." ]
[ { "id": 0, "type": "table", "value": "affiliation" }, { "id": 2, "type": "column", "value": "address" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
15,275
sakila_1
spider:train_spider.json:2955
What are the full names of actors who had roles in more than 30 films?
SELECT T2.first_name , T2.last_name FROM film_actor AS T1 JOIN actor AS T2 ON T1.actor_id = T2.actor_id GROUP BY T2.actor_id HAVING count(*) > 30
[ "What", "are", "the", "full", "names", "of", "actors", "who", "had", "roles", "in", "more", "than", "30", "films", "?" ]
[ { "id": 1, "type": "column", "value": "first_name" }, { "id": 3, "type": "table", "value": "film_actor" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 0, "type": "column", "value": "actor_id" }, { "id": 4, "type": "table", "value": "actor" }, { "id": 5, "type": "value", "value": "30" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,276
movie_platform
bird:train.json:117
Give the number of followers for the user who posted the most lists.
SELECT SUM(T1.list_followers) FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id GROUP BY T1.user_id ORDER BY COUNT(T1.list_id) DESC LIMIT 1
[ "Give", "the", "number", "of", "followers", "for", "the", "user", "who", "posted", "the", "most", "lists", "." ]
[ { "id": 3, "type": "column", "value": "list_followers" }, { "id": 2, "type": "table", "value": "lists_users" }, { "id": 0, "type": "column", "value": "user_id" }, { "id": 4, "type": "column", "value": "list_id" }, { "id": 1, "type": "table", "value": "lists" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
15,277
food_inspection
bird:train.json:8837
List the names and business certificates of the eateries which got inspection score under 50.
SELECT T2.name, T2.business_id FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.score < 50
[ "List", "the", "names", "and", "business", "certificates", "of", "the", "eateries", "which", "got", "inspection", "score", "under", "50", "." ]
[ { "id": 1, "type": "column", "value": "business_id" }, { "id": 2, "type": "table", "value": "inspections" }, { "id": 3, "type": "table", "value": "businesses" }, { "id": 4, "type": "column", "value": "score" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "50" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
15,278
loan_1
spider:train_spider.json:3081
What is the total amount of money loaned by banks in New York state?
SELECT sum(T2.amount) FROM bank AS T1 JOIN loan AS T2 ON T1.branch_id = T2.branch_id WHERE T1.state = 'New York'
[ "What", "is", "the", "total", "amount", "of", "money", "loaned", "by", "banks", "in", "New", "York", "state", "?" ]
[ { "id": 5, "type": "column", "value": "branch_id" }, { "id": 3, "type": "value", "value": "New York" }, { "id": 4, "type": "column", "value": "amount" }, { "id": 2, "type": "column", "value": "state" }, { "id": 0, "type": "table", "value": "bank" }, { "id": 1, "type": "table", "value": "loan" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O" ]
15,279
chicago_crime
bird:train.json:8659
How many crimes are commited on January 1, 2018?
SELECT COUNT(*) FROM Crime WHERE date LIKE '1/1/2018%'
[ "How", "many", "crimes", "are", "commited", "on", "January", "1", ",", "2018", "?" ]
[ { "id": 2, "type": "value", "value": "1/1/2018%" }, { "id": 0, "type": "table", "value": "crime" }, { "id": 1, "type": "column", "value": "date" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7, 8, 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
15,280
shop_membership
spider:train_spider.json:5427
What are the names and cities of the branches that do not have any registered members?
SELECT name , city FROM branch WHERE branch_id NOT IN (SELECT branch_id FROM membership_register_branch)
[ "What", "are", "the", "names", "and", "cities", "of", "the", "branches", "that", "do", "not", "have", "any", "registered", "members", "?" ]
[ { "id": 4, "type": "table", "value": "membership_register_branch" }, { "id": 3, "type": "column", "value": "branch_id" }, { "id": 0, "type": "table", "value": "branch" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "city" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,281
beer_factory
bird:train.json:5342
What is the amount difference between the bottles of root beer sold from Louisiana and Missouri?
SELECT ( SELECT COUNT(T1.BrandID) FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID WHERE T2.State = 'LA' AND T1.ContainerType = 'Bottle' ) - ( SELECT COUNT(T3.BrandID) FROM rootbeer AS T3 INNER JOIN rootbeerbrand AS T4 ON T3.BrandID = T4.BrandID WHERE T4.State = 'MO' AND T3.ContainerType = 'Bottle' ) AS DIFFERENCE
[ "What", "is", "the", "amount", "difference", "between", "the", "bottles", "of", "root", "beer", "sold", "from", "Louisiana", "and", "Missouri", "?" ]
[ { "id": 1, "type": "table", "value": "rootbeerbrand" }, { "id": 5, "type": "column", "value": "containertype" }, { "id": 0, "type": "table", "value": "rootbeer" }, { "id": 2, "type": "column", "value": "brandid" }, { "id": 6, "type": "value", "value": "Bottle" }, { "id": 3, "type": "column", "value": "state" }, { "id": 4, "type": "value", "value": "LA" }, { "id": 7, "type": "value", "value": "MO" } ]
[ { "entity_id": 0, "token_idxs": [ 9, 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 7 ] }, { "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-VALUE", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,282
movie_3
bird:train.json:9111
What is the email address of the staff Jon Stephens?
SELECT email FROM staff WHERE first_name = 'Jon' AND last_name = 'Stephens'
[ "What", "is", "the", "email", "address", "of", "the", "staff", "Jon", "Stephens", "?" ]
[ { "id": 2, "type": "column", "value": "first_name" }, { "id": 4, "type": "column", "value": "last_name" }, { "id": 5, "type": "value", "value": "Stephens" }, { "id": 0, "type": "table", "value": "staff" }, { "id": 1, "type": "column", "value": "email" }, { "id": 3, "type": "value", "value": "Jon" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-VALUE", "B-VALUE", "O" ]
15,283
student_club
bird:dev.json:1359
How many times was the budget in Advertisement for "Yearly Kickoff" meeting more than "October Meeting"?
SELECT CAST(SUM(CASE WHEN T2.event_name = 'Yearly Kickoff' THEN T1.amount ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.event_name = 'October Meeting' THEN T1.amount ELSE 0 END) FROM budget AS T1 INNER JOIN event AS T2 ON T1.link_to_event = T2.event_id WHERE T1.category = 'Advertisement' AND T2.type = 'Meeting'
[ "How", "many", "times", "was", "the", "budget", "in", "Advertisement", "for", "\"", "Yearly", "Kickoff", "\"", "meeting", "more", "than", "\"", "October", "Meeting", "\"", "?" ]
[ { "id": 11, "type": "value", "value": "October Meeting" }, { "id": 12, "type": "value", "value": "Yearly Kickoff" }, { "id": 2, "type": "column", "value": "link_to_event" }, { "id": 5, "type": "value", "value": "Advertisement" }, { "id": 10, "type": "column", "value": "event_name" }, { "id": 3, "type": "column", "value": "event_id" }, { "id": 4, "type": "column", "value": "category" }, { "id": 7, "type": "value", "value": "Meeting" }, { "id": 0, "type": "table", "value": "budget" }, { "id": 9, "type": "column", "value": "amount" }, { "id": 1, "type": "table", "value": "event" }, { "id": 6, "type": "column", "value": "type" }, { "id": 8, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 13 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [ 17, 18 ] }, { "entity_id": 12, "token_idxs": [ 10, 11 ] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O" ]
15,284
simpson_episodes
bird:train.json:4324
Write down all the keywords for winner of "WGA Award (TV)" award.
SELECT T2.keyword FROM Award AS T1 INNER JOIN Keyword AS T2 ON T2.episode_id = T1.episode_id WHERE T1.award_category = 'WGA Award (TV)';
[ "Write", "down", "all", "the", "keywords", "for", "winner", "of", "\"", "WGA", "Award", "(", "TV", ")", "\"", "award", "." ]
[ { "id": 3, "type": "column", "value": "award_category" }, { "id": 4, "type": "value", "value": "WGA Award (TV)" }, { "id": 5, "type": "column", "value": "episode_id" }, { "id": 0, "type": "column", "value": "keyword" }, { "id": 2, "type": "table", "value": "keyword" }, { "id": 1, "type": "table", "value": "award" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 15 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9, 10, 11, 12, 13 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
15,285
scientist_1
spider:train_spider.json:6485
Find the name of the project for which a scientist whose name contains ‘Smith’ is assigned to.
SELECT T2.name FROM assignedto AS T1 JOIN projects AS T2 ON T1.project = T2.code JOIN scientists AS T3 ON T1.scientist = T3.SSN WHERE T3.name LIKE '%Smith%'
[ "Find", "the", "name", "of", "the", "project", "for", "which", "a", "scientist", "whose", "name", "contains", "‘", "Smith", "’", "is", "assigned", "to", "." ]
[ { "id": 1, "type": "table", "value": "scientists" }, { "id": 3, "type": "table", "value": "assignedto" }, { "id": 5, "type": "column", "value": "scientist" }, { "id": 4, "type": "table", "value": "projects" }, { "id": 2, "type": "value", "value": "%Smith%" }, { "id": 7, "type": "column", "value": "project" }, { "id": 0, "type": "column", "value": "name" }, { "id": 8, "type": "column", "value": "code" }, { "id": 6, "type": "column", "value": "ssn" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [ 17, 18 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 5 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "B-TABLE", "I-TABLE", "O" ]
15,286
regional_sales
bird:train.json:2590
List down the customer IDs and names that start with alphabet "W".
SELECT DISTINCT CustomerID, `Customer Names` FROM Customers WHERE `Customer Names` LIKE 'W%' ORDER BY `Customer Names` DESC
[ "List", "down", "the", "customer", "IDs", "and", "names", "that", "start", "with", "alphabet", "\"", "W", "\"", "." ]
[ { "id": 2, "type": "column", "value": "Customer Names" }, { "id": 1, "type": "column", "value": "customerid" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 3, "type": "value", "value": "W%" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "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-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,288
sakila_1
spider:train_spider.json:2956
Which store owns most items?
SELECT store_id FROM inventory GROUP BY store_id ORDER BY count(*) DESC LIMIT 1
[ "Which", "store", "owns", "most", "items", "?" ]
[ { "id": 0, "type": "table", "value": "inventory" }, { "id": 1, "type": "column", "value": "store_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O" ]
15,289
thrombosis_prediction
bird:dev.json:1161
For in-patient age 50 and above, what is their average anti-cardiolipin antibody (IgG) concentration?
SELECT AVG(T2.`aCL IgG`) FROM Patient AS T1 INNER JOIN Examination AS T2 ON T1.ID = T2.ID WHERE STRFTIME('%Y', CURRENT_TIMESTAMP) - STRFTIME('%Y', T1.Birthday) >= 50 AND T1.Admission = '+'
[ "For", "in", "-", "patient", "age", "50", "and", "above", ",", "what", "is", "their", "average", "anti", "-", "cardiolipin", "antibody", "(", "IgG", ")", "concentration", "?" ]
[ { "id": 1, "type": "table", "value": "examination" }, { "id": 5, "type": "column", "value": "admission" }, { "id": 8, "type": "column", "value": "birthday" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 2, "type": "column", "value": "aCL IgG" }, { "id": 3, "type": "column", "value": "id" }, { "id": 4, "type": "value", "value": "50" }, { "id": 7, "type": "value", "value": "%Y" }, { "id": 6, "type": "value", "value": "+" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 20 ] }, { "entity_id": 2, "token_idxs": [ 18 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
15,291
retails
bird:train.json:6767
How many customers who are not in debt ordered an urgent order?
SELECT COUNT(T2.c_custkey) FROM orders AS T1 INNER JOIN customer AS T2 ON T1.o_custkey = T2.c_custkey WHERE T2.c_acctbal > 0 AND T1.o_orderpriority = '1-URGENT'
[ "How", "many", "customers", "who", "are", "not", "in", "debt", "ordered", "an", "urgent", "order", "?" ]
[ { "id": 6, "type": "column", "value": "o_orderpriority" }, { "id": 2, "type": "column", "value": "c_custkey" }, { "id": 3, "type": "column", "value": "o_custkey" }, { "id": 4, "type": "column", "value": "c_acctbal" }, { "id": 1, "type": "table", "value": "customer" }, { "id": 7, "type": "value", "value": "1-URGENT" }, { "id": 0, "type": "table", "value": "orders" }, { "id": 5, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "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": [ 10 ] }, { "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", "B-VALUE", "B-TABLE", "O" ]
15,292
shipping
bird:train.json:5622
Where was shipment no. 1002 headed?
SELECT T2.city_name FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T1.ship_id = '1002'
[ "Where", "was", "shipment", "no", ".", "1002", "headed", "?" ]
[ { "id": 0, "type": "column", "value": "city_name" }, { "id": 1, "type": "table", "value": "shipment" }, { "id": 3, "type": "column", "value": "ship_id" }, { "id": 5, "type": "column", "value": "city_id" }, { "id": 2, "type": "table", "value": "city" }, { "id": 4, "type": "value", "value": "1002" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O" ]
15,293
car_retails
bird:train.json:1605
What is the full address of the office where 4 people work and one of them is Sales Representation?
SELECT T1.addressLine1, T1.addressLine2 FROM customers AS T1 INNER JOIN employees AS T2 ON T1.salesRepEmployeeNumber = T2.employeeNumber WHERE T2.jobTitle = 'Sales Rep'
[ "What", "is", "the", "full", "address", "of", "the", "office", "where", "4", "people", "work", "and", "one", "of", "them", "is", "Sales", "Representation", "?" ]
[ { "id": 6, "type": "column", "value": "salesrepemployeenumber" }, { "id": 7, "type": "column", "value": "employeenumber" }, { "id": 0, "type": "column", "value": "addressline1" }, { "id": 1, "type": "column", "value": "addressline2" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 3, "type": "table", "value": "employees" }, { "id": 5, "type": "value", "value": "Sales Rep" }, { "id": 4, "type": "column", "value": "jobtitle" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 17 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,294
vehicle_driver
bird:test.json:155
How many vehicles has a driver driven at most, and what is the driver id of the driver who has driven this many vehicles?
SELECT count(*) , driver_id FROM vehicle_driver GROUP BY driver_id ORDER BY count(*) DESC LIMIT 1
[ "How", "many", "vehicles", "has", "a", "driver", "driven", "at", "most", ",", "and", "what", "is", "the", "driver", "i", "d", "of", "the", "driver", "who", "has", "driven", "this", "many", "vehicles", "?" ]
[ { "id": 0, "type": "table", "value": "vehicle_driver" }, { "id": 1, "type": "column", "value": "driver_id" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3, 4, 5 ] }, { "entity_id": 1, "token_idxs": [ 14, 15, 16 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,295
bakery_1
bird:test.json:1520
Count the number of goods for each food type.
SELECT count(*) , food FROM goods GROUP BY food
[ "Count", "the", "number", "of", "goods", "for", "each", "food", "type", "." ]
[ { "id": 0, "type": "table", "value": "goods" }, { "id": 1, "type": "column", "value": "food" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O" ]
15,296
public_review_platform
bird:train.json:3812
How many active businesses are there in Phoenix?
SELECT COUNT(business_id) FROM Business WHERE city LIKE 'Phoenix' AND active LIKE 'TRUE'
[ "How", "many", "active", "businesses", "are", "there", "in", "Phoenix", "?" ]
[ { "id": 1, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "business" }, { "id": 3, "type": "value", "value": "Phoenix" }, { "id": 4, "type": "column", "value": "active" }, { "id": 2, "type": "column", "value": "city" }, { "id": 5, "type": "value", "value": "TRUE" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
15,297
college_1
spider:train_spider.json:3315
Find the first names and offices of all instructors who have taught some course and the course description and the department name.
SELECT T2.emp_fname , T4.prof_office , T3.crs_description , T5.dept_name FROM CLASS AS T1 JOIN employee AS T2 ON T1.prof_num = T2.emp_num JOIN course AS T3 ON T1.crs_code = T3.crs_code JOIN professor AS T4 ON T2.emp_num = T4.emp_num JOIN department AS T5 ON T4.dept_code = T5.dept_code
[ "Find", "the", "first", "names", "and", "offices", "of", "all", "instructors", "who", "have", "taught", "some", "course", "and", "the", "course", "description", "and", "the", "department", "name", "." ]
[ { "id": 2, "type": "column", "value": "crs_description" }, { "id": 1, "type": "column", "value": "prof_office" }, { "id": 4, "type": "table", "value": "department" }, { "id": 0, "type": "column", "value": "emp_fname" }, { "id": 3, "type": "column", "value": "dept_name" }, { "id": 5, "type": "table", "value": "professor" }, { "id": 6, "type": "column", "value": "dept_code" }, { "id": 10, "type": "table", "value": "employee" }, { "id": 11, "type": "column", "value": "crs_code" }, { "id": 12, "type": "column", "value": "prof_num" }, { "id": 8, "type": "column", "value": "emp_num" }, { "id": 7, "type": "table", "value": "course" }, { "id": 9, "type": "table", "value": "class" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 16, 17 ] }, { "entity_id": 3, "token_idxs": [ 20, 21 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 13 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,298
city_record
spider:train_spider.json:6298
Please give me a list of cities whose regional population is over 8000000 or under 5000000.
SELECT city FROM city WHERE regional_population > 10000000 UNION SELECT city FROM city WHERE regional_population < 5000000
[ "Please", "give", "me", "a", "list", "of", "cities", "whose", "regional", "population", "is", "over", "8000000", "or", "under", "5000000", "." ]
[ { "id": 2, "type": "column", "value": "regional_population" }, { "id": 3, "type": "value", "value": "10000000" }, { "id": 4, "type": "value", "value": "5000000" }, { "id": 0, "type": "table", "value": "city" }, { "id": 1, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 8, 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
15,299
european_football_2
bird:dev.json:1126
State the name of players who came from Belgium.
SELECT t3.player_name FROM Country AS t1 INNER JOIN Match AS t2 ON t1.id = t2.country_id INNER JOIN Player AS t3 ON t2.home_player_1 = t3.player_api_id WHERE t1.name = 'Belgium'
[ "State", "the", "name", "of", "players", "who", "came", "from", "Belgium", "." ]
[ { "id": 6, "type": "column", "value": "home_player_1" }, { "id": 7, "type": "column", "value": "player_api_id" }, { "id": 0, "type": "column", "value": "player_name" }, { "id": 9, "type": "column", "value": "country_id" }, { "id": 3, "type": "value", "value": "Belgium" }, { "id": 4, "type": "table", "value": "country" }, { "id": 1, "type": "table", "value": "player" }, { "id": 5, "type": "table", "value": "match" }, { "id": 2, "type": "column", "value": "name" }, { "id": 8, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 3 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-COLUMN", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
15,300
superhero
bird:dev.json:739
What are the names of the superheroes with the power of death touch?
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN hero_power AS T2 ON T1.id = T2.hero_id INNER JOIN superpower AS T3 ON T2.power_id = T3.id WHERE T3.power_name = 'Death Touch'
[ "What", "are", "the", "names", "of", "the", "superheroes", "with", "the", "power", "of", "death", "touch", "?" ]
[ { "id": 0, "type": "column", "value": "superhero_name" }, { "id": 3, "type": "value", "value": "Death Touch" }, { "id": 1, "type": "table", "value": "superpower" }, { "id": 2, "type": "column", "value": "power_name" }, { "id": 5, "type": "table", "value": "hero_power" }, { "id": 4, "type": "table", "value": "superhero" }, { "id": 6, "type": "column", "value": "power_id" }, { "id": 8, "type": "column", "value": "hero_id" }, { "id": 7, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 11, 12 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "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", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
15,301
restaurant
bird:train.json:1761
Among all indian restaurants in Castro St., Mountainview, how many of them is about cookhouse in their label?
SELECT COUNT(T1.id_restaurant) FROM location AS T1 INNER JOIN generalinfo AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T1.street_name = 'castro st' AND T1.city = 'mountain view' AND T2.food_type = 'indian' AND T2.label LIKE '%cookhouse%'
[ "Among", "all", "indian", "restaurants", "in", "Castro", "St.", ",", "Mountainview", ",", "how", "many", "of", "them", "is", "about", "cookhouse", "in", "their", "label", "?" ]
[ { "id": 2, "type": "column", "value": "id_restaurant" }, { "id": 6, "type": "value", "value": "mountain view" }, { "id": 1, "type": "table", "value": "generalinfo" }, { "id": 3, "type": "column", "value": "street_name" }, { "id": 10, "type": "value", "value": "%cookhouse%" }, { "id": 4, "type": "value", "value": "castro st" }, { "id": 7, "type": "column", "value": "food_type" }, { "id": 0, "type": "table", "value": "location" }, { "id": 8, "type": "value", "value": "indian" }, { "id": 9, "type": "column", "value": "label" }, { "id": 5, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5, 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 8 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 2 ] }, { "entity_id": 9, "token_idxs": [ 19 ] }, { "entity_id": 10, "token_idxs": [ 16 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O" ]
15,302
department_store
spider:train_spider.json:4717
What are the staff ids and genders of all staffs whose job title is Department Manager?
SELECT T1.staff_id , T1.staff_gender FROM staff AS T1 JOIN staff_department_assignments AS T2 ON T1.staff_id = T2.staff_id WHERE T2.job_title_code = "Department Manager"
[ "What", "are", "the", "staff", "ids", "and", "genders", "of", "all", "staffs", "whose", "job", "title", "is", "Department", "Manager", "?" ]
[ { "id": 3, "type": "table", "value": "staff_department_assignments" }, { "id": 5, "type": "column", "value": "Department Manager" }, { "id": 4, "type": "column", "value": "job_title_code" }, { "id": 1, "type": "column", "value": "staff_gender" }, { "id": 0, "type": "column", "value": "staff_id" }, { "id": 2, "type": "table", "value": "staff" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11, 12 ] }, { "entity_id": 5, "token_idxs": [ 14, 15 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,303
pilot_1
bird:test.json:1161
Find the max age for each group of pilots with the same name.
SELECT max(age) , pilot_name FROM pilotskills GROUP BY pilot_name
[ "Find", "the", "max", "age", "for", "each", "group", "of", "pilots", "with", "the", "same", "name", "." ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "pilot_name" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
15,304
shooting
bird:train.json:2472
From the cases where the subject were deceased, list the subject's last name, gender, race and case number.
SELECT T2.last_name, T2.gender, T2.race, T2.case_number FROM incidents AS T1 INNER JOIN subjects AS T2 ON T1.case_number = T2.case_number WHERE T1.subject_statuses = 'Deceased'
[ "From", "the", "cases", "where", "the", "subject", "were", "deceased", ",", "list", "the", "subject", "'s", "last", "name", ",", "gender", ",", "race", "and", "case", "number", "." ]
[ { "id": 6, "type": "column", "value": "subject_statuses" }, { "id": 3, "type": "column", "value": "case_number" }, { "id": 0, "type": "column", "value": "last_name" }, { "id": 4, "type": "table", "value": "incidents" }, { "id": 5, "type": "table", "value": "subjects" }, { "id": 7, "type": "value", "value": "Deceased" }, { "id": 1, "type": "column", "value": "gender" }, { "id": 2, "type": "column", "value": "race" } ]
[ { "entity_id": 0, "token_idxs": [ 13, 14 ] }, { "entity_id": 1, "token_idxs": [ 16 ] }, { "entity_id": 2, "token_idxs": [ 18 ] }, { "entity_id": 3, "token_idxs": [ 20, 21 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 11, 12 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 7 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,305
soccer_2
spider:train_spider.json:4951
How many different players trained for more than 1000 hours?
SELECT count(*) FROM Player WHERE HS > 1000
[ "How", "many", "different", "players", "trained", "for", "more", "than", "1000", "hours", "?" ]
[ { "id": 0, "type": "table", "value": "player" }, { "id": 2, "type": "value", "value": "1000" }, { "id": 1, "type": "column", "value": "hs" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "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", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,306
retails
bird:train.json:6738
List the suppliers' names which supplied smoke red pale saddle plum.
SELECT T3.s_name FROM part AS T1 INNER JOIN partsupp AS T2 ON T1.p_partkey = T2.ps_partkey INNER JOIN supplier AS T3 ON T2.ps_suppkey = T3.s_suppkey WHERE T1.p_name = 'smoke red pale saddle plum'
[ "List", "the", "suppliers", "'", "names", "which", "supplied", "smoke", "red", "pale", "saddle", "plum", "." ]
[ { "id": 3, "type": "value", "value": "smoke red pale saddle plum" }, { "id": 6, "type": "column", "value": "ps_suppkey" }, { "id": 9, "type": "column", "value": "ps_partkey" }, { "id": 7, "type": "column", "value": "s_suppkey" }, { "id": 8, "type": "column", "value": "p_partkey" }, { "id": 1, "type": "table", "value": "supplier" }, { "id": 5, "type": "table", "value": "partsupp" }, { "id": 0, "type": "column", "value": "s_name" }, { "id": 2, "type": "column", "value": "p_name" }, { "id": 4, "type": "table", "value": "part" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 7, 8, 9, 10, 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 6 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
15,307
department_store
spider:train_spider.json:4766
Return the phone numbers for all customers and suppliers.
SELECT customer_phone FROM customers UNION SELECT supplier_phone FROM suppliers
[ "Return", "the", "phone", "numbers", "for", "all", "customers", "and", "suppliers", "." ]
[ { "id": 2, "type": "column", "value": "customer_phone" }, { "id": 3, "type": "column", "value": "supplier_phone" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 1, "type": "table", "value": "suppliers" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O" ]
15,308
apartment_rentals
spider:train_spider.json:1237
Which guests have apartment bookings with status code "Confirmed"? Return their first names and last names.
SELECT T2.guest_first_name , T2.guest_last_name FROM Apartment_Bookings AS T1 JOIN Guests AS T2 ON T1.guest_id = T2.guest_id WHERE T1.booking_status_code = "Confirmed"
[ "Which", "guests", "have", "apartment", "bookings", "with", "status", "code", "\"", "Confirmed", "\"", "?", "Return", "their", "first", "names", "and", "last", "names", "." ]
[ { "id": 4, "type": "column", "value": "booking_status_code" }, { "id": 2, "type": "table", "value": "apartment_bookings" }, { "id": 0, "type": "column", "value": "guest_first_name" }, { "id": 1, "type": "column", "value": "guest_last_name" }, { "id": 5, "type": "column", "value": "Confirmed" }, { "id": 6, "type": "column", "value": "guest_id" }, { "id": 3, "type": "table", "value": "guests" } ]
[ { "entity_id": 0, "token_idxs": [ 14, 15 ] }, { "entity_id": 1, "token_idxs": [ 17, 18 ] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "entity_id": 3, "token_idxs": [ 1 ] }, { "entity_id": 4, "token_idxs": [ 5, 6, 7 ] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,309
music_platform_2
bird:train.json:7943
How many total reviews runned at in June 2022 were added to the podcasts?
SELECT SUM(reviews_added) FROM runs WHERE run_at LIKE '2022-06-%'
[ "How", "many", "total", "reviews", "runned", "at", "in", "June", "2022", "were", "added", "to", "the", "podcasts", "?" ]
[ { "id": 3, "type": "column", "value": "reviews_added" }, { "id": 2, "type": "value", "value": "2022-06-%" }, { "id": 1, "type": "column", "value": "run_at" }, { "id": 0, "type": "table", "value": "runs" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O" ]
15,310
cinema
spider:train_spider.json:1948
Who are all the directors?
SELECT DISTINCT directed_by FROM film
[ "Who", "are", "all", "the", "directors", "?" ]
[ { "id": 1, "type": "column", "value": "directed_by" }, { "id": 0, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O" ]
15,311
hr_1
spider:train_spider.json:3407
List the full name (first and last name), and salary for those employees who earn below 6000.
SELECT first_name , last_name , salary FROM employees WHERE salary < 6000
[ "List", "the", "full", "name", "(", "first", "and", "last", "name", ")", ",", "and", "salary", "for", "those", "employees", "who", "earn", "below", "6000", "." ]
[ { "id": 1, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 3, "type": "column", "value": "salary" }, { "id": 4, "type": "value", "value": "6000" } ]
[ { "entity_id": 0, "token_idxs": [ 15 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 7, 8 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 19 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
15,312
retail_world
bird:train.json:6371
What is the name of the supplier that supplies the most products to the company?
SELECT T1.SupplierID FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID GROUP BY T1.SupplierID ORDER BY COUNT(*) DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "supplier", "that", "supplies", "the", "most", "products", "to", "the", "company", "?" ]
[ { "id": 0, "type": "column", "value": "supplierid" }, { "id": 2, "type": "table", "value": "suppliers" }, { "id": 1, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
15,313
customers_and_products_contacts
spider:train_spider.json:5654
Show all distinct cities in the address record.
SELECT DISTINCT city FROM addresses
[ "Show", "all", "distinct", "cities", "in", "the", "address", "record", "." ]
[ { "id": 0, "type": "table", "value": "addresses" }, { "id": 1, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O" ]