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authors
bird:train.json:3584
How many authors were associated with the Microsoft Research when paper number 1 was written?
SELECT COUNT(PaperId) FROM PaperAuthor WHERE Affiliation LIKE '%Microsoft Research%'
[ "How", "many", "authors", "were", "associated", "with", "the", "Microsoft", "Research", "when", "paper", "number", "1", "was", "written", "?" ]
[ { "id": 2, "type": "value", "value": "%Microsoft Research%" }, { "id": 0, "type": "table", "value": "paperauthor" }, { "id": 1, "type": "column", "value": "affiliation" }, { "id": 3, "type": "column", "value": "paperid" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
2,039
works_cycles
bird:train.json:7403
What is the minimum inventory quantity of Chainring Bolts?
SELECT SafetyStockLevel FROM Product WHERE Name = 'Chainring Bolts'
[ "What", "is", "the", "minimum", "inventory", "quantity", "of", "Chainring", "Bolts", "?" ]
[ { "id": 1, "type": "column", "value": "safetystocklevel" }, { "id": 3, "type": "value", "value": "Chainring Bolts" }, { "id": 0, "type": "table", "value": "product" }, { "id": 2, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
2,040
e_government
spider:train_spider.json:6317
What are the party emails associated with parties that used the party form that is the most common?
SELECT t1.party_email FROM parties AS t1 JOIN party_forms AS t2 ON t1.party_id = t2.party_id WHERE t2.form_id = (SELECT form_id FROM party_forms GROUP BY form_id ORDER BY count(*) DESC LIMIT 1)
[ "What", "are", "the", "party", "emails", "associated", "with", "parties", "that", "used", "the", "party", "form", "that", "is", "the", "most", "common", "?" ]
[ { "id": 0, "type": "column", "value": "party_email" }, { "id": 2, "type": "table", "value": "party_forms" }, { "id": 4, "type": "column", "value": "party_id" }, { "id": 1, "type": "table", "value": "parties" }, { "id": 3, "type": "column", "value": "form_id" } ]
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[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
2,042
aircraft
spider:train_spider.json:4803
What are the number of international and domestic passengers of the airport named London "Heathrow"?
SELECT International_Passengers , Domestic_Passengers FROM airport WHERE Airport_Name = "London Heathrow"
[ "What", "are", "the", "number", "of", "international", "and", "domestic", "passengers", "of", "the", "airport", "named", "London", "\"", "Heathrow", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "international_passengers" }, { "id": 2, "type": "column", "value": "domestic_passengers" }, { "id": 4, "type": "column", "value": "London Heathrow" }, { "id": 3, "type": "column", "value": "airport_name" }, { "id": 0, "type": "table", "value": "airport" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
2,043
legislator
bird:train.json:4762
List the full name of all the senior senators in year 2013.
SELECT T2.official_full_name FROM `current-terms` AS T1 INNER JOIN current AS T2 ON T2.bioguide_id = T1.bioguide WHERE T1.state_rank = 'senior' AND T1.type = 'sen' AND T1.start LIKE '2013%'
[ "List", "the", "full", "name", "of", "all", "the", "senior", "senators", "in", "year", "2013", "." ]
[ { "id": 0, "type": "column", "value": "official_full_name" }, { "id": 1, "type": "table", "value": "current-terms" }, { "id": 3, "type": "column", "value": "bioguide_id" }, { "id": 5, "type": "column", "value": "state_rank" }, { "id": 4, "type": "column", "value": "bioguide" }, { "id": 2, "type": "table", "value": "current" }, { "id": 6, "type": "value", "value": "senior" }, { "id": 9, "type": "column", "value": "start" }, { "id": 10, "type": "value", "value": "2013%" }, { "id": 7, "type": "column", "value": "type" }, { "id": 8, "type": "value", "value": "sen" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O" ]
2,044
farm
spider:train_spider.json:48
List the official names of cities that have not held any competition.
SELECT Official_Name FROM city WHERE City_ID NOT IN (SELECT Host_city_ID FROM farm_competition)
[ "List", "the", "official", "names", "of", "cities", "that", "have", "not", "held", "any", "competition", "." ]
[ { "id": 3, "type": "table", "value": "farm_competition" }, { "id": 1, "type": "column", "value": "official_name" }, { "id": 4, "type": "column", "value": "host_city_id" }, { "id": 2, "type": "column", "value": "city_id" }, { "id": 0, "type": "table", "value": "city" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
2,046
superhero
bird:dev.json:756
How many bad superheroes are there?
SELECT COUNT(T1.id) FROM superhero AS T1 INNER JOIN alignment AS T2 ON T1.alignment_id = T2.id WHERE T2.alignment = 'Bad'
[ "How", "many", "bad", "superheroes", "are", "there", "?" ]
[ { "id": 5, "type": "column", "value": "alignment_id" }, { "id": 0, "type": "table", "value": "superhero" }, { "id": 1, "type": "table", "value": "alignment" }, { "id": 2, "type": "column", "value": "alignment" }, { "id": 3, "type": "value", "value": "Bad" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O" ]
2,047
cre_Docs_and_Epenses
spider:train_spider.json:6447
What are the document ids for the budget type code 'SF'?
SELECT document_id FROM Documents_with_expenses WHERE budget_type_code = 'SF'
[ "What", "are", "the", "document", "ids", "for", "the", "budget", "type", "code", "'", "SF", "'", "?" ]
[ { "id": 0, "type": "table", "value": "documents_with_expenses" }, { "id": 2, "type": "column", "value": "budget_type_code" }, { "id": 1, "type": "column", "value": "document_id" }, { "id": 3, "type": "value", "value": "SF" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O" ]
2,048
driving_school
spider:train_spider.json:6646
How long is the total lesson time took by customer with first name as Rylan and last name as Goodwin?
SELECT sum(T1.lesson_time) FROM Lessons AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id WHERE T2.first_name = "Rylan" AND T2.last_name = "Goodwin";
[ "How", "long", "is", "the", "total", "lesson", "time", "took", "by", "customer", "with", "first", "name", "as", "Rylan", "and", "last", "name", "as", "Goodwin", "?" ]
[ { "id": 2, "type": "column", "value": "lesson_time" }, { "id": 3, "type": "column", "value": "customer_id" }, { "id": 4, "type": "column", "value": "first_name" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 6, "type": "column", "value": "last_name" }, { "id": 0, "type": "table", "value": "lessons" }, { "id": 7, "type": "column", "value": "Goodwin" }, { "id": 5, "type": "column", "value": "Rylan" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O" ]
2,049
election
spider:train_spider.json:2792
Show the people that have been governor the most times.
SELECT Governor FROM party GROUP BY Governor ORDER BY COUNT(*) DESC LIMIT 1
[ "Show", "the", "people", "that", "have", "been", "governor", "the", "most", "times", "." ]
[ { "id": 1, "type": "column", "value": "governor" }, { "id": 0, "type": "table", "value": "party" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
2,050
dorm_1
spider:train_spider.json:5720
Find the number of dorms and total capacity for each gender.
SELECT count(*) , sum(student_capacity) , gender FROM dorm GROUP BY gender
[ "Find", "the", "number", "of", "dorms", "and", "total", "capacity", "for", "each", "gender", "." ]
[ { "id": 2, "type": "column", "value": "student_capacity" }, { "id": 1, "type": "column", "value": "gender" }, { "id": 0, "type": "table", "value": "dorm" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
2,051
works_cycles
bird:train.json:7250
In 2007, which job position was hired the most?
SELECT JobTitle FROM Employee WHERE STRFTIME('%Y', HireDate) = '2007' GROUP BY HireDate ORDER BY COUNT(JobTitle) DESC LIMIT 1
[ "In", "2007", ",", "which", "job", "position", "was", "hired", "the", "most", "?" ]
[ { "id": 0, "type": "table", "value": "employee" }, { "id": 1, "type": "column", "value": "hiredate" }, { "id": 2, "type": "column", "value": "jobtitle" }, { "id": 3, "type": "value", "value": "2007" }, { "id": 4, "type": "value", "value": "%Y" } ]
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[ "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
2,052
works_cycles
bird:train.json:7110
Please list the family names of any employees whose middle names begin with C.
SELECT LastName FROM Person WHERE PersonType = 'EM' AND MiddleName LIKE 'C%'
[ "Please", "list", "the", "family", "names", "of", "any", "employees", "whose", "middle", "names", "begin", "with", "C." ]
[ { "id": 2, "type": "column", "value": "persontype" }, { "id": 4, "type": "column", "value": "middlename" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 0, "type": "table", "value": "person" }, { "id": 3, "type": "value", "value": "EM" }, { "id": 5, "type": "value", "value": "C%" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O" ]
2,053
planet_1
bird:test.json:1861
What is Turanga Leela's salary and position?
SELECT Salary , POSITION FROM Employee WHERE Name = "Turanga Leela";
[ "What", "is", "Turanga", "Leela", "'s", "salary", "and", "position", "?" ]
[ { "id": 4, "type": "column", "value": "Turanga Leela" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 2, "type": "column", "value": "position" }, { "id": 1, "type": "column", "value": "salary" }, { "id": 3, "type": "column", "value": "name" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
2,054
headphone_store
bird:test.json:919
Find the model of the most expensive headphone.
SELECT model FROM headphone ORDER BY price DESC LIMIT 1
[ "Find", "the", "model", "of", "the", "most", "expensive", "headphone", "." ]
[ { "id": 0, "type": "table", "value": "headphone" }, { "id": 1, "type": "column", "value": "model" }, { "id": 2, "type": "column", "value": "price" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
2,055
public_review_platform
bird:train.json:3833
What are the categories that business number 15 belongs to?
SELECT T2.category_name FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id WHERE T1.business_id = 15
[ "What", "are", "the", "categories", "that", "business", "number", "15", "belongs", "to", "?" ]
[ { "id": 1, "type": "table", "value": "business_categories" }, { "id": 0, "type": "column", "value": "category_name" }, { "id": 3, "type": "column", "value": "business_id" }, { "id": 5, "type": "column", "value": "category_id" }, { "id": 2, "type": "table", "value": "categories" }, { "id": 4, "type": "value", "value": "15" } ]
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[ "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O" ]
2,056
music_platform_2
bird:train.json:7958
What is the average rating of all the podcasts in category art?
SELECT AVG(T2.rating) FROM categories AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T1.category = 'arts'
[ "What", "is", "the", "average", "rating", "of", "all", "the", "podcasts", "in", "category", "art", "?" ]
[ { "id": 0, "type": "table", "value": "categories" }, { "id": 5, "type": "column", "value": "podcast_id" }, { "id": 2, "type": "column", "value": "category" }, { "id": 1, "type": "table", "value": "reviews" }, { "id": 4, "type": "column", "value": "rating" }, { "id": 3, "type": "value", "value": "arts" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-VALUE", "O" ]
2,057
hr_1
spider:train_spider.json:3455
display the country ID and number of cities for each country.
SELECT country_id , COUNT(*) FROM locations GROUP BY country_id
[ "display", "the", "country", "ID", "and", "number", "of", "cities", "for", "each", "country", "." ]
[ { "id": 1, "type": "column", "value": "country_id" }, { "id": 0, "type": "table", "value": "locations" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,058
disney
bird:train.json:4708
Which movies of director Wolfgang Reitherman do not have villain?
SELECT T1.movie_title FROM characters AS T1 INNER JOIN director AS T2 ON T1.movie_title = T2.name WHERE T2.director = 'Wolfgang Reitherman' AND T1.villian IS NULL
[ "Which", "movies", "of", "director", "Wolfgang", "Reitherman", "do", "not", "have", "villain", "?" ]
[ { "id": 5, "type": "value", "value": "Wolfgang Reitherman" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 2, "type": "table", "value": "director" }, { "id": 4, "type": "column", "value": "director" }, { "id": 6, "type": "column", "value": "villian" }, { "id": 3, "type": "column", "value": "name" } ]
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[ "O", "B-COLUMN", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "O", "O", "O", "B-COLUMN", "O" ]
2,059
inn_1
spider:train_spider.json:2612
Find the name of the room with the maximum occupancy.
SELECT roomName FROM Rooms ORDER BY maxOccupancy DESC LIMIT 1;
[ "Find", "the", "name", "of", "the", "room", "with", "the", "maximum", "occupancy", "." ]
[ { "id": 2, "type": "column", "value": "maxoccupancy" }, { "id": 1, "type": "column", "value": "roomname" }, { "id": 0, "type": "table", "value": "rooms" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
2,061
sales
bird:train.json:5440
In sales ID between 30 and 40, who is the customer that bought a total quantity of 403?
SELECT T2.FirstName, T2.LastName FROM Sales AS T1 INNER JOIN Customers AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.Quantity = 403 AND T1.SalesID BETWEEN 30 AND 40
[ "In", "sales", "ID", "between", "30", "and", "40", ",", "who", "is", "the", "customer", "that", "bought", "a", "total", "quantity", "of", "403", "?" ]
[ { "id": 4, "type": "column", "value": "customerid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 3, "type": "table", "value": "customers" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 5, "type": "column", "value": "quantity" }, { "id": 7, "type": "column", "value": "salesid" }, { "id": 2, "type": "table", "value": "sales" }, { "id": 6, "type": "value", "value": "403" }, { "id": 8, "type": "value", "value": "30" }, { "id": 9, "type": "value", "value": "40" } ]
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[ "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
2,062
toxicology
bird:dev.json:217
Identify all the atoms that are connected to the atoms of the TR181 molecule.
SELECT T2.atom_id, T2.atom_id2 FROM atom AS T1 INNER JOIN connected AS T2 ON T2.atom_id = T1.atom_id WHERE T1.molecule_id = 'TR181'
[ "Identify", "all", "the", "atoms", "that", "are", "connected", "to", "the", "atoms", "of", "the", "TR181", "molecule", "." ]
[ { "id": 4, "type": "column", "value": "molecule_id" }, { "id": 3, "type": "table", "value": "connected" }, { "id": 1, "type": "column", "value": "atom_id2" }, { "id": 0, "type": "column", "value": "atom_id" }, { "id": 5, "type": "value", "value": "TR181" }, { "id": 2, "type": "table", "value": "atom" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,063
customers_and_addresses
spider:train_spider.json:6094
For which countries are there more than four distinct addresses listed?
SELECT country FROM addresses GROUP BY country HAVING count(address_id) > 4
[ "For", "which", "countries", "are", "there", "more", "than", "four", "distinct", "addresses", "listed", "?" ]
[ { "id": 3, "type": "column", "value": "address_id" }, { "id": 0, "type": "table", "value": "addresses" }, { "id": 1, "type": "column", "value": "country" }, { "id": 2, "type": "value", "value": "4" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O" ]
2,064
hockey
bird:train.json:7748
What is the name of the coach whose team placed 4th in the 1969 game? Indicate their coachID.
SELECT T1.coachID FROM Coaches AS T1 INNER JOIN Teams AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.year = 1969 AND T2.rank = 4
[ "What", "is", "the", "name", "of", "the", "coach", "whose", "team", "placed", "4th", "in", "the", "1969", "game", "?", "Indicate", "their", "coachID", "." ]
[ { "id": 0, "type": "column", "value": "coachid" }, { "id": 1, "type": "table", "value": "coaches" }, { "id": 2, "type": "table", "value": "teams" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "1969" }, { "id": 5, "type": "column", "value": "rank" }, { "id": 7, "type": "column", "value": "tmid" }, { "id": 6, "type": "value", "value": "4" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
2,065
swimming
spider:train_spider.json:5631
What is the average capacity of the stadiums that were opened in year 2005?
SELECT avg(capacity) FROM stadium WHERE opening_year = 2005
[ "What", "is", "the", "average", "capacity", "of", "the", "stadiums", "that", "were", "opened", "in", "year", "2005", "?" ]
[ { "id": 1, "type": "column", "value": "opening_year" }, { "id": 3, "type": "column", "value": "capacity" }, { "id": 0, "type": "table", "value": "stadium" }, { "id": 2, "type": "value", "value": "2005" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
2,066
bike_share_1
bird:train.json:9058
How many bike stations are installed after August, 2013 in San Jose?
SELECT COUNT(installation_date) FROM station WHERE city = 'San Jose' AND (SUBSTR(CAST(installation_date AS TEXT), 1, INSTR(installation_date, '/') - 1) IN ('8', '9', '10', '11', '12') AND SUBSTR(CAST(installation_date AS TEXT), -4) = '2013') OR SUBSTR(CAST(installation_date AS TEXT), -4) > '2013'
[ "How", "many", "bike", "stations", "are", "installed", "after", "August", ",", "2013", "in", "San", "Jose", "?" ]
[ { "id": 1, "type": "column", "value": "installation_date" }, { "id": 4, "type": "value", "value": "San Jose" }, { "id": 0, "type": "table", "value": "station" }, { "id": 2, "type": "value", "value": "2013" }, { "id": 3, "type": "column", "value": "city" }, { "id": 5, "type": "value", "value": "-4" }, { "id": 8, "type": "value", "value": "10" }, { "id": 9, "type": "value", "value": "11" }, { "id": 10, "type": "value", "value": "12" }, { "id": 6, "type": "value", "value": "8" }, { "id": 7, "type": "value", "value": "9" }, { "id": 11, "type": "value", "value": "1" }, { "id": 12, "type": "value", "value": "/" } ]
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[ "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O", "B-VALUE", "I-VALUE", "O" ]
2,067
hockey
bird:train.json:7648
How many coaches worked a temporary term in the year 2007?
SELECT COUNT(coachID) FROM Coaches WHERE year = 2007 AND notes = 'interim'
[ "How", "many", "coaches", "worked", "a", "temporary", "term", "in", "the", "year", "2007", "?" ]
[ { "id": 0, "type": "table", "value": "coaches" }, { "id": 1, "type": "column", "value": "coachid" }, { "id": 5, "type": "value", "value": "interim" }, { "id": 4, "type": "column", "value": "notes" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "2007" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
2,068
ice_hockey_draft
bird:train.json:6983
Calculate the average weight in pounds of all players drafted by Arizona Coyotes.
SELECT CAST(SUM(T1.weight_in_lbs) AS REAL) / COUNT(T2.ELITEID) FROM weight_info AS T1 INNER JOIN PlayerInfo AS T2 ON T1.weight_id = T2.weight WHERE T2.overallby = 'Arizona Coyotes'
[ "Calculate", "the", "average", "weight", "in", "pounds", "of", "all", "players", "drafted", "by", "Arizona", "Coyotes", "." ]
[ { "id": 3, "type": "value", "value": "Arizona Coyotes" }, { "id": 7, "type": "column", "value": "weight_in_lbs" }, { "id": 0, "type": "table", "value": "weight_info" }, { "id": 1, "type": "table", "value": "playerinfo" }, { "id": 2, "type": "column", "value": "overallby" }, { "id": 4, "type": "column", "value": "weight_id" }, { "id": 6, "type": "column", "value": "eliteid" }, { "id": 5, "type": "column", "value": "weight" } ]
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[ "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O" ]
2,069
movie
bird:train.json:758
What is the percentage of the actors that showed up in the credit list of movie "Dawn of the Planet of the Apes" that were born after "1970/1/1"?
SELECT CAST(SUM(CASE WHEN T3.`Date of Birth` > '1970-01-01' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T3.`Date of Birth`) FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE T1.Title = 'Dawn of the Planet of the Apes'
[ "What", "is", "the", "percentage", "of", "the", "actors", "that", "showed", "up", "in", "the", "credit", "list", "of", "movie", "\"", "Dawn", "of", "the", "Planet", "of", "the", "Apes", "\"", "that", "were", "born", "after", "\"", "1970/1/1", "\"", "?" ]
[ { "id": 2, "type": "value", "value": "Dawn of the Planet of the Apes" }, { "id": 7, "type": "column", "value": "Date of Birth" }, { "id": 4, "type": "table", "value": "characters" }, { "id": 11, "type": "value", "value": "1970-01-01" }, { "id": 5, "type": "column", "value": "actorid" }, { "id": 8, "type": "column", "value": "movieid" }, { "id": 0, "type": "table", "value": "actor" }, { "id": 1, "type": "column", "value": "title" }, { "id": 3, "type": "table", "value": "movie" }, { "id": 6, "type": "value", "value": "100" }, { "id": 9, "type": "value", "value": "0" }, { "id": 10, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
2,070
retails
bird:train.json:6753
Among the customers in Asia, how many customers are in debt?
SELECT COUNT(T1.n_name) FROM nation AS T1 INNER JOIN customer AS T2 ON T1.n_nationkey = T2.c_nationkey INNER JOIN region AS T3 ON T1.n_regionkey = T3.r_regionkey WHERE T2.c_acctbal < 0 AND T3.r_name = 'ASIA'
[ "Among", "the", "customers", "in", "Asia", ",", "how", "many", "customers", "are", "in", "debt", "?" ]
[ { "id": 4, "type": "column", "value": "n_regionkey" }, { "id": 5, "type": "column", "value": "r_regionkey" }, { "id": 10, "type": "column", "value": "n_nationkey" }, { "id": 11, "type": "column", "value": "c_nationkey" }, { "id": 6, "type": "column", "value": "c_acctbal" }, { "id": 3, "type": "table", "value": "customer" }, { "id": 0, "type": "table", "value": "region" }, { "id": 1, "type": "column", "value": "n_name" }, { "id": 2, "type": "table", "value": "nation" }, { "id": 8, "type": "column", "value": "r_name" }, { "id": 9, "type": "value", "value": "ASIA" }, { "id": 7, "type": "value", "value": "0" } ]
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[ "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O" ]
2,071
image_and_language
bird:train.json:7474
How many images have over 20 object samples?
SELECT COUNT(T1.IMG_ID) FROM ( SELECT IMG_ID FROM IMG_OBJ GROUP BY IMG_ID HAVING COUNT(OBJ_SAMPLE_ID) > 20 ) T1
[ "How", "many", "images", "have", "over", "20", "object", "samples", "?" ]
[ { "id": 3, "type": "column", "value": "obj_sample_id" }, { "id": 1, "type": "table", "value": "img_obj" }, { "id": 0, "type": "column", "value": "img_id" }, { "id": 2, "type": "value", "value": "20" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 6, 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O" ]
2,072
tracking_grants_for_research
spider:train_spider.json:4380
What are the result description of the project whose detail is 'sint'?
SELECT T1.outcome_description FROM Research_outcomes AS T1 JOIN Project_outcomes AS T2 ON T1.outcome_code = T2.outcome_code JOIN Projects AS T3 ON T2.project_id = T3.project_id WHERE T3.project_details = 'sint'
[ "What", "are", "the", "result", "description", "of", "the", "project", "whose", "detail", "is", "'", "sint", "'", "?" ]
[ { "id": 0, "type": "column", "value": "outcome_description" }, { "id": 4, "type": "table", "value": "research_outcomes" }, { "id": 5, "type": "table", "value": "project_outcomes" }, { "id": 2, "type": "column", "value": "project_details" }, { "id": 7, "type": "column", "value": "outcome_code" }, { "id": 6, "type": "column", "value": "project_id" }, { "id": 1, "type": "table", "value": "projects" }, { "id": 3, "type": "value", "value": "sint" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O" ]
2,073
bike_share_1
bird:train.json:9016
What is the name of the station that is less used by customers who borrow bikes from? Indicate when was the station installed.
SELECT T1.start_station_name, T2.installation_date FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.subscription_type = 'Customer' GROUP BY T1.start_station_name ORDER BY COUNT(T1.subscription_type) LIMIT 1
[ "What", "is", "the", "name", "of", "the", "station", "that", "is", "less", "used", "by", "customers", "who", "borrow", "bikes", "from", "?", "Indicate", "when", "was", "the", "station", "installed", "." ]
[ { "id": 0, "type": "column", "value": "start_station_name" }, { "id": 1, "type": "column", "value": "installation_date" }, { "id": 4, "type": "column", "value": "subscription_type" }, { "id": 5, "type": "value", "value": "Customer" }, { "id": 3, "type": "table", "value": "station" }, { "id": 2, "type": "table", "value": "trip" }, { "id": 6, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
2,074
authors
bird:train.json:3592
What is the title of the paper that was written by Cheng Huang and affiliated with Microsoft?
SELECT T1.Title FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T2.Name = 'Cheng Huang' AND T2.Affiliation = 'Microsoft'
[ "What", "is", "the", "title", "of", "the", "paper", "that", "was", "written", "by", "Cheng", "Huang", "and", "affiliated", "with", "Microsoft", "?" ]
[ { "id": 2, "type": "table", "value": "paperauthor" }, { "id": 6, "type": "value", "value": "Cheng Huang" }, { "id": 7, "type": "column", "value": "affiliation" }, { "id": 8, "type": "value", "value": "Microsoft" }, { "id": 4, "type": "column", "value": "paperid" }, { "id": 0, "type": "column", "value": "title" }, { "id": 1, "type": "table", "value": "paper" }, { "id": 5, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
2,075
music_1
spider:train_spider.json:3537
List the name and country of origin for all singers who have produced songs with rating above 9.
SELECT DISTINCT T1.artist_name , T1.country FROM artist AS T1 JOIN song AS T2 ON T1.artist_name = T2.artist_name WHERE T2.rating > 9
[ "List", "the", "name", "and", "country", "of", "origin", "for", "all", "singers", "who", "have", "produced", "songs", "with", "rating", "above", "9", "." ]
[ { "id": 0, "type": "column", "value": "artist_name" }, { "id": 1, "type": "column", "value": "country" }, { "id": 2, "type": "table", "value": "artist" }, { "id": 4, "type": "column", "value": "rating" }, { "id": 3, "type": "table", "value": "song" }, { "id": 5, "type": "value", "value": "9" } ]
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[ "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
2,076
activity_1
spider:train_spider.json:6781
Show all the activity names and the number of faculty involved in each activity.
SELECT T1.activity_name , count(*) FROM Activity AS T1 JOIN Faculty_participates_in AS T2 ON T1.actID = T2.actID GROUP BY T1.actID
[ "Show", "all", "the", "activity", "names", "and", "the", "number", "of", "faculty", "involved", "in", "each", "activity", "." ]
[ { "id": 3, "type": "table", "value": "faculty_participates_in" }, { "id": 1, "type": "column", "value": "activity_name" }, { "id": 2, "type": "table", "value": "activity" }, { "id": 0, "type": "column", "value": "actid" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
2,077
apartment_rentals
spider:train_spider.json:1219
What are dates of birth of all the guests whose gender is "Male"?
SELECT date_of_birth FROM Guests WHERE gender_code = "Male"
[ "What", "are", "dates", "of", "birth", "of", "all", "the", "guests", "whose", "gender", "is", "\"", "Male", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "date_of_birth" }, { "id": 2, "type": "column", "value": "gender_code" }, { "id": 0, "type": "table", "value": "guests" }, { "id": 3, "type": "column", "value": "Male" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
2,078
hospital_1
spider:train_spider.json:3975
Which physician was trained in the procedure that costs the most.
SELECT T1.name FROM physician AS T1 JOIN trained_in AS T2 ON T1.employeeid = T2.physician JOIN procedures AS T3 ON T3.code = T2.treatment ORDER BY T3.cost DESC LIMIT 1
[ "Which", "physician", "was", "trained", "in", "the", "procedure", "that", "costs", "the", "most", "." ]
[ { "id": 1, "type": "table", "value": "procedures" }, { "id": 4, "type": "table", "value": "trained_in" }, { "id": 7, "type": "column", "value": "employeeid" }, { "id": 3, "type": "table", "value": "physician" }, { "id": 6, "type": "column", "value": "treatment" }, { "id": 8, "type": "column", "value": "physician" }, { "id": 0, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "cost" }, { "id": 5, "type": "column", "value": "code" } ]
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[ "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O" ]
2,079
school_player
spider:train_spider.json:4893
Which schools do not have any player? Give me the school locations.
SELECT LOCATION FROM school WHERE School_ID NOT IN (SELECT School_ID FROM Player)
[ "Which", "schools", "do", "not", "have", "any", "player", "?", "Give", "me", "the", "school", "locations", "." ]
[ { "id": 2, "type": "column", "value": "school_id" }, { "id": 1, "type": "column", "value": "location" }, { "id": 0, "type": "table", "value": "school" }, { "id": 3, "type": "table", "value": "player" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
2,080
address
bird:train.json:5088
Please list the names of all the counties with at least one residential area that implements daylight saving.
SELECT DISTINCT T2.county FROM zip_data AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T1.daylight_savings = 'Yes'
[ "Please", "list", "the", "names", "of", "all", "the", "counties", "with", "at", "least", "one", "residential", "area", "that", "implements", "daylight", "saving", "." ]
[ { "id": 3, "type": "column", "value": "daylight_savings" }, { "id": 1, "type": "table", "value": "zip_data" }, { "id": 5, "type": "column", "value": "zip_code" }, { "id": 2, "type": "table", "value": "country" }, { "id": 0, "type": "column", "value": "county" }, { "id": 4, "type": "value", "value": "Yes" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
2,081
aan_1
bird:test.json:1032
Count the number of collaborators that Mckeown , Kathleen has had .
select count (distinct t2.author_id) from author_list as t1 join author_list as t2 on t1.paper_id = t2.paper_id and t1.author_id != t2.author_id join author as t3 on t1.author_id = t3.author_id where t3.name = "mckeown , kathleen"
[ "Count", "the", "number", "of", "collaborators", "that", "Mckeown", ",", "Kathleen", "has", "had", "." ]
[ { "id": 2, "type": "column", "value": "mckeown , kathleen" }, { "id": 4, "type": "table", "value": "author_list" }, { "id": 3, "type": "column", "value": "author_id" }, { "id": 5, "type": "column", "value": "paper_id" }, { "id": 0, "type": "table", "value": "author" }, { "id": 1, "type": "column", "value": "name" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O" ]
2,082
shipping
bird:train.json:5617
How many shipments were shipped to the most densely populated city?
SELECT COUNT(*) FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id ORDER BY T2.area / T2.population DESC LIMIT 1
[ "How", "many", "shipments", "were", "shipped", "to", "the", "most", "densely", "populated", "city", "?" ]
[ { "id": 4, "type": "column", "value": "population" }, { "id": 0, "type": "table", "value": "shipment" }, { "id": 2, "type": "column", "value": "city_id" }, { "id": 1, "type": "table", "value": "city" }, { "id": 3, "type": "column", "value": "area" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O" ]
2,083
retails
bird:train.json:6867
Please list the names of the top 3 suppliers with the most amount of money in their accounts.
SELECT s_name FROM supplier ORDER BY s_acctbal DESC LIMIT 3
[ "Please", "list", "the", "names", "of", "the", "top", "3", "suppliers", "with", "the", "most", "amount", "of", "money", "in", "their", "accounts", "." ]
[ { "id": 2, "type": "column", "value": "s_acctbal" }, { "id": 0, "type": "table", "value": "supplier" }, { "id": 1, "type": "column", "value": "s_name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,084
cs_semester
bird:train.json:895
What are the GPAs of the unpaid Research Assistants?
SELECT T2.gpa FROM RA AS T1 INNER JOIN student AS T2 ON T1.student_id = T2.student_id WHERE T1.salary = 'free'
[ "What", "are", "the", "GPAs", "of", "the", "unpaid", "Research", "Assistants", "?" ]
[ { "id": 5, "type": "column", "value": "student_id" }, { "id": 2, "type": "table", "value": "student" }, { "id": 3, "type": "column", "value": "salary" }, { "id": 4, "type": "value", "value": "free" }, { "id": 0, "type": "column", "value": "gpa" }, { "id": 1, "type": "table", "value": "ra" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
2,086
race_track
spider:train_spider.json:757
Show the name, location, open year for all tracks with a seating higher than the average.
SELECT name , LOCATION , year_opened FROM track WHERE seating > (SELECT avg(seating) FROM track)
[ "Show", "the", "name", ",", "location", ",", "open", "year", "for", "all", "tracks", "with", "a", "seating", "higher", "than", "the", "average", "." ]
[ { "id": 3, "type": "column", "value": "year_opened" }, { "id": 2, "type": "column", "value": "location" }, { "id": 4, "type": "column", "value": "seating" }, { "id": 0, "type": "table", "value": "track" }, { "id": 1, "type": "column", "value": "name" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
2,087
store_1
spider:train_spider.json:596
How many employees live in Canada?
SELECT count(*) FROM employees WHERE country = "Canada";
[ "How", "many", "employees", "live", "in", "Canada", "?" ]
[ { "id": 0, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "country" }, { "id": 2, "type": "column", "value": "Canada" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
2,089
formula_1
bird:dev.json:938
Who was the champion of 2008's Australian Grand Prix and where can I know more about him?
SELECT T1.forename, T1.surname, T1.url FROM drivers AS T1 INNER JOIN results AS T2 ON T1.driverId = T2.driverId INNER JOIN races AS T3 ON T3.raceId = T2.raceId WHERE T3.name = 'Australian Grand Prix' AND T2.time LIKE '_:%:__.___' AND T3.year = 2008
[ "Who", "was", "the", "champion", "of", "2008", "'s", "Australian", "Grand", "Prix", "and", "where", "can", "I", "know", "more", "about", "him", "?" ]
[ { "id": 8, "type": "value", "value": "Australian Grand Prix" }, { "id": 10, "type": "value", "value": "_:%:__.___" }, { "id": 0, "type": "column", "value": "forename" }, { "id": 13, "type": "column", "value": "driverid" }, { "id": 1, "type": "column", "value": "surname" }, { "id": 4, "type": "table", "value": "drivers" }, { "id": 5, "type": "table", "value": "results" }, { "id": 6, "type": "column", "value": "raceid" }, { "id": 3, "type": "table", "value": "races" }, { "id": 7, "type": "column", "value": "name" }, { "id": 9, "type": "column", "value": "time" }, { "id": 11, "type": "column", "value": "year" }, { "id": 12, "type": "value", "value": "2008" }, { "id": 2, "type": "column", "value": "url" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,090
game_1
spider:train_spider.json:6026
What are the ids of all female students who play football?
SELECT StuID FROM Student WHERE sex = 'F' INTERSECT SELECT StuID FROM Sportsinfo WHERE sportname = "Football"
[ "What", "are", "the", "ids", "of", "all", "female", "students", "who", "play", "football", "?" ]
[ { "id": 1, "type": "table", "value": "sportsinfo" }, { "id": 5, "type": "column", "value": "sportname" }, { "id": 6, "type": "column", "value": "Football" }, { "id": 0, "type": "table", "value": "student" }, { "id": 2, "type": "column", "value": "stuid" }, { "id": 3, "type": "column", "value": "sex" }, { "id": 4, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
2,092
legislator
bird:train.json:4754
What is the average number of terms for a current female legislator?
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.gender_bio = 'F'
[ "What", "is", "the", "average", "number", "of", "terms", "for", "a", "current", "female", "legislator", "?" ]
[ { "id": 1, "type": "table", "value": "current-terms" }, { "id": 4, "type": "column", "value": "bioguide_id" }, { "id": 2, "type": "column", "value": "gender_bio" }, { "id": 5, "type": "column", "value": "bioguide" }, { "id": 0, "type": "table", "value": "current" }, { "id": 3, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
2,093
authors
bird:train.json:3619
List all the paper that were under the conference homepage URL "http://www.irma-international.org/".
SELECT T1.Title FROM Paper AS T1 INNER JOIN Conference AS T2 ON T1.ConferenceId = T2.Id WHERE T2.HomePage = 'http://www.irma-international.org/'
[ "List", "all", "the", "paper", "that", "were", "under", "the", "conference", "homepage", "URL", "\"", "http://www.irma-international.org/", "\"", "." ]
[ { "id": 4, "type": "value", "value": "http://www.irma-international.org/" }, { "id": 5, "type": "column", "value": "conferenceid" }, { "id": 2, "type": "table", "value": "conference" }, { "id": 3, "type": "column", "value": "homepage" }, { "id": 0, "type": "column", "value": "title" }, { "id": 1, "type": "table", "value": "paper" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O", "O" ]
2,094
retails
bird:train.json:6692
What is the nationality of "Customer#000000055"?
SELECT T2.n_name FROM customer AS T1 INNER JOIN nation AS T2 ON T1.c_name = 'Customer#000000055'
[ "What", "is", "the", "nationality", "of", "\"", "Customer#000000055", "\"", "?" ]
[ { "id": 4, "type": "value", "value": "Customer#000000055" }, { "id": 1, "type": "table", "value": "customer" }, { "id": 0, "type": "column", "value": "n_name" }, { "id": 2, "type": "table", "value": "nation" }, { "id": 3, "type": "column", "value": "c_name" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O" ]
2,095
food_inspection_2
bird:train.json:6110
Please list the full names of all the sanitarians under the supervision of Darlisha Jacobs.
SELECT first_name, last_name FROM employee WHERE title = 'Sanitarian' AND supervisor = ( SELECT employee_id FROM employee WHERE first_name = 'Darlisha' AND last_name = 'Jacobs' )
[ "Please", "list", "the", "full", "names", "of", "all", "the", "sanitarians", "under", "the", "supervision", "of", "Darlisha", "Jacobs", "." ]
[ { "id": 6, "type": "column", "value": "employee_id" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 4, "type": "value", "value": "Sanitarian" }, { "id": 5, "type": "column", "value": "supervisor" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 7, "type": "value", "value": "Darlisha" }, { "id": 8, "type": "value", "value": "Jacobs" }, { "id": 3, "type": "column", "value": "title" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-VALUE", "O" ]
2,096
real_estate_rentals
bird:test.json:1451
What are the user ids of property owners who have property photos, and how many do each of them have?
SELECT T1.owner_user_id , count(*) FROM Properties AS T1 JOIN Property_Photos AS T2 ON T1.property_id = T2.property_id GROUP BY T1.owner_user_id;
[ "What", "are", "the", "user", "ids", "of", "property", "owners", "who", "have", "property", "photos", ",", "and", "how", "many", "do", "each", "of", "them", "have", "?" ]
[ { "id": 2, "type": "table", "value": "property_photos" }, { "id": 0, "type": "column", "value": "owner_user_id" }, { "id": 3, "type": "column", "value": "property_id" }, { "id": 1, "type": "table", "value": "properties" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,097
bike_1
spider:train_spider.json:113
For each city, return the highest latitude among its stations.
SELECT city , max(lat) FROM station GROUP BY city
[ "For", "each", "city", ",", "return", "the", "highest", "latitude", "among", "its", "stations", "." ]
[ { "id": 0, "type": "table", "value": "station" }, { "id": 1, "type": "column", "value": "city" }, { "id": 2, "type": "column", "value": "lat" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
2,098
ice_hockey_draft
bird:train.json:6978
Who has played the most game plays in the 2000-2001 season of the International league?
SELECT DISTINCT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '2000-2001' AND T1.LEAGUE = 'International' ORDER BY T1.GP DESC LIMIT 1
[ "Who", "has", "played", "the", "most", "game", "plays", "in", "the", "2000", "-", "2001", "season", "of", "the", "International", "league", "?" ]
[ { "id": 8, "type": "value", "value": "International" }, { "id": 1, "type": "table", "value": "seasonstatus" }, { "id": 0, "type": "column", "value": "playername" }, { "id": 2, "type": "table", "value": "playerinfo" }, { "id": 6, "type": "value", "value": "2000-2001" }, { "id": 4, "type": "column", "value": "eliteid" }, { "id": 5, "type": "column", "value": "season" }, { "id": 7, "type": "column", "value": "league" }, { "id": 3, "type": "column", "value": "gp" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,099
tracking_grants_for_research
spider:train_spider.json:4365
What is the type of the document whose description starts with the word 'Initial'?
SELECT document_type_code FROM Document_Types WHERE document_description LIKE 'Initial%'
[ "What", "is", "the", "type", "of", "the", "document", "whose", "description", "starts", "with", "the", "word", "'", "Initial", "'", "?" ]
[ { "id": 2, "type": "column", "value": "document_description" }, { "id": 1, "type": "column", "value": "document_type_code" }, { "id": 0, "type": "table", "value": "document_types" }, { "id": 3, "type": "value", "value": "Initial%" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
2,100
sports_competition
spider:train_spider.json:3369
List the types of competition that have at most five competitions of that type.
SELECT Competition_type FROM competition GROUP BY Competition_type HAVING COUNT(*) <= 5
[ "List", "the", "types", "of", "competition", "that", "have", "at", "most", "five", "competitions", "of", "that", "type", "." ]
[ { "id": 1, "type": "column", "value": "competition_type" }, { "id": 0, "type": "table", "value": "competition" }, { "id": 2, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
2,101
legislator
bird:train.json:4860
State all the Facebook ID for current legislators under the democrat party.
SELECT T2.facebook_id FROM `current-terms` AS T1 INNER JOIN `social-media` AS T2 ON T1.bioguide = T2.bioguide WHERE T1.party = 'Democrat' GROUP BY T2.facebook_id
[ "State", "all", "the", "Facebook", "ID", "for", "current", "legislators", "under", "the", "democrat", "party", "." ]
[ { "id": 1, "type": "table", "value": "current-terms" }, { "id": 2, "type": "table", "value": "social-media" }, { "id": 0, "type": "column", "value": "facebook_id" }, { "id": 4, "type": "value", "value": "Democrat" }, { "id": 5, "type": "column", "value": "bioguide" }, { "id": 3, "type": "column", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "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", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,102
customers_and_orders
bird:test.json:274
Give the address, phone, and email for customers with the name Jeromy.
SELECT customer_address , customer_phone , customer_email FROM Customers WHERE customer_name = "Jeromy"
[ "Give", "the", "address", ",", "phone", ",", "and", "email", "for", "customers", "with", "the", "name", "Jeromy", "." ]
[ { "id": 1, "type": "column", "value": "customer_address" }, { "id": 2, "type": "column", "value": "customer_phone" }, { "id": 3, "type": "column", "value": "customer_email" }, { "id": 4, "type": "column", "value": "customer_name" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 5, "type": "column", "value": "Jeromy" } ]
[ { "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": [] }, { "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", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
2,104
movie_3
bird:train.json:9289
What is the rental price per day for Airplane Sierra?
SELECT rental_rate / rental_duration AS result FROM film WHERE title = 'AIRPLANE SIERRA'
[ "What", "is", "the", "rental", "price", "per", "day", "for", "Airplane", "Sierra", "?" ]
[ { "id": 2, "type": "value", "value": "AIRPLANE SIERRA" }, { "id": 4, "type": "column", "value": "rental_duration" }, { "id": 3, "type": "column", "value": "rental_rate" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8, 9 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
2,105
world_development_indicators
bird:train.json:2222
In Sub-Saharan Africa, how many female out-of-school children of primary school age are there in the country with the higest number of female out-of-school children of primary school age? Indicate the year of when it was recorded.
SELECT MAX(T1.value), T1.year FROM indicators AS T1 INNER JOIN country AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Region = 'Sub-Saharan Africa' AND T1.IndicatorName = 'Out-of-school children of primary school age, female (number)'
[ "In", "Sub", "-", "Saharan", "Africa", ",", "how", "many", "female", "out", "-", "of", "-", "school", "children", "of", "primary", "school", "age", "are", "there", "in", "the", "country", "with", "the", "higest", "number", "of", "female", "out", "-", "of", "-", "school", "children", "of", "primary", "school", "age", "?", "Indicate", "the", "year", "of", "when", "it", "was", "recorded", "." ]
[ { "id": 8, "type": "value", "value": "Out-of-school children of primary school age, female (number)" }, { "id": 6, "type": "value", "value": "Sub-Saharan Africa" }, { "id": 7, "type": "column", "value": "indicatorname" }, { "id": 4, "type": "column", "value": "countrycode" }, { "id": 1, "type": "table", "value": "indicators" }, { "id": 2, "type": "table", "value": "country" }, { "id": 5, "type": "column", "value": "region" }, { "id": 3, "type": "column", "value": "value" }, { "id": 0, "type": "column", "value": "year" } ]
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[ "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
2,106
disney
bird:train.json:4679
What proportion of the total gross of all movies is from movies with songs?
SELECT CAST(COUNT(CASE WHEN T1.song IS NOT NULL THEN T2.movie_title ELSE NULL END) AS REAL) * 100 / COUNT(T2.movie_title) FROM characters AS T1 INNER JOIN movies_total_gross AS T2 ON T1.movie_title = T2.movie_title
[ "What", "proportion", "of", "the", "total", "gross", "of", "all", "movies", "is", "from", "movies", "with", "songs", "?" ]
[ { "id": 1, "type": "table", "value": "movies_total_gross" }, { "id": 2, "type": "column", "value": "movie_title" }, { "id": 0, "type": "table", "value": "characters" }, { "id": 4, "type": "column", "value": "song" }, { "id": 3, "type": "value", "value": "100" } ]
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[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
2,107
chicago_crime
bird:train.json:8585
How many community areas are there in Central Chicago?
SELECT COUNT(*) FROM Community_Area WHERE side = 'Central'
[ "How", "many", "community", "areas", "are", "there", "in", "Central", "Chicago", "?" ]
[ { "id": 0, "type": "table", "value": "community_area" }, { "id": 2, "type": "value", "value": "Central" }, { "id": 1, "type": "column", "value": "side" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-VALUE", "O", "O" ]
2,108
public_review_platform
bird:train.json:3796
How many active businesses of city are underrated?
SELECT COUNT(business_id) FROM Business WHERE review_count LIKE 'Low' AND active LIKE 'TRUE'
[ "How", "many", "active", "businesses", "of", "city", "are", "underrated", "?" ]
[ { "id": 2, "type": "column", "value": "review_count" }, { "id": 1, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "business" }, { "id": 4, "type": "column", "value": "active" }, { "id": 5, "type": "value", "value": "TRUE" }, { "id": 3, "type": "value", "value": "Low" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 0 ] }, { "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": [] } ]
[ "B-VALUE", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O" ]
2,109
world_development_indicators
bird:train.json:2227
Which country has the highest population in largest city for 19 consecutive years starting from 1960? Indicate the region to which the country is located.
SELECT T2.CountryCode, T2.Region FROM Indicators AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.IndicatorName = 'Population in largest city' AND T1.Year >= 1960 AND T1.Year < 1980 ORDER BY T2.Region DESC LIMIT 1
[ "Which", "country", "has", "the", "highest", "population", "in", "largest", "city", "for", "19", "consecutive", "years", "starting", "from", "1960", "?", "Indicate", "the", "region", "to", "which", "the", "country", "is", "located", "." ]
[ { "id": 5, "type": "value", "value": "Population in largest city" }, { "id": 4, "type": "column", "value": "indicatorname" }, { "id": 0, "type": "column", "value": "countrycode" }, { "id": 2, "type": "table", "value": "indicators" }, { "id": 3, "type": "table", "value": "country" }, { "id": 1, "type": "column", "value": "region" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "1960" }, { "id": 8, "type": "value", "value": "1980" } ]
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[ "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
2,110
solvency_ii
spider:train_spider.json:4589
Show different type codes of products and the number of products with each type code.
SELECT Product_Type_Code , COUNT(*) FROM Products GROUP BY Product_Type_Code
[ "Show", "different", "type", "codes", "of", "products", "and", "the", "number", "of", "products", "with", "each", "type", "code", "." ]
[ { "id": 1, "type": "column", "value": "product_type_code" }, { "id": 0, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
2,111
cs_semester
bird:train.json:945
Among the students with less than four intelligence, list the full name and phone number of students with a greater than 3 GPA.
SELECT f_name, l_name, phone_number FROM student WHERE gpa > 3 AND intelligence < 4
[ "Among", "the", "students", "with", "less", "than", "four", "intelligence", ",", "list", "the", "full", "name", "and", "phone", "number", "of", "students", "with", "a", "greater", "than", "3", "GPA", "." ]
[ { "id": 3, "type": "column", "value": "phone_number" }, { "id": 6, "type": "column", "value": "intelligence" }, { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "f_name" }, { "id": 2, "type": "column", "value": "l_name" }, { "id": 4, "type": "column", "value": "gpa" }, { "id": 5, "type": "value", "value": "3" }, { "id": 7, "type": "value", "value": "4" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,112
law_episode
bird:train.json:1274
How many awards has Julia Roberts been nominated for?
SELECT COUNT(T2.award_id) FROM Person AS T1 INNER JOIN Award AS T2 ON T1.person_id = T2.person_id WHERE T1.name = 'Julia Roberts' AND T2.result = 'Nominee'
[ "How", "many", "awards", "has", "Julia", "Roberts", "been", "nominated", "for", "?" ]
[ { "id": 5, "type": "value", "value": "Julia Roberts" }, { "id": 3, "type": "column", "value": "person_id" }, { "id": 2, "type": "column", "value": "award_id" }, { "id": 7, "type": "value", "value": "Nominee" }, { "id": 0, "type": "table", "value": "person" }, { "id": 6, "type": "column", "value": "result" }, { "id": 1, "type": "table", "value": "award" }, { "id": 4, "type": "column", "value": "name" } ]
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[ "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O", "O" ]
2,113
student_loan
bird:train.json:4464
How many of the students joined two organization?
SELECT COUNT(name) FROM enlist WHERE organ >= 2
[ "How", "many", "of", "the", "students", "joined", "two", "organization", "?" ]
[ { "id": 0, "type": "table", "value": "enlist" }, { "id": 1, "type": "column", "value": "organ" }, { "id": 3, "type": "column", "value": "name" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
2,114
college_3
spider:train_spider.json:4672
What is the name of the department with the most students minoring in it?
SELECT T1.DName FROM DEPARTMENT AS T1 JOIN MINOR_IN AS T2 ON T1.DNO = T2.DNO GROUP BY T2.DNO ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "department", "with", "the", "most", "students", "minoring", "in", "it", "?" ]
[ { "id": 2, "type": "table", "value": "department" }, { "id": 3, "type": "table", "value": "minor_in" }, { "id": 1, "type": "column", "value": "dname" }, { "id": 0, "type": "column", "value": "dno" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
2,115
art_1
bird:test.json:1286
What are the maximum height and id of paintings painted before 1900?
SELECT max(height_mm) , paintingID FROM paintings WHERE YEAR < 1900
[ "What", "are", "the", "maximum", "height", "and", "i", "d", "of", "paintings", "painted", "before", "1900", "?" ]
[ { "id": 1, "type": "column", "value": "paintingid" }, { "id": 0, "type": "table", "value": "paintings" }, { "id": 4, "type": "column", "value": "height_mm" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "1900" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
2,116
hockey
bird:train.json:7655
Among the people who got into the Hall of Fame after the year 1980, how many of them belong to the category of "Player"?
SELECT COUNT(hofID) FROM HOF WHERE year > 1980 AND category = 'Player'
[ "Among", "the", "people", "who", "got", "into", "the", "Hall", "of", "Fame", "after", "the", "year", "1980", ",", "how", "many", "of", "them", "belong", "to", "the", "category", "of", "\"", "Player", "\"", "?" ]
[ { "id": 4, "type": "column", "value": "category" }, { "id": 5, "type": "value", "value": "Player" }, { "id": 1, "type": "column", "value": "hofid" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "1980" }, { "id": 0, "type": "table", "value": "hof" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O" ]
2,117
hockey
bird:train.json:7719
What is the percentage of winning rate of improvement since Alain Vigneault became the coach of Vancouver Canucks in 2006 season?
SELECT SUM(CASE WHEN T1.year = 2006 THEN CAST(T1.W AS REAL) * 100 / (T1.W + T1.L) ELSE 0 END) - ( SELECT CAST(W AS REAL) * 100 / (W + L) FROM Teams WHERE year = '2005' AND name = 'Vancouver Canucks' ) FROM Teams AS T1 INNER JOIN Coaches AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year INNER JOIN Master AS T3 ON T2.coachID = T3.coachID WHERE T1.name = 'Vancouver Canucks' AND T3.firstName = 'Alain' AND T3.lastName = 'Vigneault'
[ "What", "is", "the", "percentage", "of", "winning", "rate", "of", "improvement", "since", "Alain", "Vigneault", "became", "the", "coach", "of", "Vancouver", "Canucks", "in", "2006", "season", "?" ]
[ { "id": 5, "type": "value", "value": "Vancouver Canucks" }, { "id": 6, "type": "column", "value": "firstname" }, { "id": 9, "type": "value", "value": "Vigneault" }, { "id": 8, "type": "column", "value": "lastname" }, { "id": 2, "type": "table", "value": "coaches" }, { "id": 3, "type": "column", "value": "coachid" }, { "id": 0, "type": "table", "value": "master" }, { "id": 1, "type": "table", "value": "teams" }, { "id": 7, "type": "value", "value": "Alain" }, { "id": 4, "type": "column", "value": "name" }, { "id": 11, "type": "column", "value": "tmid" }, { "id": 12, "type": "column", "value": "year" }, { "id": 13, "type": "value", "value": "2006" }, { "id": 14, "type": "value", "value": "2005" }, { "id": 15, "type": "value", "value": "100" }, { "id": 10, "type": "value", "value": "0" }, { "id": 16, "type": "column", "value": "w" }, { "id": 17, "type": "column", "value": "l" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-VALUE", "B-COLUMN", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O", "O" ]
2,118
school_bus
spider:train_spider.json:6348
How many drivers are there?
SELECT count(*) FROM driver
[ "How", "many", "drivers", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "driver" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O" ]
2,119
voter_2
spider:train_spider.json:5499
What are the distinct last names of the students who have president votes and have 8741 as the advisor?
SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote INTERSECT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "8741"
[ "What", "are", "the", "distinct", "last", "names", "of", "the", "students", "who", "have", "president", "votes", "and", "have", "8741", "as", "the", "advisor", "?" ]
[ { "id": 6, "type": "column", "value": "president_vote" }, { "id": 2, "type": "table", "value": "voting_record" }, { "id": 0, "type": "table", "value": "student" }, { "id": 3, "type": "column", "value": "advisor" }, { "id": 1, "type": "column", "value": "lname" }, { "id": 5, "type": "column", "value": "stuid" }, { "id": 4, "type": "column", "value": "8741" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
2,120
game_1
spider:train_spider.json:6037
Show ids of students who play video game and play sports.
SELECT StuID FROM Sportsinfo INTERSECT SELECT StuID FROM Plays_games
[ "Show", "ids", "of", "students", "who", "play", "video", "game", "and", "play", "sports", "." ]
[ { "id": 1, "type": "table", "value": "plays_games" }, { "id": 0, "type": "table", "value": "sportsinfo" }, { "id": 2, "type": "column", "value": "stuid" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 5, 6, 7 ] }, { "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", "I-TABLE", "I-TABLE", "O", "O", "B-TABLE", "O" ]
2,121
planet_1
bird:test.json:1918
What are the package numbers and weights that are between 10 and 30?
SELECT PackageNumber , Weight FROM PACKAGE WHERE Weight BETWEEN 10 AND 30;
[ "What", "are", "the", "package", "numbers", "and", "weights", "that", "are", "between", "10", "and", "30", "?" ]
[ { "id": 1, "type": "column", "value": "packagenumber" }, { "id": 0, "type": "table", "value": "package" }, { "id": 2, "type": "column", "value": "weight" }, { "id": 3, "type": "value", "value": "10" }, { "id": 4, "type": "value", "value": "30" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
2,122
debit_card_specializing
bird:dev.json:1478
Which segment had the least consumption?
SELECT T1.Segment FROM customers AS T1 INNER JOIN yearmonth AS T2 ON T1.CustomerID = T2.CustomerID GROUP BY T1.Segment ORDER BY SUM(T2.Consumption) ASC LIMIT 1
[ "Which", "segment", "had", "the", "least", "consumption", "?" ]
[ { "id": 4, "type": "column", "value": "consumption" }, { "id": 3, "type": "column", "value": "customerid" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "yearmonth" }, { "id": 0, "type": "column", "value": "segment" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O" ]
2,123
shop_membership
spider:train_spider.json:5425
What are the names of the members that have never registered at any branch?
SELECT name FROM member WHERE member_id NOT IN (SELECT member_id FROM membership_register_branch)
[ "What", "are", "the", "names", "of", "the", "members", "that", "have", "never", "registered", "at", "any", "branch", "?" ]
[ { "id": 3, "type": "table", "value": "membership_register_branch" }, { "id": 2, "type": "column", "value": "member_id" }, { "id": 0, "type": "table", "value": "member" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10, 11, 12, 13 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "I-TABLE", "I-TABLE", "O" ]
2,124
image_and_language
bird:train.json:7537
How many attributes are related to the object sample no. 7 on image no. 4?
SELECT COUNT(ATT_CLASS_ID) FROM IMG_OBJ_ATT WHERE IMG_ID = 4 AND OBJ_SAMPLE_ID = 7
[ "How", "many", "attributes", "are", "related", "to", "the", "object", "sample", "no", ".", "7", "on", "image", "no", ".", "4", "?" ]
[ { "id": 4, "type": "column", "value": "obj_sample_id" }, { "id": 1, "type": "column", "value": "att_class_id" }, { "id": 0, "type": "table", "value": "img_obj_att" }, { "id": 2, "type": "column", "value": "img_id" }, { "id": 3, "type": "value", "value": "4" }, { "id": 5, "type": "value", "value": "7" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 16 ] }, { "entity_id": 4, "token_idxs": [ 7, 8 ] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O" ]
2,125
company_office
spider:train_spider.json:4556
Count the number of distinct company industries.
SELECT count(DISTINCT Industry) FROM Companies
[ "Count", "the", "number", "of", "distinct", "company", "industries", "." ]
[ { "id": 0, "type": "table", "value": "companies" }, { "id": 1, "type": "column", "value": "industry" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
2,126
planet_1
bird:test.json:1887
What are the Coordinates of planet Mars?
SELECT Coordinates FROM Planet WHERE Name = "Mars";
[ "What", "are", "the", "Coordinates", "of", "planet", "Mars", "?" ]
[ { "id": 1, "type": "column", "value": "coordinates" }, { "id": 0, "type": "table", "value": "planet" }, { "id": 2, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "Mars" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O" ]
2,127
wrestler
spider:train_spider.json:1872
Please show the most common reigns of wrestlers.
SELECT Reign FROM wrestler GROUP BY Reign ORDER BY COUNT(*) DESC LIMIT 1
[ "Please", "show", "the", "most", "common", "reigns", "of", "wrestlers", "." ]
[ { "id": 0, "type": "table", "value": "wrestler" }, { "id": 1, "type": "column", "value": "reign" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
2,128
european_football_1
bird:train.json:2788
How many matches of the Bundesliga division ended with an away victory in the 2021 season?
SELECT COUNT(T1.Div) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.name = 'Bundesliga' AND T1.FTR = 'A' AND T1.season = 2021
[ "How", "many", "matches", "of", "the", "Bundesliga", "division", "ended", "with", "an", "away", "victory", "in", "the", "2021", "season", "?" ]
[ { "id": 5, "type": "value", "value": "Bundesliga" }, { "id": 1, "type": "table", "value": "divisions" }, { "id": 3, "type": "column", "value": "division" }, { "id": 0, "type": "table", "value": "matchs" }, { "id": 8, "type": "column", "value": "season" }, { "id": 4, "type": "column", "value": "name" }, { "id": 9, "type": "value", "value": "2021" }, { "id": 2, "type": "column", "value": "div" }, { "id": 6, "type": "column", "value": "ftr" }, { "id": 7, "type": "value", "value": "A" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 9 ] }, { "entity_id": 8, "token_idxs": [ 15 ] }, { "entity_id": 9, "token_idxs": [ 14 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
2,129
legislator
bird:train.json:4901
Among all the current legislators who have served for more than 4 terms, what is the percentage of them being female?
SELECT CAST(SUM(CASE WHEN gender_bio = 'F' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T3.bioguide) FROM ( SELECT T2.bioguide, T1.gender_bio FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide GROUP BY T2.bioguide HAVING COUNT(T2.bioguide) > 4 ) T3
[ "Among", "all", "the", "current", "legislators", "who", "have", "served", "for", "more", "than", "4", "terms", ",", "what", "is", "the", "percentage", "of", "them", "being", "female", "?" ]
[ { "id": 4, "type": "table", "value": "current-terms" }, { "id": 6, "type": "column", "value": "bioguide_id" }, { "id": 2, "type": "column", "value": "gender_bio" }, { "id": 0, "type": "column", "value": "bioguide" }, { "id": 3, "type": "table", "value": "current" }, { "id": 1, "type": "value", "value": "100" }, { "id": 5, "type": "value", "value": "4" }, { "id": 7, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" }, { "id": 9, "type": "value", "value": "F" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 18 ] }, { "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", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
2,130
talkingdata
bird:train.json:1180
Which phone brand and model was used for event ID "6701"?
SELECT T2.phone_brand, T2.device_model FROM events AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.event_id = 6701
[ "Which", "phone", "brand", "and", "model", "was", "used", "for", "event", "ID", "\"", "6701", "\"", "?" ]
[ { "id": 3, "type": "table", "value": "phone_brand_device_model2" }, { "id": 1, "type": "column", "value": "device_model" }, { "id": 0, "type": "column", "value": "phone_brand" }, { "id": 6, "type": "column", "value": "device_id" }, { "id": 4, "type": "column", "value": "event_id" }, { "id": 2, "type": "table", "value": "events" }, { "id": 5, "type": "value", "value": "6701" } ]
[ { "entity_id": 0, "token_idxs": [ 1, 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "I-COLUMN", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
2,131
cre_Students_Information_Systems
bird:test.json:512
What are the start time and end time of addresses for the students who receive 2 transcripts?
SELECT date_from , date_to FROM Students_Addresses WHERE student_id IN ( SELECT student_id FROM Transcripts GROUP BY student_id HAVING count(*) = 2 )
[ "What", "are", "the", "start", "time", "and", "end", "time", "of", "addresses", "for", "the", "students", "who", "receive", "2", "transcripts", "?" ]
[ { "id": 0, "type": "table", "value": "students_addresses" }, { "id": 4, "type": "table", "value": "transcripts" }, { "id": 3, "type": "column", "value": "student_id" }, { "id": 1, "type": "column", "value": "date_from" }, { "id": 2, "type": "column", "value": "date_to" }, { "id": 5, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "B-TABLE", "O" ]
2,132
customers_card_transactions
spider:train_spider.json:704
Return the full name and phone of the customer who has card number 4560596484842.
SELECT T2.customer_first_name , T2.customer_last_name , T2.customer_phone FROM Customers_cards AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id WHERE T1.card_number = "4560596484842"
[ "Return", "the", "full", "name", "and", "phone", "of", "the", "customer", "who", "has", "card", "number", "4560596484842", "." ]
[ { "id": 0, "type": "column", "value": "customer_first_name" }, { "id": 1, "type": "column", "value": "customer_last_name" }, { "id": 3, "type": "table", "value": "customers_cards" }, { "id": 2, "type": "column", "value": "customer_phone" }, { "id": 6, "type": "column", "value": "4560596484842" }, { "id": 5, "type": "column", "value": "card_number" }, { "id": 7, "type": "column", "value": "customer_id" }, { "id": 4, "type": "table", "value": "customers" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
2,133
retail_world
bird:train.json:6650
List down the company names which supplied products for the order on 14th August, 1996.
SELECT T1.CompanyName FROM Suppliers AS T1 INNER JOIN Products AS T2 ON T1.SupplierID = T2.SupplierID INNER JOIN `Order Details` AS T3 ON T2.ProductID = T3.ProductID INNER JOIN Orders AS T4 ON T3.OrderID = T4.OrderID WHERE date(T4.OrderDate) = '1996-08-14'
[ "List", "down", "the", "company", "names", "which", "supplied", "products", "for", "the", "order", "on", "14th", "August", ",", "1996", "." ]
[ { "id": 3, "type": "table", "value": "Order Details" }, { "id": 0, "type": "column", "value": "companyname" }, { "id": 2, "type": "value", "value": "1996-08-14" }, { "id": 9, "type": "column", "value": "supplierid" }, { "id": 5, "type": "column", "value": "orderdate" }, { "id": 6, "type": "table", "value": "suppliers" }, { "id": 8, "type": "column", "value": "productid" }, { "id": 7, "type": "table", "value": "products" }, { "id": 4, "type": "column", "value": "orderid" }, { "id": 1, "type": "table", "value": "orders" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
2,134
chicago_crime
bird:train.json:8657
Calculate the percentage of the domestic violence cases handled by Christopher Taliaferro. Among them, list report numbers of cases that happened in the bank.
SELECT CAST(COUNT(CASE WHEN T1.domestic = 'TRUE' THEN T1.report_no END) AS REAL) * 100 / COUNT(T1.report_no), COUNT(CASE WHEN T1.domestic = 'TRUE' AND T1.location_description = 'BANK' THEN T1.report_no END) AS "number" FROM Crime AS T1 INNER JOIN Ward AS T2 ON T2.ward_no = T1.ward_no WHERE T2.alderman_first_name = 'Christopher' AND T2.alderman_last_name = 'Taliaferro'
[ "Calculate", "the", "percentage", "of", "the", "domestic", "violence", "cases", "handled", "by", "Christopher", "Taliaferro", ".", "Among", "them", ",", "list", "report", "numbers", "of", "cases", "that", "happened", "in", "the", "bank", "." ]
[ { "id": 11, "type": "column", "value": "location_description" }, { "id": 3, "type": "column", "value": "alderman_first_name" }, { "id": 5, "type": "column", "value": "alderman_last_name" }, { "id": 4, "type": "value", "value": "Christopher" }, { "id": 6, "type": "value", "value": "Taliaferro" }, { "id": 8, "type": "column", "value": "report_no" }, { "id": 9, "type": "column", "value": "domestic" }, { "id": 2, "type": "column", "value": "ward_no" }, { "id": 0, "type": "table", "value": "crime" }, { "id": 1, "type": "table", "value": "ward" }, { "id": 10, "type": "value", "value": "TRUE" }, { "id": 12, "type": "value", "value": "BANK" }, { "id": 7, "type": "value", "value": "100" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 11 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 17 ] }, { "entity_id": 9, "token_idxs": [ 5 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [ 25 ] }, { "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", "B-VALUE", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
2,135
sales
bird:train.json:5422
Please provide sales ID for products named Hex Nut with a price greater than 100.
SELECT T2.SalesID FROM Products AS T1 INNER JOIN Sales AS T2 ON T1.ProductID = T2.ProductID WHERE T1.Name LIKE 'Hex Nut%' AND T1.Price > 100
[ "Please", "provide", "sales", "ID", "for", "products", "named", "Hex", "Nut", "with", "a", "price", "greater", "than", "100", "." ]
[ { "id": 3, "type": "column", "value": "productid" }, { "id": 1, "type": "table", "value": "products" }, { "id": 5, "type": "value", "value": "Hex Nut%" }, { "id": 0, "type": "column", "value": "salesid" }, { "id": 2, "type": "table", "value": "sales" }, { "id": 6, "type": "column", "value": "price" }, { "id": 4, "type": "column", "value": "name" }, { "id": 7, "type": "value", "value": "100" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [ 7, 8 ] }, { "entity_id": 6, "token_idxs": [ 11 ] }, { "entity_id": 7, "token_idxs": [ 14 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "I-VALUE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
2,136
video_games
bird:train.json:3493
What is the genre of the game ID 119?
SELECT T2.genre_name FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T1.id = 119
[ "What", "is", "the", "genre", "of", "the", "game", "ID", "119", "?" ]
[ { "id": 0, "type": "column", "value": "genre_name" }, { "id": 5, "type": "column", "value": "genre_id" }, { "id": 2, "type": "table", "value": "genre" }, { "id": 1, "type": "table", "value": "game" }, { "id": 4, "type": "value", "value": "119" }, { "id": 3, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O" ]
2,137
advertising_agencies
bird:test.json:2072
What are the agency details for clients with the detail Mac?
SELECT T2.agency_details FROM Clients AS T1 JOIN Agencies AS T2 ON T1.agency_id = T2.agency_id WHERE T1.client_details = 'Mac'
[ "What", "are", "the", "agency", "details", "for", "clients", "with", "the", "detail", "Mac", "?" ]
[ { "id": 0, "type": "column", "value": "agency_details" }, { "id": 3, "type": "column", "value": "client_details" }, { "id": 5, "type": "column", "value": "agency_id" }, { "id": 2, "type": "table", "value": "agencies" }, { "id": 1, "type": "table", "value": "clients" }, { "id": 4, "type": "value", "value": "Mac" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
2,138
synthea
bird:train.json:1459
What is the average body weight of Asian patients?
SELECT SUM(T2.VALUE) / COUNT(T1.patient) FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T1.race = 'asian' AND T2.DESCRIPTION = 'Body Weight' AND T2.UNITS = 'kg'
[ "What", "is", "the", "average", "body", "weight", "of", "Asian", "patients", "?" ]
[ { "id": 1, "type": "table", "value": "observations" }, { "id": 5, "type": "column", "value": "description" }, { "id": 6, "type": "value", "value": "Body Weight" }, { "id": 0, "type": "table", "value": "patients" }, { "id": 2, "type": "column", "value": "patient" }, { "id": 4, "type": "value", "value": "asian" }, { "id": 7, "type": "column", "value": "units" }, { "id": 9, "type": "column", "value": "value" }, { "id": 3, "type": "column", "value": "race" }, { "id": 8, "type": "value", "value": "kg" } ]
[ { "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": [ 7 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 4, 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "B-COLUMN", "O" ]
2,139
retail_world
bird:train.json:6607
What is the full address of Rattlesnake Canyon Grocery?
SELECT DISTINCT ShipAddress, ShipCity, ShipRegion, ShipPostalCode, ShipCountry FROM Orders WHERE ShipName = 'Rattlesnake Canyon Grocery'
[ "What", "is", "the", "full", "address", "of", "Rattlesnake", "Canyon", "Grocery", "?" ]
[ { "id": 7, "type": "value", "value": "Rattlesnake Canyon Grocery" }, { "id": 4, "type": "column", "value": "shippostalcode" }, { "id": 1, "type": "column", "value": "shipaddress" }, { "id": 5, "type": "column", "value": "shipcountry" }, { "id": 3, "type": "column", "value": "shipregion" }, { "id": 2, "type": "column", "value": "shipcity" }, { "id": 6, "type": "column", "value": "shipname" }, { "id": 0, "type": "table", "value": "orders" } ]
[ { "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": [ 6, 7, 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", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
2,140
works_cycles
bird:train.json:7414
Please list the names of all the store contact employees whose credit cards expired in 2007.
SELECT T1.FirstName, T1.LastName FROM Person AS T1 INNER JOIN PersonCreditCard AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN CreditCard AS T3 ON T2.CreditCardID = T3.CreditCardID WHERE T3.ExpYear = 2007 AND T1.PersonType = 'SC'
[ "Please", "list", "the", "names", "of", "all", "the", "store", "contact", "employees", "whose", "credit", "cards", "expired", "in", "2007", "." ]
[ { "id": 4, "type": "table", "value": "personcreditcard" }, { "id": 10, "type": "column", "value": "businessentityid" }, { "id": 5, "type": "column", "value": "creditcardid" }, { "id": 2, "type": "table", "value": "creditcard" }, { "id": 8, "type": "column", "value": "persontype" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 6, "type": "column", "value": "expyear" }, { "id": 3, "type": "table", "value": "person" }, { "id": 7, "type": "value", "value": "2007" }, { "id": 9, "type": "value", "value": "SC" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "B-VALUE", "O" ]
2,141
beer_factory
bird:train.json:5358
What is the email address of the customer who made a purchase in transaction 100016?
SELECT T1.Email FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.TransactionID = '100016'
[ "What", "is", "the", "email", "address", "of", "the", "customer", "who", "made", "a", "purchase", "in", "transaction", "100016", "?" ]
[ { "id": 3, "type": "column", "value": "transactionid" }, { "id": 2, "type": "table", "value": "transaction" }, { "id": 5, "type": "column", "value": "customerid" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 4, "type": "value", "value": "100016" }, { "id": 0, "type": "column", "value": "email" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "B-VALUE", "O" ]
2,142
sakila_1
spider:train_spider.json:2972
What are all the movies rated as R? List the titles.
SELECT title FROM film WHERE rating = 'R'
[ "What", "are", "all", "the", "movies", "rated", "as", "R", "?", "List", "the", "titles", "." ]
[ { "id": 2, "type": "column", "value": "rating" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "film" }, { "id": 3, "type": "value", "value": "R" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "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", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O" ]
2,145
product_catalog
spider:train_spider.json:314
What are the name and publication date of the catalogs with catalog level number above 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
[ "What", "are", "the", "name", "and", "publication", "date", "of", "the", "catalogs", "with", "catalog", "level", "number", "above", "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" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 12, 13 ] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [ 11 ] }, { "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-TABLE", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
2,146
gas_company
spider:train_spider.json:2018
For each location, how many gas stations are there in order?
SELECT LOCATION , count(*) FROM gas_station GROUP BY LOCATION ORDER BY count(*)
[ "For", "each", "location", ",", "how", "many", "gas", "stations", "are", "there", "in", "order", "?" ]
[ { "id": 0, "type": "table", "value": "gas_station" }, { "id": 1, "type": "column", "value": "location" } ]
[ { "entity_id": 0, "token_idxs": [ 6, 7 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O" ]