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534
soccer_2
spider:train_spider.json:5014
What is the maximum training hours for the students whose training hours is greater than 1000 in different positions?
SELECT max(T1.HS) , pPos FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T1.HS > 1000 GROUP BY T2.pPos
[ "What", "is", "the", "maximum", "training", "hours", "for", "the", "students", "whose", "training", "hours", "is", "greater", "than", "1000", "in", "different", "positions", "?" ]
[ { "id": 1, "type": "table", "value": "player" }, { "id": 2, "type": "table", "value": "tryout" }, { "id": 0, "type": "column", "value": "ppos" }, { "id": 4, "type": "value", "value": "1000" }, { "id": 5, "type": "column", "value": "pid" }, { "id": 3, "type": "column", "value": "hs" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
535
document_management
spider:train_spider.json:4507
What is the average access count of documents?
SELECT avg(access_count) FROM documents
[ "What", "is", "the", "average", "access", "count", "of", "documents", "?" ]
[ { "id": 1, "type": "column", "value": "access_count" }, { "id": 0, "type": "table", "value": "documents" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O" ]
536
flight_4
spider:train_spider.json:6833
Find the name and city of the airport which is the destination of the most number of routes.
SELECT T1.name , T1.city , T2.dst_apid FROM airports AS T1 JOIN routes AS T2 ON T1.apid = T2.dst_apid GROUP BY T2.dst_apid ORDER BY count(*) DESC LIMIT 1
[ "Find", "the", "name", "and", "city", "of", "the", "airport", "which", "is", "the", "destination", "of", "the", "most", "number", "of", "routes", "." ]
[ { "id": 0, "type": "column", "value": "dst_apid" }, { "id": 3, "type": "table", "value": "airports" }, { "id": 4, "type": "table", "value": "routes" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "city" }, { "id": 5, "type": "column", "value": "apid" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
537
authors
bird:train.json:3651
What are the different ways the name of the author, Randall Davis, is written on their papers?
SELECT DISTINCT T1.Name FROM PaperAuthor AS T1 INNER JOIN Author AS T2 ON T1.AuthorId = T2.Id WHERE T2.Name = 'Randall Davis' AND T1.Name != 'Randall Davis'
[ "What", "are", "the", "different", "ways", "the", "name", "of", "the", "author", ",", "Randall", "Davis", ",", "is", "written", "on", "their", "papers", "?" ]
[ { "id": 5, "type": "value", "value": "Randall Davis" }, { "id": 1, "type": "table", "value": "paperauthor" }, { "id": 3, "type": "column", "value": "authorid" }, { "id": 2, "type": "table", "value": "author" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O" ]
538
image_and_language
bird:train.json:7567
List all the IDs of images that have objects with the attributes of 'wired'.
SELECT DISTINCT T2.IMG_ID FROM ATT_CLASSES AS T1 INNER JOIN IMG_OBJ_ATT AS T2 ON T1.ATT_CLASS_ID = T2.ATT_CLASS_ID WHERE T1.ATT_CLASS = 'wired'
[ "List", "all", "the", "IDs", "of", "images", "that", "have", "objects", "with", "the", "attributes", "of", "'", "wired", "'", "." ]
[ { "id": 5, "type": "column", "value": "att_class_id" }, { "id": 1, "type": "table", "value": "att_classes" }, { "id": 2, "type": "table", "value": "img_obj_att" }, { "id": 3, "type": "column", "value": "att_class" }, { "id": 0, "type": "column", "value": "img_id" }, { "id": 4, "type": "value", "value": "wired" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
539
law_episode
bird:train.json:1255
For how many times was Park Dietz credited?
SELECT COUNT(T3.person_id) FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T2.credited = 'true' AND T3.name = 'Park Dietz'
[ "For", "how", "many", "times", "was", "Park", "Dietz", "credited", "?" ]
[ { "id": 7, "type": "value", "value": "Park Dietz" }, { "id": 8, "type": "column", "value": "episode_id" }, { "id": 1, "type": "column", "value": "person_id" }, { "id": 4, "type": "column", "value": "credited" }, { "id": 2, "type": "table", "value": "episode" }, { "id": 0, "type": "table", "value": "person" }, { "id": 3, "type": "table", "value": "credit" }, { "id": 5, "type": "value", "value": "true" }, { "id": 6, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "B-TABLE", "O" ]
540
college_completion
bird:train.json:3684
What is the number of female graduates between 2011 to 2013 from the state where 'Gateway Community College' is located?
SELECT COUNT(T2.grad_cohort) FROM institution_details AS T1 INNER JOIN state_sector_grads AS T2 ON T1.state = T2.state WHERE T2.year BETWEEN 2011 AND 2013 AND T1.chronname = 'Gateway Community College' AND T2.gender = 'F'
[ "What", "is", "the", "number", "of", "female", "graduates", "between", "2011", "to", "2013", "from", "the", "state", "where", "'", "Gateway", "Community", "College", "'", "is", "located", "?" ]
[ { "id": 8, "type": "value", "value": "Gateway Community College" }, { "id": 0, "type": "table", "value": "institution_details" }, { "id": 1, "type": "table", "value": "state_sector_grads" }, { "id": 2, "type": "column", "value": "grad_cohort" }, { "id": 7, "type": "column", "value": "chronname" }, { "id": 9, "type": "column", "value": "gender" }, { "id": 3, "type": "column", "value": "state" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "2011" }, { "id": 6, "type": "value", "value": "2013" }, { "id": 10, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O" ]
541
student_club
bird:dev.json:1417
List out the type of events which have remaining budget more than 30 USD.
SELECT T1.type FROM event AS T1 INNER JOIN budget AS T2 ON T1.event_id = T2.link_to_event WHERE T2.remaining > 30
[ "List", "out", "the", "type", "of", "events", "which", "have", "remaining", "budget", "more", "than", "30", "USD", "." ]
[ { "id": 6, "type": "column", "value": "link_to_event" }, { "id": 3, "type": "column", "value": "remaining" }, { "id": 5, "type": "column", "value": "event_id" }, { "id": 2, "type": "table", "value": "budget" }, { "id": 1, "type": "table", "value": "event" }, { "id": 0, "type": "column", "value": "type" }, { "id": 4, "type": "value", "value": "30" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "B-VALUE", "O", "O" ]
542
roller_coaster
spider:train_spider.json:6206
List the names of countries whose language is not "German".
SELECT Name FROM country WHERE Languages != "German"
[ "List", "the", "names", "of", "countries", "whose", "language", "is", "not", "\"", "German", "\"", "." ]
[ { "id": 2, "type": "column", "value": "languages" }, { "id": 0, "type": "table", "value": "country" }, { "id": 3, "type": "column", "value": "German" }, { "id": 1, "type": "column", "value": "name" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
543
pilot_1
bird:test.json:1123
What are the planes owned by pilot Smith with age 41?
SELECT plane_name FROM pilotskills WHERE pilot_name = 'Smith' AND age = 41
[ "What", "are", "the", "planes", "owned", "by", "pilot", "Smith", "with", "age", "41", "?" ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "plane_name" }, { "id": 2, "type": "column", "value": "pilot_name" }, { "id": 3, "type": "value", "value": "Smith" }, { "id": 4, "type": "column", "value": "age" }, { "id": 5, "type": "value", "value": "41" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "B-VALUE", "O", "B-COLUMN", "B-VALUE", "O" ]
544
icfp_1
spider:train_spider.json:2873
What is the name of the institution the author "Katsuhiro Ueno" belongs to?
SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Katsuhiro" AND t1.lname = "Ueno"
[ "What", "is", "the", "name", "of", "the", "institution", "the", "author", "\"", "Katsuhiro", "Ueno", "\"", "belongs", "to", "?" ]
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[ "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O" ]
545
shooting
bird:train.json:2481
How many people were injured between 2006 and 2014 as a result of a handgun?
SELECT COUNT(location) FROM incidents WHERE subject_weapon = 'Handgun' AND subject_statuses = 'Injured' AND date BETWEEN '2006-01-01' AND '2013-12-31'
[ "How", "many", "people", "were", "injured", "between", "2006", "and", "2014", "as", "a", "result", "of", "a", "handgun", "?" ]
[ { "id": 4, "type": "column", "value": "subject_statuses" }, { "id": 2, "type": "column", "value": "subject_weapon" }, { "id": 7, "type": "value", "value": "2006-01-01" }, { "id": 8, "type": "value", "value": "2013-12-31" }, { "id": 0, "type": "table", "value": "incidents" }, { "id": 1, "type": "column", "value": "location" }, { "id": 3, "type": "value", "value": "Handgun" }, { "id": 5, "type": "value", "value": "Injured" }, { "id": 6, "type": "column", "value": "date" } ]
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[ "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
546
book_press
bird:test.json:2003
Find the title, author name, and publisher name for the top 3 best sales books.
SELECT t1.name , t2.title , t3.name FROM author AS t1 JOIN book AS t2 ON t1.author_id = t2.author_id JOIN press AS t3 ON t2.press_id = t3.press_id ORDER BY t2.sale_amount DESC LIMIT 3
[ "Find", "the", "title", ",", "author", "name", ",", "and", "publisher", "name", "for", "the", "top", "3", "best", "sales", "books", "." ]
[ { "id": 3, "type": "column", "value": "sale_amount" }, { "id": 7, "type": "column", "value": "author_id" }, { "id": 6, "type": "column", "value": "press_id" }, { "id": 4, "type": "table", "value": "author" }, { "id": 1, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "press" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "table", "value": "book" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
547
world
bird:train.json:7888
What is the GNP growth rate by the country of Shanghai?
SELECT CAST((T1.GNP - T1.GNPOld) AS REAL) / T1.GNPOld FROM Country AS T1 INNER JOIN City AS T2 ON T1.Code = T2.CountryCode WHERE T2.Name = 'Shanghai'
[ "What", "is", "the", "GNP", "growth", "rate", "by", "the", "country", "of", "Shanghai", "?" ]
[ { "id": 6, "type": "column", "value": "countrycode" }, { "id": 3, "type": "value", "value": "Shanghai" }, { "id": 0, "type": "table", "value": "country" }, { "id": 4, "type": "column", "value": "gnpold" }, { "id": 1, "type": "table", "value": "city" }, { "id": 2, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" }, { "id": 7, "type": "column", "value": "gnp" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
548
formula_1
bird:dev.json:846
Please list the reference names of the drivers who are eliminated in the first period in race number 20.
SELECT T2.driverRef FROM qualifying AS T1 INNER JOIN drivers AS T2 ON T2.driverId = T1.driverId WHERE T1.raceId = 20 ORDER BY T1.q1 DESC LIMIT 5
[ "Please", "list", "the", "reference", "names", "of", "the", "drivers", "who", "are", "eliminated", "in", "the", "first", "period", "in", "race", "number", "20", "." ]
[ { "id": 1, "type": "table", "value": "qualifying" }, { "id": 0, "type": "column", "value": "driverref" }, { "id": 6, "type": "column", "value": "driverid" }, { "id": 2, "type": "table", "value": "drivers" }, { "id": 3, "type": "column", "value": "raceid" }, { "id": 4, "type": "value", "value": "20" }, { "id": 5, "type": "column", "value": "q1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
549
wine_1
spider:train_spider.json:6538
Count the number of wines produced at Robert Biale winery.
SELECT count(*) FROM WINE WHERE Winery = "Robert Biale"
[ "Count", "the", "number", "of", "wines", "produced", "at", "Robert", "Biale", "winery", "." ]
[ { "id": 2, "type": "column", "value": "Robert Biale" }, { "id": 1, "type": "column", "value": "winery" }, { "id": 0, "type": "table", "value": "wine" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 7, 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
550
social_media
bird:train.json:829
Write down the tweet text posted from Rawang, Selangor, Malaysia.
SELECT T1.text FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID WHERE T2.City = 'Rawang' AND T2.State = 'Selangor' AND T2.Country = 'Malaysia'
[ "Write", "down", "the", "tweet", "text", "posted", "from", "Rawang", ",", "Selangor", ",", "Malaysia", "." ]
[ { "id": 3, "type": "column", "value": "locationid" }, { "id": 2, "type": "table", "value": "location" }, { "id": 7, "type": "value", "value": "Selangor" }, { "id": 9, "type": "value", "value": "Malaysia" }, { "id": 1, "type": "table", "value": "twitter" }, { "id": 8, "type": "column", "value": "country" }, { "id": 5, "type": "value", "value": "Rawang" }, { "id": 6, "type": "column", "value": "state" }, { "id": 0, "type": "column", "value": "text" }, { "id": 4, "type": "column", "value": "city" } ]
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[ "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
551
works_cycles
bird:train.json:7305
What is the average selling price of different vendors of the product Hex Nut 5?
SELECT SUM(T1.StandardPrice) / COUNT(T1.BusinessEntityID) FROM ProductVendor AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Name = 'Hex Nut 5'
[ "What", "is", "the", "average", "selling", "price", "of", "different", "vendors", "of", "the", "product", "Hex", "Nut", "5", "?" ]
[ { "id": 6, "type": "column", "value": "businessentityid" }, { "id": 0, "type": "table", "value": "productvendor" }, { "id": 5, "type": "column", "value": "standardprice" }, { "id": 3, "type": "value", "value": "Hex Nut 5" }, { "id": 4, "type": "column", "value": "productid" }, { "id": 1, "type": "table", "value": "product" }, { "id": 2, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
552
car_retails
bird:train.json:1602
To whom does the employee have to inform that is the sales representative of the French customer?
SELECT T1.reportsTo FROM employees AS T1 INNER JOIN customers AS T2 ON T1.employeeNumber = T2.salesRepEmployeeNumber WHERE T2.country = 'France'
[ "To", "whom", "does", "the", "employee", "have", "to", "inform", "that", "is", "the", "sales", "representative", "of", "the", "French", "customer", "?" ]
[ { "id": 6, "type": "column", "value": "salesrepemployeenumber" }, { "id": 5, "type": "column", "value": "employeenumber" }, { "id": 0, "type": "column", "value": "reportsto" }, { "id": 1, "type": "table", "value": "employees" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 3, "type": "column", "value": "country" }, { "id": 4, "type": "value", "value": "France" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
553
book_press
bird:test.json:2014
Which authors have never published under the "Accor" press? Give me their names.
SELECT name FROM author EXCEPT SELECT t1.name FROM author AS t1 JOIN book AS t2 ON t1.author_id = t2.author_id JOIN press AS t3 ON t2.press_id = t3.press_id WHERE t3.name = 'Accor'
[ "Which", "authors", "have", "never", "published", "under", "the", "\"", "Accor", "\"", "press", "?", "Give", "me", "their", "names", "." ]
[ { "id": 6, "type": "column", "value": "author_id" }, { "id": 5, "type": "column", "value": "press_id" }, { "id": 0, "type": "table", "value": "author" }, { "id": 2, "type": "table", "value": "press" }, { "id": 3, "type": "value", "value": "Accor" }, { "id": 1, "type": "column", "value": "name" }, { "id": 4, "type": "table", "value": "book" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 15 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
554
shakespeare
bird:train.json:3058
What is the chapter description where the paragraph "What, wilt thou hear some music, my sweet love?" belongs?
SELECT T1.id, T1.Description FROM chapters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.chapter_id WHERE T2.PlainText = 'What, wilt thou hear some music, my sweet love?'
[ "What", "is", "the", "chapter", "description", "where", "the", "paragraph", "\"", "What", ",", "wilt", "thou", "hear", "some", "music", ",", "my", "sweet", "love", "?", "\"", "belongs", "?" ]
[ { "id": 5, "type": "value", "value": "What, wilt thou hear some music, my sweet love?" }, { "id": 1, "type": "column", "value": "description" }, { "id": 3, "type": "table", "value": "paragraphs" }, { "id": 6, "type": "column", "value": "chapter_id" }, { "id": 4, "type": "column", "value": "plaintext" }, { "id": 2, "type": "table", "value": "chapters" }, { "id": 0, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O" ]
555
hospital_1
spider:train_spider.json:3935
How many rooms are located for each block code?
SELECT count(*) , T1.blockcode FROM BLOCK AS T1 JOIN room AS T2 ON T1.blockfloor = T2.blockfloor AND T1.blockcode = T2.blockcode GROUP BY T1.blockcode
[ "How", "many", "rooms", "are", "located", "for", "each", "block", "code", "?" ]
[ { "id": 3, "type": "column", "value": "blockfloor" }, { "id": 0, "type": "column", "value": "blockcode" }, { "id": 1, "type": "table", "value": "block" }, { "id": 2, "type": "table", "value": "room" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
556
debit_card_specializing
bird:dev.json:1518
For the deal happened at 2012/8/24 12:42:00, which country was it?
SELECT T2.Country FROM transactions_1k AS T1 INNER JOIN gasstations AS T2 ON T1.GasStationID = T2.GasStationID WHERE T1.Date = '2012-08-24' AND T1.Time = '12:42:00'
[ "For", "the", "deal", "happened", "at", "2012/8/24", "12:42:00", ",", "which", "country", "was", "it", "?" ]
[ { "id": 1, "type": "table", "value": "transactions_1k" }, { "id": 3, "type": "column", "value": "gasstationid" }, { "id": 2, "type": "table", "value": "gasstations" }, { "id": 5, "type": "value", "value": "2012-08-24" }, { "id": 7, "type": "value", "value": "12:42:00" }, { "id": 0, "type": "column", "value": "country" }, { "id": 4, "type": "column", "value": "date" }, { "id": 6, "type": "column", "value": "time" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "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": [ 5 ] }, { "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", "O", "O", "B-COLUMN", "B-VALUE", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "O" ]
557
pilot_1
bird:test.json:1154
Return the average age of pilots for each plane name.
SELECT avg(age) , plane_name FROM pilotskills GROUP BY plane_name
[ "Return", "the", "average", "age", "of", "pilots", "for", "each", "plane", "name", "." ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 1, "type": "column", "value": "plane_name" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 8, 9 ] }, { "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", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
558
financial
bird:dev.json:110
What is the disposition id of the client who made 5100 USD transaction in 1998/9/2?
SELECT T1.disp_id FROM disp AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id INNER JOIN trans AS T3 ON T2.account_id = T3.account_id WHERE T3.date='1997-08-20' AND T3.amount = 5100
[ "What", "is", "the", "disposition", "i", "d", "of", "the", "client", "who", "made", "5100", "USD", "transaction", "in", "1998/9/2", "?" ]
[ { "id": 4, "type": "column", "value": "account_id" }, { "id": 6, "type": "value", "value": "1997-08-20" }, { "id": 0, "type": "column", "value": "disp_id" }, { "id": 3, "type": "table", "value": "account" }, { "id": 7, "type": "column", "value": "amount" }, { "id": 1, "type": "table", "value": "trans" }, { "id": 2, "type": "table", "value": "disp" }, { "id": 5, "type": "column", "value": "date" }, { "id": 8, "type": "value", "value": "5100" } ]
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[ "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-TABLE", "O", "O", "O" ]
559
tv_shows
bird:test.json:139
List the station names of city channels whose affiliation is not "ABC".
SELECT Station_name FROM city_channel WHERE Affiliation != "ABC"
[ "List", "the", "station", "names", "of", "city", "channels", "whose", "affiliation", "is", "not", "\"", "ABC", "\"", "." ]
[ { "id": 0, "type": "table", "value": "city_channel" }, { "id": 1, "type": "column", "value": "station_name" }, { "id": 2, "type": "column", "value": "affiliation" }, { "id": 3, "type": "column", "value": "ABC" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
560
driving_school
spider:train_spider.json:6695
What are the first and last names of all customers with more than 2 payments?
SELECT T2.first_name , T2.last_name FROM Customer_Payments AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id HAVING count(*) > 2;
[ "What", "are", "the", "first", "and", "last", "names", "of", "all", "customers", "with", "more", "than", "2", "payments", "?" ]
[ { "id": 3, "type": "table", "value": "customer_payments" }, { "id": 0, "type": "column", "value": "customer_id" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 4, "type": "table", "value": "customers" }, { "id": 5, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "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", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O", "O" ]
561
european_football_2
bird:dev.json:1083
Which player has the strongest overall strength?
SELECT t1.player_name FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id ORDER BY t2.overall_rating DESC LIMIT 1
[ "Which", "player", "has", "the", "strongest", "overall", "strength", "?" ]
[ { "id": 2, "type": "table", "value": "player_attributes" }, { "id": 3, "type": "column", "value": "overall_rating" }, { "id": 4, "type": "column", "value": "player_api_id" }, { "id": 0, "type": "column", "value": "player_name" }, { "id": 1, "type": "table", "value": "player" } ]
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[ "O", "B-TABLE", "B-TABLE", "I-TABLE", "I-TABLE", "B-COLUMN", "O", "O" ]
562
food_inspection
bird:train.json:8825
Provide eateries' IDs, risk categories and descriptions with violation ID of 103101.
SELECT business_id, risk_category, description FROM violations WHERE violation_type_id = '103101'
[ "Provide", "eateries", "'", "IDs", ",", "risk", "categories", "and", "descriptions", "with", "violation", "ID", "of", "103101", "." ]
[ { "id": 4, "type": "column", "value": "violation_type_id" }, { "id": 2, "type": "column", "value": "risk_category" }, { "id": 1, "type": "column", "value": "business_id" }, { "id": 3, "type": "column", "value": "description" }, { "id": 0, "type": "table", "value": "violations" }, { "id": 5, "type": "value", "value": "103101" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "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", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
563
body_builder
spider:train_spider.json:1173
What is the minimum snatch score?
SELECT min(snatch) FROM body_builder
[ "What", "is", "the", "minimum", "snatch", "score", "?" ]
[ { "id": 0, "type": "table", "value": "body_builder" }, { "id": 1, "type": "column", "value": "snatch" } ]
[ { "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", "O" ]
564
soccer_3
bird:test.json:4
What are the managers and captains of clubs?
SELECT Manager , Captain FROM club
[ "What", "are", "the", "managers", "and", "captains", "of", "clubs", "?" ]
[ { "id": 1, "type": "column", "value": "manager" }, { "id": 2, "type": "column", "value": "captain" }, { "id": 0, "type": "table", "value": "club" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
565
assets_maintenance
spider:train_spider.json:3146
Which staff have contacted which engineers? List the staff name and the engineer first name and last name.
SELECT T1.staff_name , T3.first_name , T3.last_name FROM Staff AS T1 JOIN Engineer_Visits AS T2 ON T1.staff_id = T2.contact_staff_id JOIN Maintenance_Engineers AS T3 ON T2.engineer_id = T3.engineer_id
[ "Which", "staff", "have", "contacted", "which", "engineers", "?", "List", "the", "staff", "name", "and", "the", "engineer", "first", "name", "and", "last", "name", "." ]
[ { "id": 3, "type": "table", "value": "maintenance_engineers" }, { "id": 8, "type": "column", "value": "contact_staff_id" }, { "id": 5, "type": "table", "value": "engineer_visits" }, { "id": 6, "type": "column", "value": "engineer_id" }, { "id": 0, "type": "column", "value": "staff_name" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 7, "type": "column", "value": "staff_id" }, { "id": 4, "type": "table", "value": "staff" } ]
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[ "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "B-TABLE", "I-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
566
tracking_orders
spider:train_spider.json:6935
Find the distinct details of invoices which are created before 1989-09-03 or after 2007-12-25.
SELECT DISTINCT invoice_details FROM invoices WHERE invoice_date < "1989-09-03" OR invoice_date > "2007-12-25"
[ "Find", "the", "distinct", "details", "of", "invoices", "which", "are", "created", "before", "1989", "-", "09", "-", "03", "or", "after", "2007", "-", "12", "-", "25", "." ]
[ { "id": 1, "type": "column", "value": "invoice_details" }, { "id": 2, "type": "column", "value": "invoice_date" }, { "id": 3, "type": "column", "value": "1989-09-03" }, { "id": 4, "type": "column", "value": "2007-12-25" }, { "id": 0, "type": "table", "value": "invoices" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
567
soccer_2016
bird:train.json:1921
How many games were not won by runs?
SELECT SUM(CASE WHEN T2.Win_Type != 'runs' THEN 1 ELSE 0 END) FROM `Match` AS T1 INNER JOIN Win_By AS T2 ON T1.Win_Type = T2.Win_Id
[ "How", "many", "games", "were", "not", "won", "by", "runs", "?" ]
[ { "id": 2, "type": "column", "value": "win_type" }, { "id": 1, "type": "table", "value": "win_by" }, { "id": 3, "type": "column", "value": "win_id" }, { "id": 0, "type": "table", "value": "Match" }, { "id": 6, "type": "value", "value": "runs" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 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", "B-TABLE", "I-TABLE", "B-VALUE", "O" ]
568
musical
spider:train_spider.json:236
List the name of actors in ascending alphabetical order.
SELECT Name FROM actor ORDER BY Name ASC
[ "List", "the", "name", "of", "actors", "in", "ascending", "alphabetical", "order", "." ]
[ { "id": 0, "type": "table", "value": "actor" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
569
debit_card_specializing
bird:dev.json:1473
What was the average monthly consumption of customers in SME for the year 2013?
SELECT AVG(T2.Consumption) / 12 FROM customers AS T1 INNER JOIN yearmonth AS T2 ON T1.CustomerID = T2.CustomerID WHERE SUBSTR(T2.Date, 1, 4) = '2013' AND T1.Segment = 'SME'
[ "What", "was", "the", "average", "monthly", "consumption", "of", "customers", "in", "SME", "for", "the", "year", "2013", "?" ]
[ { "id": 7, "type": "column", "value": "consumption" }, { "id": 3, "type": "column", "value": "customerid" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 1, "type": "table", "value": "yearmonth" }, { "id": 5, "type": "column", "value": "segment" }, { "id": 4, "type": "value", "value": "2013" }, { "id": 8, "type": "column", "value": "date" }, { "id": 6, "type": "value", "value": "SME" }, { "id": 2, "type": "value", "value": "12" }, { "id": 9, "type": "value", "value": "1" }, { "id": 10, "type": "value", "value": "4" } ]
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[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O" ]
570
movie_2
bird:test.json:1844
What are the names of all cinemas not showing any movies?
SELECT DISTINCT name FROM MovieTheaters WHERE Movie = 'null'
[ "What", "are", "the", "names", "of", "all", "cinemas", "not", "showing", "any", "movies", "?" ]
[ { "id": 0, "type": "table", "value": "movietheaters" }, { "id": 2, "type": "column", "value": "movie" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "null" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
571
allergy_1
spider:train_spider.json:481
How many students live in HKG or CHI?
SELECT count(*) FROM Student WHERE city_code = "HKG" OR city_code = "CHI"
[ "How", "many", "students", "live", "in", "HKG", "or", "CHI", "?" ]
[ { "id": 1, "type": "column", "value": "city_code" }, { "id": 0, "type": "table", "value": "student" }, { "id": 2, "type": "column", "value": "HKG" }, { "id": 3, "type": "column", "value": "CHI" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
572
thrombosis_prediction
bird:dev.json:1149
Are there more in-patient or outpatient who were male? What is the deviation in percentage?
SELECT CAST(SUM(CASE WHEN Admission = '+' THEN 1 ELSE 0 END) AS REAL) * 100 / SUM(CASE WHEN Admission = '-' THEN 1 ELSE 0 END) FROM Patient WHERE SEX = 'M'
[ "Are", "there", "more", "in", "-", "patient", "or", "outpatient", "who", "were", "male", "?", "What", "is", "the", "deviation", "in", "percentage", "?" ]
[ { "id": 6, "type": "column", "value": "admission" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 1, "type": "column", "value": "sex" }, { "id": 3, "type": "value", "value": "100" }, { "id": 2, "type": "value", "value": "M" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" }, { "id": 7, "type": "value", "value": "-" }, { "id": 8, "type": "value", "value": "+" } ]
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[ "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
573
ship_1
spider:train_spider.json:6235
What are the names of captains that have either the rank Midshipman or Lieutenant?
SELECT name FROM captain WHERE rank = 'Midshipman' OR rank = 'Lieutenant'
[ "What", "are", "the", "names", "of", "captains", "that", "have", "either", "the", "rank", "Midshipman", "or", "Lieutenant", "?" ]
[ { "id": 3, "type": "value", "value": "Midshipman" }, { "id": 4, "type": "value", "value": "Lieutenant" }, { "id": 0, "type": "table", "value": "captain" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "rank" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "B-VALUE", "O" ]
574
student_assessment
spider:train_spider.json:75
Find id of the candidate who most recently accessed the course?
SELECT candidate_id FROM candidate_assessments ORDER BY assessment_date DESC LIMIT 1
[ "Find", "i", "d", "of", "the", "candidate", "who", "most", "recently", "accessed", "the", "course", "?" ]
[ { "id": 0, "type": "table", "value": "candidate_assessments" }, { "id": 2, "type": "column", "value": "assessment_date" }, { "id": 1, "type": "column", "value": "candidate_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 9, 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
575
public_review_platform
bird:train.json:3851
How many Yelp_Businesses do not provide alcohol?
SELECT COUNT(T1.attribute_id) FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T1.attribute_name LIKE 'Alcohol' AND T2.attribute_value LIKE 'none'
[ "How", "many", "Yelp_Businesses", "do", "not", "provide", "alcohol", "?" ]
[ { "id": 1, "type": "table", "value": "business_attributes" }, { "id": 5, "type": "column", "value": "attribute_value" }, { "id": 3, "type": "column", "value": "attribute_name" }, { "id": 2, "type": "column", "value": "attribute_id" }, { "id": 0, "type": "table", "value": "attributes" }, { "id": 4, "type": "value", "value": "Alcohol" }, { "id": 6, "type": "value", "value": "none" } ]
[ { "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": [ 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", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
576
public_review_platform
bird:train.json:3938
What city does the business have a business hour from 10 am to 12 pm on Sunday?
SELECT T1.city FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T2.opening_time LIKE '10AM' AND T2.closing_time LIKE '12PM' AND T3.day_of_week LIKE 'Sunday'
[ "What", "city", "does", "the", "business", "have", "a", "business", "hour", "from", "10", "am", "to", "12", "pm", "on", "Sunday", "?" ]
[ { "id": 3, "type": "table", "value": "business_hours" }, { "id": 5, "type": "column", "value": "opening_time" }, { "id": 7, "type": "column", "value": "closing_time" }, { "id": 9, "type": "column", "value": "day_of_week" }, { "id": 11, "type": "column", "value": "business_id" }, { "id": 2, "type": "table", "value": "business" }, { "id": 4, "type": "column", "value": "day_id" }, { "id": 10, "type": "value", "value": "Sunday" }, { "id": 0, "type": "column", "value": "city" }, { "id": 1, "type": "table", "value": "days" }, { "id": 6, "type": "value", "value": "10AM" }, { "id": 8, "type": "value", "value": "12PM" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
577
cre_Students_Information_Systems
bird:test.json:474
What are the date and detail of each transcript?
SELECT date_of_transcript , transcript_details FROM Transcripts
[ "What", "are", "the", "date", "and", "detail", "of", "each", "transcript", "?" ]
[ { "id": 1, "type": "column", "value": "date_of_transcript" }, { "id": 2, "type": "column", "value": "transcript_details" }, { "id": 0, "type": "table", "value": "transcripts" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
578
mental_health_survey
bird:train.json:4609
How many users answered the question "Overall, how much importance does your employer place on physical health?"?
SELECT COUNT(T1.UserID) FROM Answer AS T1 INNER JOIN Question AS T2 ON T1.QuestionID = T2.questionid WHERE T2.questiontext LIKE 'Overall, how much importance does your employer place on physical health?'
[ "How", "many", "users", "answered", "the", "question", "\"", "Overall", ",", "how", "much", "importance", "does", "your", "employer", "place", "on", "physical", "health", "?", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "Overall, how much importance does your employer place on physical health?" }, { "id": 2, "type": "column", "value": "questiontext" }, { "id": 5, "type": "column", "value": "questionid" }, { "id": 1, "type": "table", "value": "question" }, { "id": 0, "type": "table", "value": "answer" }, { "id": 4, "type": "column", "value": "userid" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
579
sports_competition
spider:train_spider.json:3344
What are the types of every competition and in which countries are they located?
SELECT Competition_type , Country FROM competition
[ "What", "are", "the", "types", "of", "every", "competition", "and", "in", "which", "countries", "are", "they", "located", "?" ]
[ { "id": 1, "type": "column", "value": "competition_type" }, { "id": 0, "type": "table", "value": "competition" }, { "id": 2, "type": "column", "value": "country" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
580
network_2
spider:train_spider.json:4426
What is minimum age for different job title?
SELECT min(age) , job FROM Person GROUP BY job
[ "What", "is", "minimum", "age", "for", "different", "job", "title", "?" ]
[ { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "job" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
581
hospital_1
spider:train_spider.json:3916
What is the name of the patient who made the most recent appointment?
SELECT T1.name FROM patient AS T1 JOIN appointment AS T2 ON T1.ssn = T2.patient ORDER BY T2.start DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "patient", "who", "made", "the", "most", "recent", "appointment", "?" ]
[ { "id": 2, "type": "table", "value": "appointment" }, { "id": 1, "type": "table", "value": "patient" }, { "id": 5, "type": "column", "value": "patient" }, { "id": 3, "type": "column", "value": "start" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "ssn" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
582
hr_1
spider:train_spider.json:3528
What are full names and salaries of employees working in the city of London?
SELECT first_name , last_name , salary FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id JOIN locations AS T3 ON T2.location_id = T3.location_id WHERE T3.city = 'London'
[ "What", "are", "full", "names", "and", "salaries", "of", "employees", "working", "in", "the", "city", "of", "London", "?" ]
[ { "id": 9, "type": "column", "value": "department_id" }, { "id": 7, "type": "table", "value": "departments" }, { "id": 8, "type": "column", "value": "location_id" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 3, "type": "table", "value": "locations" }, { "id": 6, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "salary" }, { "id": 5, "type": "value", "value": "London" }, { "id": 4, "type": "column", "value": "city" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
583
menu
bird:train.json:5568
Among the menu pages of "Ritz Carlton", how many of them have a width of over 1000?
SELECT SUM(CASE WHEN T1.name = 'Ritz Carlton' THEN 1 ELSE 0 END) FROM Menu AS T1 INNER JOIN MenuPage AS T2 ON T1.id = T2.menu_id WHERE T2.full_width > 1000
[ "Among", "the", "menu", "pages", "of", "\"", "Ritz", "Carlton", "\"", ",", "how", "many", "of", "them", "have", "a", "width", "of", "over", "1000", "?" ]
[ { "id": 9, "type": "value", "value": "Ritz Carlton" }, { "id": 2, "type": "column", "value": "full_width" }, { "id": 1, "type": "table", "value": "menupage" }, { "id": 5, "type": "column", "value": "menu_id" }, { "id": 0, "type": "table", "value": "menu" }, { "id": 3, "type": "value", "value": "1000" }, { "id": 8, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "id" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "O", "B-TABLE", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
584
authors
bird:train.json:3607
How many authors is affiliated to the organization "Otterbein University"?
SELECT COUNT(Name) FROM Author WHERE Affiliation = 'Otterbein University'
[ "How", "many", "authors", "is", "affiliated", "to", "the", "organization", "\"", "Otterbein", "University", "\"", "?" ]
[ { "id": 2, "type": "value", "value": "Otterbein University" }, { "id": 1, "type": "column", "value": "affiliation" }, { "id": 0, "type": "table", "value": "author" }, { "id": 3, "type": "column", "value": "name" } ]
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[ "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O" ]
585
formula_1
spider:train_spider.json:2170
What is the id, first name, and last name of the driver who was in the first position for laptime at least twice?
SELECT T1.driverid , T1.forename , T1.surname FROM drivers AS T1 JOIN laptimes AS T2 ON T1.driverid = T2.driverid WHERE POSITION = '1' GROUP BY T1.driverid HAVING count(*) >= 2
[ "What", "is", "the", "i", "d", ",", "first", "name", ",", "and", "last", "name", "of", "the", "driver", "who", "was", "in", "the", "first", "position", "for", "laptime", "at", "least", "twice", "?" ]
[ { "id": 0, "type": "column", "value": "driverid" }, { "id": 1, "type": "column", "value": "forename" }, { "id": 4, "type": "table", "value": "laptimes" }, { "id": 5, "type": "column", "value": "position" }, { "id": 2, "type": "column", "value": "surname" }, { "id": 3, "type": "table", "value": "drivers" }, { "id": 6, "type": "value", "value": "1" }, { "id": 7, "type": "value", "value": "2" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O" ]
586
law_episode
bird:train.json:1320
Write down the organization, year, award, and award category in which Rene Balcer is the winner.
SELECT T2.organization, T2.year, T2.award, T2.award_category FROM Person AS T1 INNER JOIN Award AS T2 ON T1.person_id = T2.person_id WHERE T1.name = 'Rene Balcer' AND T2.result = 'Winner'
[ "Write", "down", "the", "organization", ",", "year", ",", "award", ",", "and", "award", "category", "in", "which", "Rene", "Balcer", "is", "the", "winner", "." ]
[ { "id": 3, "type": "column", "value": "award_category" }, { "id": 0, "type": "column", "value": "organization" }, { "id": 8, "type": "value", "value": "Rene Balcer" }, { "id": 6, "type": "column", "value": "person_id" }, { "id": 4, "type": "table", "value": "person" }, { "id": 9, "type": "column", "value": "result" }, { "id": 10, "type": "value", "value": "Winner" }, { "id": 2, "type": "column", "value": "award" }, { "id": 5, "type": "table", "value": "award" }, { "id": 1, "type": "column", "value": "year" }, { "id": 7, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "B-VALUE", "O" ]
587
protein_institute
spider:train_spider.json:1926
How many proteins are associated with an institution founded after 1880 or an institution with type "Private"?
SELECT count(*) FROM institution AS T1 JOIN protein AS T2 ON T1.institution_id = T2.institution_id WHERE T1.founded > 1880 OR T1.type = 'Private'
[ "How", "many", "proteins", "are", "associated", "with", "an", "institution", "founded", "after", "1880", "or", "an", "institution", "with", "type", "\"", "Private", "\"", "?" ]
[ { "id": 2, "type": "column", "value": "institution_id" }, { "id": 0, "type": "table", "value": "institution" }, { "id": 1, "type": "table", "value": "protein" }, { "id": 3, "type": "column", "value": "founded" }, { "id": 6, "type": "value", "value": "Private" }, { "id": 4, "type": "value", "value": "1880" }, { "id": 5, "type": "column", "value": "type" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
588
formula_1
spider:train_spider.json:2210
What are the last names and ids of all drivers who had 11 pit stops and participated in more than 5 races?
SELECT T1.surname , T1.driverid FROM drivers AS T1 JOIN pitstops AS T2 ON T1.driverid = T2.driverid GROUP BY T1.driverid HAVING count(*) = 11 INTERSECT SELECT T1.surname , T1.driverid FROM drivers AS T1 JOIN results AS T2 ON T1.driverid = T2.driverid GROUP BY T1.driverid HAVING count(*) > 5
[ "What", "are", "the", "last", "names", "and", "ids", "of", "all", "drivers", "who", "had", "11", "pit", "stops", "and", "participated", "in", "more", "than", "5", "races", "?" ]
[ { "id": 0, "type": "column", "value": "driverid" }, { "id": 3, "type": "table", "value": "pitstops" }, { "id": 1, "type": "column", "value": "surname" }, { "id": 2, "type": "table", "value": "drivers" }, { "id": 5, "type": "table", "value": "results" }, { "id": 4, "type": "value", "value": "11" }, { "id": 6, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
589
match_season
spider:train_spider.json:1094
Return all players sorted by college in ascending alphabetical order.
SELECT player FROM match_season ORDER BY College ASC
[ "Return", "all", "players", "sorted", "by", "college", "in", "ascending", "alphabetical", "order", "." ]
[ { "id": 0, "type": "table", "value": "match_season" }, { "id": 2, "type": "column", "value": "college" }, { "id": 1, "type": "column", "value": "player" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
591
mondial_geo
bird:train.json:8395
Which two countries have the border in length of 803 km? Give the full names of the countries.
SELECT T1.Name, T3.Name FROM country AS T1 INNER JOIN borders AS T2 ON T1.Code = T2.Country1 INNER JOIN country AS T3 ON T3.Code = T2.Country2 WHERE T2.Length = 803
[ "Which", "two", "countries", "have", "the", "border", "in", "length", "of", "803", "km", "?", "Give", "the", "full", "names", "of", "the", "countries", "." ]
[ { "id": 6, "type": "column", "value": "country2" }, { "id": 7, "type": "column", "value": "country1" }, { "id": 1, "type": "table", "value": "country" }, { "id": 4, "type": "table", "value": "borders" }, { "id": 2, "type": "column", "value": "length" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" }, { "id": 3, "type": "value", "value": "803" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
592
retails
bird:train.json:6714
How many suppliers are from Japan?
SELECT COUNT(T1.c_custkey) FROM customer AS T1 INNER JOIN nation AS T2 ON T1.c_nationkey = T2.n_nationkey WHERE T2.n_name = 'JAPAN'
[ "How", "many", "suppliers", "are", "from", "Japan", "?" ]
[ { "id": 5, "type": "column", "value": "c_nationkey" }, { "id": 6, "type": "column", "value": "n_nationkey" }, { "id": 4, "type": "column", "value": "c_custkey" }, { "id": 0, "type": "table", "value": "customer" }, { "id": 1, "type": "table", "value": "nation" }, { "id": 2, "type": "column", "value": "n_name" }, { "id": 3, "type": "value", "value": "JAPAN" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "O" ]
593
address
bird:train.json:5216
Among the cities with alias Ponce, what is the percentage of cities with a country level FIPS code of less than 20?
SELECT CAST(COUNT(CASE WHEN T2.county_fips < 20 THEN T2.zip_code ELSE NULL END) AS REAL) * 100 / COUNT(T2.zip_code) FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.alias = 'Ponce'
[ "Among", "the", "cities", "with", "alias", "Ponce", ",", "what", "is", "the", "percentage", "of", "cities", "with", "a", "country", "level", "FIPS", "code", "of", "less", "than", "20", "?" ]
[ { "id": 6, "type": "column", "value": "county_fips" }, { "id": 1, "type": "table", "value": "zip_data" }, { "id": 4, "type": "column", "value": "zip_code" }, { "id": 0, "type": "table", "value": "alias" }, { "id": 2, "type": "column", "value": "alias" }, { "id": 3, "type": "value", "value": "Ponce" }, { "id": 5, "type": "value", "value": "100" }, { "id": 7, "type": "value", "value": "20" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
594
college_1
spider:train_spider.json:3188
Where is the history department?
SELECT dept_address FROM department WHERE dept_name = 'History'
[ "Where", "is", "the", "history", "department", "?" ]
[ { "id": 1, "type": "column", "value": "dept_address" }, { "id": 0, "type": "table", "value": "department" }, { "id": 2, "type": "column", "value": "dept_name" }, { "id": 3, "type": "value", "value": "History" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "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-VALUE", "B-COLUMN", "O" ]
595
cinema
spider:train_spider.json:1954
What are the title and director of the films without any schedule?
SELECT title , directed_by FROM film WHERE film_id NOT IN (SELECT film_id FROM schedule)
[ "What", "are", "the", "title", "and", "director", "of", "the", "films", "without", "any", "schedule", "?" ]
[ { "id": 2, "type": "column", "value": "directed_by" }, { "id": 4, "type": "table", "value": "schedule" }, { "id": 3, "type": "column", "value": "film_id" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
596
customers_and_orders
bird:test.json:285
Show the id and the product type for all products, order by product name.
SELECT product_id , product_type_code FROM Products ORDER BY product_name
[ "Show", "the", "i", "d", "and", "the", "product", "type", "for", "all", "products", ",", "order", "by", "product", "name", "." ]
[ { "id": 2, "type": "column", "value": "product_type_code" }, { "id": 3, "type": "column", "value": "product_name" }, { "id": 1, "type": "column", "value": "product_id" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 14, 15 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
597
retail_complains
bird:train.json:398
List the product reviewed with 1 star on March 14, 2016 from Newton, Massachusetts.
SELECT T2.Product FROM district AS T1 INNER JOIN reviews AS T2 ON T1.district_id = T2.district_id WHERE T1.city = 'Newton' AND T1.state_abbrev = 'MA' AND T2.Date = '2016-03-14' AND T2.Stars = 1
[ "List", "the", "product", "reviewed", "with", "1", "star", "on", "March", "14", ",", "2016", "from", "Newton", ",", "Massachusetts", "." ]
[ { "id": 6, "type": "column", "value": "state_abbrev" }, { "id": 3, "type": "column", "value": "district_id" }, { "id": 9, "type": "value", "value": "2016-03-14" }, { "id": 1, "type": "table", "value": "district" }, { "id": 0, "type": "column", "value": "product" }, { "id": 2, "type": "table", "value": "reviews" }, { "id": 5, "type": "value", "value": "Newton" }, { "id": 10, "type": "column", "value": "stars" }, { "id": 4, "type": "column", "value": "city" }, { "id": 8, "type": "column", "value": "date" }, { "id": 7, "type": "value", "value": "MA" }, { "id": 11, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "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": [ 6 ] }, { "entity_id": 11, "token_idxs": [ 5 ] }, { "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", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
598
store_product
spider:train_spider.json:4938
Find the name of the products that are not using the most frequently-used max page size.
SELECT product FROM product WHERE product != (SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1)
[ "Find", "the", "name", "of", "the", "products", "that", "are", "not", "using", "the", "most", "frequently", "-", "used", "max", "page", "size", "." ]
[ { "id": 2, "type": "column", "value": "max_page_size" }, { "id": 0, "type": "table", "value": "product" }, { "id": 1, "type": "column", "value": "product" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 15, 16, 17 ] }, { "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", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
599
books
bird:train.json:6002
How many of the customer addresses are inactive?
SELECT COUNT(*) FROM customer_address AS T1 INNER JOIN address_status AS T2 ON T1.status_id = T2.status_id WHERE T2.address_status = 'Inactive'
[ "How", "many", "of", "the", "customer", "addresses", "are", "inactive", "?" ]
[ { "id": 0, "type": "table", "value": "customer_address" }, { "id": 1, "type": "table", "value": "address_status" }, { "id": 2, "type": "column", "value": "address_status" }, { "id": 4, "type": "column", "value": "status_id" }, { "id": 3, "type": "value", "value": "Inactive" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
600
movie_platform
bird:train.json:149
Among all movies in the list, calculate the percentage of movies that were never been rated?
SELECT CAST(SUM(CASE WHEN T2.movie_id IS NULL THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.movie_id) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id
[ "Among", "all", "movies", "in", "the", "list", ",", "calculate", "the", "percentage", "of", "movies", "that", "were", "never", "been", "rated", "?" ]
[ { "id": 2, "type": "column", "value": "movie_id" }, { "id": 0, "type": "table", "value": "ratings" }, { "id": 1, "type": "table", "value": "movies" }, { "id": 3, "type": "value", "value": "100" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "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", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
601
cars
bird:train.json:3069
Please list the names of all the car models whose origin country is the USA.
SELECT DISTINCT T1.car_name FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T2.country = T3.origin WHERE T3.country = 'USA'
[ "Please", "list", "the", "names", "of", "all", "the", "car", "models", "whose", "origin", "country", "is", "the", "USA", "." ]
[ { "id": 5, "type": "table", "value": "production" }, { "id": 0, "type": "column", "value": "car_name" }, { "id": 1, "type": "table", "value": "country" }, { "id": 2, "type": "column", "value": "country" }, { "id": 6, "type": "column", "value": "origin" }, { "id": 4, "type": "table", "value": "data" }, { "id": 3, "type": "value", "value": "USA" }, { "id": 7, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
602
works_cycles
bird:train.json:7270
What is the full name of the sales person who has the the highest commission percent received per sale?
SELECT T2.FirstName, T2.MiddleName, T2.LastName FROM SalesPerson AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID ORDER BY T1.CommissionPct DESC LIMIT 1
[ "What", "is", "the", "full", "name", "of", "the", "sales", "person", "who", "has", "the", "the", "highest", "commission", "percent", "received", "per", "sale", "?" ]
[ { "id": 6, "type": "column", "value": "businessentityid" }, { "id": 5, "type": "column", "value": "commissionpct" }, { "id": 3, "type": "table", "value": "salesperson" }, { "id": 1, "type": "column", "value": "middlename" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 4, "type": "table", "value": "person" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "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", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
603
movie_platform
bird:train.json:94
Please list the names of the top three movies in the number of likes related to the critic made by the user rating the movie.
SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id ORDER BY T1.critic_likes DESC LIMIT 3
[ "Please", "list", "the", "names", "of", "the", "top", "three", "movies", "in", "the", "number", "of", "likes", "related", "to", "the", "critic", "made", "by", "the", "user", "rating", "the", "movie", "." ]
[ { "id": 3, "type": "column", "value": "critic_likes" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 4, "type": "column", "value": "movie_id" }, { "id": 1, "type": "table", "value": "ratings" }, { "id": 2, "type": "table", "value": "movies" } ]
[ { "entity_id": 0, "token_idxs": [ 9, 10 ] }, { "entity_id": 1, "token_idxs": [ 22 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 17 ] }, { "entity_id": 4, "token_idxs": [ 24 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O" ]
604
movie_3
bird:train.json:9409
What are the titles of the films starred by Russell Close?
SELECT T3.title FROM film_actor AS T1 INNER JOIN actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T1.film_id = T3.film_id WHERE T2.first_name = 'Russell' AND T2.last_name = 'Close'
[ "What", "are", "the", "titles", "of", "the", "films", "starred", "by", "Russell", "Close", "?" ]
[ { "id": 2, "type": "table", "value": "film_actor" }, { "id": 5, "type": "column", "value": "first_name" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 9, "type": "column", "value": "actor_id" }, { "id": 4, "type": "column", "value": "film_id" }, { "id": 6, "type": "value", "value": "Russell" }, { "id": 0, "type": "column", "value": "title" }, { "id": 3, "type": "table", "value": "actor" }, { "id": 8, "type": "value", "value": "Close" }, { "id": 1, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "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": [ 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 10 ] }, { "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-VALUE", "B-VALUE", "O" ]
605
retail_world
bird:train.json:6383
What is the average price of products with more than fifty units in stock?
SELECT SUM(UnitPrice) / COUNT(UnitPrice) FROM Products WHERE UnitsInStock > 50
[ "What", "is", "the", "average", "price", "of", "products", "with", "more", "than", "fifty", "units", "in", "stock", "?" ]
[ { "id": 1, "type": "column", "value": "unitsinstock" }, { "id": 3, "type": "column", "value": "unitprice" }, { "id": 0, "type": "table", "value": "products" }, { "id": 2, "type": "value", "value": "50" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 11, 12, 13 ] }, { "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", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
606
company_employee
spider:train_spider.json:4111
list the names of the companies with more than 200 sales in the descending order of sales and profits.
SELECT name FROM company WHERE Sales_in_Billion > 200 ORDER BY Sales_in_Billion , Profits_in_Billion DESC
[ "list", "the", "names", "of", "the", "companies", "with", "more", "than", "200", "sales", "in", "the", "descending", "order", "of", "sales", "and", "profits", "." ]
[ { "id": 4, "type": "column", "value": "profits_in_billion" }, { "id": 2, "type": "column", "value": "sales_in_billion" }, { "id": 0, "type": "table", "value": "company" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "200" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 10, 11 ] }, { "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-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
607
movie_1
spider:train_spider.json:2512
Find the names of reviewers who had given higher than 3 star ratings.
SELECT T2.name FROM Rating AS T1 JOIN Reviewer AS T2 ON T1.rID = T2.rID WHERE T1.stars > 3
[ "Find", "the", "names", "of", "reviewers", "who", "had", "given", "higher", "than", "3", "star", "ratings", "." ]
[ { "id": 2, "type": "table", "value": "reviewer" }, { "id": 1, "type": "table", "value": "rating" }, { "id": 3, "type": "column", "value": "stars" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "rid" }, { "id": 4, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "B-TABLE", "O" ]
608
legislator
bird:train.json:4902
What is the average number of terms served for a current legislator that's famous or impact?
SELECT CAST(COUNT(T2.bioguide) AS REAL) / COUNT(DISTINCT T1.bioguide_id) FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.wikipedia_id IS NOT NULL
[ "What", "is", "the", "average", "number", "of", "terms", "served", "for", "a", "current", "legislator", "that", "'s", "famous", "or", "impact", "?" ]
[ { "id": 1, "type": "table", "value": "current-terms" }, { "id": 2, "type": "column", "value": "wikipedia_id" }, { "id": 3, "type": "column", "value": "bioguide_id" }, { "id": 4, "type": "column", "value": "bioguide" }, { "id": 0, "type": "table", "value": "current" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O" ]
609
phone_market
spider:train_spider.json:1992
List the names of phones that are not on any market.
SELECT Name FROM phone WHERE Phone_id NOT IN (SELECT Phone_ID FROM phone_market)
[ "List", "the", "names", "of", "phones", "that", "are", "not", "on", "any", "market", "." ]
[ { "id": 3, "type": "table", "value": "phone_market" }, { "id": 2, "type": "column", "value": "phone_id" }, { "id": 0, "type": "table", "value": "phone" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
610
synthea
bird:train.json:1496
What condition forced Mrs. Joye Homenick to seek medical attention in 2017?
SELECT T2.DESCRIPTION FROM patients AS T1 INNER JOIN conditions AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Joye' AND T1.last = 'Homenick' AND strftime('%Y', T2.START) = '2017'
[ "What", "condition", "forced", "Mrs.", "Joye", "Homenick", "to", "seek", "medical", "attention", "in", "2017", "?" ]
[ { "id": 0, "type": "column", "value": "description" }, { "id": 2, "type": "table", "value": "conditions" }, { "id": 1, "type": "table", "value": "patients" }, { "id": 7, "type": "value", "value": "Homenick" }, { "id": 3, "type": "column", "value": "patient" }, { "id": 4, "type": "column", "value": "first" }, { "id": 10, "type": "column", "value": "start" }, { "id": 5, "type": "value", "value": "Joye" }, { "id": 6, "type": "column", "value": "last" }, { "id": 8, "type": "value", "value": "2017" }, { "id": 9, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 1 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 4 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 5 ] }, { "entity_id": 8, "token_idxs": [ 11 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "B-VALUE", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
611
retails
bird:train.json:6815
What is the name of the customer number 93697 with the total order price of 191918.92?
SELECT T2.c_name FROM orders AS T1 INNER JOIN customer AS T2 ON T1.o_custkey = T2.c_custkey WHERE T1.o_totalprice = 191918.92 AND T1.o_custkey = 93697
[ "What", "is", "the", "name", "of", "the", "customer", "number", "93697", "with", "the", "total", "order", "price", "of", "191918.92", "?" ]
[ { "id": 5, "type": "column", "value": "o_totalprice" }, { "id": 3, "type": "column", "value": "o_custkey" }, { "id": 4, "type": "column", "value": "c_custkey" }, { "id": 6, "type": "value", "value": "191918.92" }, { "id": 2, "type": "table", "value": "customer" }, { "id": 0, "type": "column", "value": "c_name" }, { "id": 1, "type": "table", "value": "orders" }, { "id": 7, "type": "value", "value": "93697" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 11, 13 ] }, { "entity_id": 6, "token_idxs": [ 15 ] }, { "entity_id": 7, "token_idxs": [ 8 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
612
retail_world
bird:train.json:6392
List the names of non-US suppliers that have discontinued.
SELECT DISTINCT T2.CompanyName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.Discontinued = 1 AND T2.Country != 'USA'
[ "List", "the", "names", "of", "non", "-", "US", "suppliers", "that", "have", "discontinued", "." ]
[ { "id": 4, "type": "column", "value": "discontinued" }, { "id": 0, "type": "column", "value": "companyname" }, { "id": 3, "type": "column", "value": "supplierid" }, { "id": 2, "type": "table", "value": "suppliers" }, { "id": 1, "type": "table", "value": "products" }, { "id": 6, "type": "column", "value": "country" }, { "id": 7, "type": "value", "value": "USA" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 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", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
613
company_employee
spider:train_spider.json:4097
List the names of companies by ascending number of sales.
SELECT Name FROM company ORDER BY Sales_in_Billion ASC
[ "List", "the", "names", "of", "companies", "by", "ascending", "number", "of", "sales", "." ]
[ { "id": 2, "type": "column", "value": "sales_in_billion" }, { "id": 0, "type": "table", "value": "company" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
614
college_2
spider:train_spider.json:1385
What are the names of students and their respective departments, ordered by number of credits from least to greatest?
SELECT name , dept_name FROM student ORDER BY tot_cred
[ "What", "are", "the", "names", "of", "students", "and", "their", "respective", "departments", ",", "ordered", "by", "number", "of", "credits", "from", "least", "to", "greatest", "?" ]
[ { "id": 2, "type": "column", "value": "dept_name" }, { "id": 3, "type": "column", "value": "tot_cred" }, { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
615
aan_1
bird:test.json:1028
Count the number of papers Stanford University had between 2000 and 2009.
SELECT count(DISTINCT T1.paper_id) FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T1.year >= 2000 AND T1.year <= 2009 AND T3.name LIKE "Stanford University"
[ "Count", "the", "number", "of", "papers", "Stanford", "University", "had", "between", "2000", "and", "2009", "." ]
[ { "id": 9, "type": "column", "value": "Stanford University" }, { "id": 4, "type": "column", "value": "affiliation_id" }, { "id": 0, "type": "table", "value": "affiliation" }, { "id": 3, "type": "table", "value": "author_list" }, { "id": 1, "type": "column", "value": "paper_id" }, { "id": 2, "type": "table", "value": "paper" }, { "id": 5, "type": "column", "value": "year" }, { "id": 6, "type": "value", "value": "2000" }, { "id": 7, "type": "value", "value": "2009" }, { "id": 8, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 9 ] }, { "entity_id": 7, "token_idxs": [ 11 ] }, { "entity_id": 8, "token_idxs": [ 2 ] }, { "entity_id": 9, "token_idxs": [ 5, 6 ] }, { "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", "I-COLUMN", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
616
works_cycles
bird:train.json:7307
Please list the top 3 house-manufactured products with the highest average rating.
SELECT T2.Name FROM ProductReview AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.MakeFlag = 1 GROUP BY T2.Name ORDER BY SUM(T1.Rating) DESC LIMIT 1
[ "Please", "list", "the", "top", "3", "house", "-", "manufactured", "products", "with", "the", "highest", "average", "rating", "." ]
[ { "id": 1, "type": "table", "value": "productreview" }, { "id": 5, "type": "column", "value": "productid" }, { "id": 3, "type": "column", "value": "makeflag" }, { "id": 2, "type": "table", "value": "product" }, { "id": 6, "type": "column", "value": "rating" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "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": [ 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", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
618
cre_Doc_and_collections
bird:test.json:738
How many different collections are related to the one named 'Best'?
SELECT count(DISTINCT T1.Related_Collection_ID) FROM Collection_Subset_Members AS T1 JOIN Collections AS T2 ON T1.Collection_ID = T2.Collection_ID WHERE T2.Collection_Name = "Best";
[ "How", "many", "different", "collections", "are", "related", "to", "the", "one", "named", "'", "Best", "'", "?" ]
[ { "id": 0, "type": "table", "value": "collection_subset_members" }, { "id": 4, "type": "column", "value": "related_collection_id" }, { "id": 2, "type": "column", "value": "collection_name" }, { "id": 5, "type": "column", "value": "collection_id" }, { "id": 1, "type": "table", "value": "collections" }, { "id": 3, "type": "column", "value": "Best" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
619
college_completion
bird:train.json:3746
In Harvard University, which year recorded the highest number of first-time, full-time, degree-seeking students in the cohort being tracked, minus any exclusions?
SELECT T2.year FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T1.chronname = 'Harvard University' GROUP BY T2.year ORDER BY SUM(T2.grad_cohort) DESC LIMIT 1
[ "In", "Harvard", "University", ",", "which", "year", "recorded", "the", "highest", "number", "of", "first", "-", "time", ",", "full", "-", "time", ",", "degree", "-", "seeking", "students", "in", "the", "cohort", "being", "tracked", ",", "minus", "any", "exclusions", "?" ]
[ { "id": 1, "type": "table", "value": "institution_details" }, { "id": 4, "type": "value", "value": "Harvard University" }, { "id": 2, "type": "table", "value": "institution_grads" }, { "id": 6, "type": "column", "value": "grad_cohort" }, { "id": 3, "type": "column", "value": "chronname" }, { "id": 5, "type": "column", "value": "unitid" }, { "id": 0, "type": "column", "value": "year" } ]
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[ "O", "B-VALUE", "I-VALUE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
620
college_2
spider:train_spider.json:1414
What is the id of the instructor who advises of all students from History department?
SELECT i_id FROM advisor AS T1 JOIN student AS T2 ON T1.s_id = T2.id WHERE T2.dept_name = 'History'
[ "What", "is", "the", "i", "d", "of", "the", "instructor", "who", "advises", "of", "all", "students", "from", "History", "department", "?" ]
[ { "id": 3, "type": "column", "value": "dept_name" }, { "id": 1, "type": "table", "value": "advisor" }, { "id": 2, "type": "table", "value": "student" }, { "id": 4, "type": "value", "value": "History" }, { "id": 0, "type": "column", "value": "i_id" }, { "id": 5, "type": "column", "value": "s_id" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "B-TABLE", "O", "B-VALUE", "B-COLUMN", "O" ]
621
legislator
bird:train.json:4880
How many female representatives served in the state of California for at least 10 years?
SELECT SUM(T3.result) FROM ( SELECT CASE WHEN SUM(CAST(strftime('%Y', T2.`end`) AS int) - CAST(strftime('%Y', T2.start) AS int)) > 10 THEN 1 ELSE 0 END AS result FROM current AS T1 INNER JOIN "current-terms" AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.gender_bio = 'F' AND T2.state = 'CA' AND T2.type = 'rep' ) AS T3
[ "How", "many", "female", "representatives", "served", "in", "the", "state", "of", "California", "for", "at", "least", "10", "years", "?" ]
[ { "id": 2, "type": "table", "value": "current-terms" }, { "id": 4, "type": "column", "value": "bioguide_id" }, { "id": 6, "type": "column", "value": "gender_bio" }, { "id": 5, "type": "column", "value": "bioguide" }, { "id": 1, "type": "table", "value": "current" }, { "id": 0, "type": "column", "value": "result" }, { "id": 8, "type": "column", "value": "state" }, { "id": 16, "type": "column", "value": "start" }, { "id": 10, "type": "column", "value": "type" }, { "id": 11, "type": "value", "value": "rep" }, { "id": 15, "type": "column", "value": "end" }, { "id": 9, "type": "value", "value": "CA" }, { "id": 13, "type": "value", "value": "10" }, { "id": 14, "type": "value", "value": "%Y" }, { "id": 3, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "F" }, { "id": 12, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
622
product_catalog
spider:train_spider.json:313
Find the names and publication dates of all catalogs that have catalog level number greater than 5.
SELECT t1.catalog_name , t1.date_of_publication FROM catalogs AS t1 JOIN catalog_structure AS t2 ON t1.catalog_id = t2.catalog_id WHERE catalog_level_number > 5
[ "Find", "the", "names", "and", "publication", "dates", "of", "all", "catalogs", "that", "have", "catalog", "level", "number", "greater", "than", "5", "." ]
[ { "id": 4, "type": "column", "value": "catalog_level_number" }, { "id": 1, "type": "column", "value": "date_of_publication" }, { "id": 3, "type": "table", "value": "catalog_structure" }, { "id": 0, "type": "column", "value": "catalog_name" }, { "id": 6, "type": "column", "value": "catalog_id" }, { "id": 2, "type": "table", "value": "catalogs" }, { "id": 5, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
623
online_exams
bird:test.json:230
Which types of questions have 3 or more questions? Return the questions type code.
SELECT Type_of_Question_Code FROM Questions GROUP BY Type_of_Question_Code HAVING count(*) >= 3
[ "Which", "types", "of", "questions", "have", "3", "or", "more", "questions", "?", "Return", "the", "questions", "type", "code", "." ]
[ { "id": 1, "type": "column", "value": "type_of_question_code" }, { "id": 0, "type": "table", "value": "questions" }, { "id": 2, "type": "value", "value": "3" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
624
sales
bird:train.json:5458
How many employees sold over 20,000 quantities of "Touring-2000 Blue, 50"?
SELECT COUNT(*) FROM ( SELECT SUM(Quantity) FROM Sales WHERE ProductID IN ( SELECT ProductID FROM Products WHERE Name = 'Touring-2000 Blue, 50' ) GROUP BY Quantity, SalesPersonID HAVING SUM(Quantity) > 20000 )
[ "How", "many", "employees", "sold", "over", "20,000", "quantities", "of", "\"", "Touring-2000", "Blue", ",", "50", "\"", "?" ]
[ { "id": 7, "type": "value", "value": "Touring-2000 Blue, 50" }, { "id": 2, "type": "column", "value": "salespersonid" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 1, "type": "column", "value": "quantity" }, { "id": 5, "type": "table", "value": "products" }, { "id": 0, "type": "table", "value": "sales" }, { "id": 4, "type": "value", "value": "20000" }, { "id": 6, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
625
soccer_2016
bird:train.json:1929
How many players were born before 10/16/1975, and have a bowling skill of less than 3?
SELECT COUNT(*) FROM Player WHERE DOB < '1975-10-16' AND Bowling_skill < 3
[ "How", "many", "players", "were", "born", "before", "10/16/1975", ",", "and", "have", "a", "bowling", "skill", "of", "less", "than", "3", "?" ]
[ { "id": 3, "type": "column", "value": "bowling_skill" }, { "id": 2, "type": "value", "value": "1975-10-16" }, { "id": 0, "type": "table", "value": "player" }, { "id": 1, "type": "column", "value": "dob" }, { "id": 4, "type": "value", "value": "3" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
627
hockey
bird:train.json:7791
Which was the dominant hand for the goaltender who played 32 games for QUN in 1973? Give the full name.
SELECT T2.shootCatch, T2.firstName, T2.lastName FROM Goalies AS T1 INNER JOIN Master AS T2 ON T1.playerID = T2.playerID AND T1.year = 1973 WHERE T1.tmID = 'QUN' AND T1.GP = 32
[ "Which", "was", "the", "dominant", "hand", "for", "the", "goaltender", "who", "played", "32", "games", "for", "QUN", "in", "1973", "?", "Give", "the", "full", "name", "." ]
[ { "id": 0, "type": "column", "value": "shootcatch" }, { "id": 1, "type": "column", "value": "firstname" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 9, "type": "column", "value": "playerid" }, { "id": 3, "type": "table", "value": "goalies" }, { "id": 4, "type": "table", "value": "master" }, { "id": 5, "type": "column", "value": "tmid" }, { "id": 10, "type": "column", "value": "year" }, { "id": 11, "type": "value", "value": "1973" }, { "id": 6, "type": "value", "value": "QUN" }, { "id": 7, "type": "column", "value": "gp" }, { "id": 8, "type": "value", "value": "32" } ]
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[ "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
628
hr_1
spider:train_spider.json:3474
What are the full names and department ids for the lowest paid employees across all departments.
SELECT first_name , last_name , department_id FROM employees WHERE salary IN (SELECT MIN(salary) FROM employees GROUP BY department_id)
[ "What", "are", "the", "full", "names", "and", "department", "ids", "for", "the", "lowest", "paid", "employees", "across", "all", "departments", "." ]
[ { "id": 3, "type": "column", "value": "department_id" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 4, "type": "column", "value": "salary" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
629
soccer_2016
bird:train.json:1967
How many matches were held in 2011?
SELECT COUNT(Match_Id) FROM `Match` WHERE Match_Date LIKE '2011%'
[ "How", "many", "matches", "were", "held", "in", "2011", "?" ]
[ { "id": 1, "type": "column", "value": "match_date" }, { "id": 3, "type": "column", "value": "match_id" }, { "id": 0, "type": "table", "value": "Match" }, { "id": 2, "type": "value", "value": "2011%" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
630
dorm_1
spider:train_spider.json:5734
Find the number of students whose age is older than the average age for each gender.
SELECT count(*) , sex FROM student WHERE age > (SELECT avg(age) FROM student) GROUP BY sex
[ "Find", "the", "number", "of", "students", "whose", "age", "is", "older", "than", "the", "average", "age", "for", "each", "gender", "." ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "sex" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
631
pilot_1
bird:test.json:1168
What is the location of the plane that was flown by the pilot with the lowest age?
SELECT T2.location FROM pilotskills AS T1 JOIN hangar AS T2 ON T1.plane_name = T2.plane_name WHERE T1.age = (SELECT min(age) FROM pilotskills)
[ "What", "is", "the", "location", "of", "the", "plane", "that", "was", "flown", "by", "the", "pilot", "with", "the", "lowest", "age", "?" ]
[ { "id": 1, "type": "table", "value": "pilotskills" }, { "id": 4, "type": "column", "value": "plane_name" }, { "id": 0, "type": "column", "value": "location" }, { "id": 2, "type": "table", "value": "hangar" }, { "id": 3, "type": "column", "value": "age" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
632
car_retails
bird:train.json:1634
Which product did Cruz & Sons Co. order on 2003/3/3?
SELECT t4.productName FROM orderdetails AS t1 INNER JOIN orders AS t2 ON t1.orderNumber = t2.orderNumber INNER JOIN customers AS t3 ON t2.customerNumber = t3.customerNumber INNER JOIN products AS t4 ON t1.productCode = t4.productCode WHERE t3.customerName = 'Cruz & Sons Co.' AND t2.orderDate = '2003-03-03'
[ "Which", "product", "did", "Cruz", "&", "Sons", "Co.", "order", "on", "2003/3/3", "?" ]
[ { "id": 5, "type": "value", "value": "Cruz & Sons Co." }, { "id": 10, "type": "column", "value": "customernumber" }, { "id": 4, "type": "column", "value": "customername" }, { "id": 8, "type": "table", "value": "orderdetails" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 3, "type": "column", "value": "productcode" }, { "id": 11, "type": "column", "value": "ordernumber" }, { "id": 7, "type": "value", "value": "2003-03-03" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 6, "type": "column", "value": "orderdate" }, { "id": 1, "type": "table", "value": "products" }, { "id": 9, "type": "table", "value": "orders" } ]
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[ "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "B-COLUMN", "B-VALUE", "O" ]
633
ship_mission
spider:train_spider.json:3998
How many ships are there?
SELECT count(*) FROM ship
[ "How", "many", "ships", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "ship" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O" ]
635
flight_1
spider:train_spider.json:392
What are the numbers of all flights that can cover a distance of more than 2000?
SELECT flno FROM Flight WHERE distance > 2000
[ "What", "are", "the", "numbers", "of", "all", "flights", "that", "can", "cover", "a", "distance", "of", "more", "than", "2000", "?" ]
[ { "id": 2, "type": "column", "value": "distance" }, { "id": 0, "type": "table", "value": "flight" }, { "id": 1, "type": "column", "value": "flno" }, { "id": 3, "type": "value", "value": "2000" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
636
ship_mission
spider:train_spider.json:4009
What is the ship with the largest amount of tonnage called?
SELECT Name FROM ship ORDER BY Tonnage DESC LIMIT 1
[ "What", "is", "the", "ship", "with", "the", "largest", "amount", "of", "tonnage", "called", "?" ]
[ { "id": 2, "type": "column", "value": "tonnage" }, { "id": 0, "type": "table", "value": "ship" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
637
college_1
spider:train_spider.json:3304
What is the name and address of the department with the most students?
SELECT T2.dept_name , T2.dept_address FROM student AS T1 JOIN department AS T2 ON T1.dept_code = T2.dept_code GROUP BY T1.dept_code ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "name", "and", "address", "of", "the", "department", "with", "the", "most", "students", "?" ]
[ { "id": 2, "type": "column", "value": "dept_address" }, { "id": 4, "type": "table", "value": "department" }, { "id": 0, "type": "column", "value": "dept_code" }, { "id": 1, "type": "column", "value": "dept_name" }, { "id": 3, "type": "table", "value": "student" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]