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13,160
csu_1
spider:train_spider.json:2379
What are the campuses that had between 600 and 1000 faculty members in 2004?
SELECT T1.campus FROM campuses AS t1 JOIN faculty AS t2 ON t1.id = t2.campus WHERE t2.faculty >= 600 AND t2.faculty <= 1000 AND T1.year = 2004
[ "What", "are", "the", "campuses", "that", "had", "between", "600", "and", "1000", "faculty", "members", "in", "2004", "?" ]
[ { "id": 1, "type": "table", "value": "campuses" }, { "id": 2, "type": "table", "value": "faculty" }, { "id": 4, "type": "column", "value": "faculty" }, { "id": 0, "type": "column", "value": "campus" }, { "id": 6, "type": "value", "value": "1000" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "2004" }, { "id": 5, "type": "value", "value": "600" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
13,161
csu_1
spider:train_spider.json:2371
What degrees were conferred in San Francisco State University in the year 2001?
SELECT degrees FROM campuses AS T1 JOIN degrees AS T2 ON t1.id = t2.campus WHERE t1.campus = "San Francisco State University" AND t2.year = 2001
[ "What", "degrees", "were", "conferred", "in", "San", "Francisco", "State", "University", "in", "the", "year", "2001", "?" ]
[ { "id": 5, "type": "column", "value": "San Francisco State University" }, { "id": 1, "type": "table", "value": "campuses" }, { "id": 0, "type": "column", "value": "degrees" }, { "id": 2, "type": "table", "value": "degrees" }, { "id": 4, "type": "column", "value": "campus" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "2001" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
13,162
e_learning
spider:train_spider.json:3781
Find the number of distinct students enrolled in courses.
SELECT count(DISTINCT student_id) FROM Student_Course_Enrolment
[ "Find", "the", "number", "of", "distinct", "students", "enrolled", "in", "courses", "." ]
[ { "id": 0, "type": "table", "value": "student_course_enrolment" }, { "id": 1, "type": "column", "value": "student_id" } ]
[ { "entity_id": 0, "token_idxs": [ 6, 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", "B-TABLE", "I-TABLE", "O", "O" ]
13,163
mondial_geo
bird:train.json:8244
Please list the name of the countries with over 5 ethnic groups.
SELECT T1.Name FROM country AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Code = T2.Country GROUP BY T1.Name HAVING COUNT(T1.Name) > 5
[ "Please", "list", "the", "name", "of", "the", "countries", "with", "over", "5", "ethnic", "groups", "." ]
[ { "id": 2, "type": "table", "value": "ethnicgroup" }, { "id": 1, "type": "table", "value": "country" }, { "id": 5, "type": "column", "value": "country" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "code" }, { "id": 3, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "B-TABLE", "I-TABLE", "O" ]
13,164
activity_1
spider:train_spider.json:6776
Find the number of activities Mark Giuliano is involved in.
SELECT count(*) FROM Faculty AS T1 JOIN Faculty_participates_in AS T2 ON T1.facID = T2.facID WHERE T1.fname = "Mark" AND T1.lname = "Giuliano"
[ "Find", "the", "number", "of", "activities", "Mark", "Giuliano", "is", "involved", "in", "." ]
[ { "id": 1, "type": "table", "value": "faculty_participates_in" }, { "id": 6, "type": "column", "value": "Giuliano" }, { "id": 0, "type": "table", "value": "faculty" }, { "id": 2, "type": "column", "value": "facid" }, { "id": 3, "type": "column", "value": "fname" }, { "id": 5, "type": "column", "value": "lname" }, { "id": 4, "type": "column", "value": "Mark" } ]
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[ "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O" ]
13,165
manufactory_1
spider:train_spider.json:5275
What is the headquarter of the company whose founder is James?
SELECT headquarter FROM manufacturers WHERE founder = 'James'
[ "What", "is", "the", "headquarter", "of", "the", "company", "whose", "founder", "is", "James", "?" ]
[ { "id": 0, "type": "table", "value": "manufacturers" }, { "id": 1, "type": "column", "value": "headquarter" }, { "id": 2, "type": "column", "value": "founder" }, { "id": 3, "type": "value", "value": "James" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
13,166
retail_world
bird:train.json:6555
Mention the oldest empoyee's full name, title, salary and number of orders which were shipped to USA by him.
SELECT T1.FirstName, T1.LastName, T1.Title, T1.Salary , COUNT(T2.OrderID) FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID WHERE ShipCountry = 'USA' GROUP BY T1.FirstName, T1.LastName, T1.Title, T1.Salary, T1.BirthDate ORDER BY T1.BirthDate LIMIT 1
[ "Mention", "the", "oldest", "empoyee", "'s", "full", "name", ",", "title", ",", "salary", "and", "number", "of", "orders", "which", "were", "shipped", "to", "USA", "by", "him", "." ]
[ { "id": 7, "type": "column", "value": "shipcountry" }, { "id": 10, "type": "column", "value": "employeeid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 4, "type": "column", "value": "birthdate" }, { "id": 5, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 9, "type": "column", "value": "orderid" }, { "id": 3, "type": "column", "value": "salary" }, { "id": 6, "type": "table", "value": "orders" }, { "id": 2, "type": "column", "value": "title" }, { "id": 8, "type": "value", "value": "USA" } ]
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[ "O", "O", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
13,167
network_2
spider:train_spider.json:4411
What is the name of the oldest student?
SELECT name FROM Person WHERE job = 'student' AND age = (SELECT max(age) FROM person WHERE job = 'student' )
[ "What", "is", "the", "name", "of", "the", "oldest", "student", "?" ]
[ { "id": 3, "type": "value", "value": "student" }, { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "job" }, { "id": 4, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
13,168
election_representative
spider:train_spider.json:1183
What are the names of representatives in descending order of votes?
SELECT T2.Name FROM election AS T1 JOIN representative AS T2 ON T1.Representative_ID = T2.Representative_ID ORDER BY votes DESC
[ "What", "are", "the", "names", "of", "representatives", "in", "descending", "order", "of", "votes", "?" ]
[ { "id": 4, "type": "column", "value": "representative_id" }, { "id": 2, "type": "table", "value": "representative" }, { "id": 1, "type": "table", "value": "election" }, { "id": 3, "type": "column", "value": "votes" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
13,169
movie_platform
bird:train.json:159
What is the name of the movie whose critic received the highest amount of likes? Indicate the URL to the rating on Mubi.
SELECT T2.movie_title, T1.rating_url FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id ORDER BY T1.critic_likes DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "movie", "whose", "critic", "received", "the", "highest", "amount", "of", "likes", "?", "Indicate", "the", "URL", "to", "the", "rating", "on", "Mubi", "." ]
[ { "id": 4, "type": "column", "value": "critic_likes" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 1, "type": "column", "value": "rating_url" }, { "id": 5, "type": "column", "value": "movie_id" }, { "id": 2, "type": "table", "value": "ratings" }, { "id": 3, "type": "table", "value": "movies" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
13,170
car_retails
bird:train.json:1589
Among the motorcycles with product scale of 1:10, which of them is the most ordered by American customers?
SELECT T1.productName FROM products AS T1 INNER JOIN orderdetails AS T2 ON T1.productCode = T2.productCode INNER JOIN orders AS T3 ON T2.orderNumber = T3.orderNumber INNER JOIN customers AS T4 ON T3.customerNumber = T4.customerNumber WHERE T1.productLine = 'Motorcycles' AND T1.productScale = '1:10' AND T4.country = 'USA' GROUP BY T1.productName ORDER BY SUM(T2.quantityOrdered) DESC LIMIT 1
[ "Among", "the", "motorcycles", "with", "product", "scale", "of", "1:10", ",", "which", "of", "them", "is", "the", "most", "ordered", "by", "American", "customers", "?" ]
[ { "id": 10, "type": "column", "value": "quantityordered" }, { "id": 3, "type": "column", "value": "customernumber" }, { "id": 6, "type": "column", "value": "productscale" }, { "id": 12, "type": "table", "value": "orderdetails" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 4, "type": "column", "value": "productline" }, { "id": 5, "type": "value", "value": "Motorcycles" }, { "id": 13, "type": "column", "value": "ordernumber" }, { "id": 14, "type": "column", "value": "productcode" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 11, "type": "table", "value": "products" }, { "id": 8, "type": "column", "value": "country" }, { "id": 2, "type": "table", "value": "orders" }, { "id": 7, "type": "value", "value": "1:10" }, { "id": 9, "type": "value", "value": "USA" } ]
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[ "O", "O", "B-VALUE", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
13,171
network_2
spider:train_spider.json:4407
How many different jobs are listed?
SELECT count(DISTINCT job) FROM Person
[ "How", "many", "different", "jobs", "are", "listed", "?" ]
[ { "id": 0, "type": "table", "value": "person" }, { "id": 1, "type": "column", "value": "job" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
13,172
menu
bird:train.json:5565
To which menu does the menu page image ID5189412 belong? Please give its name.
SELECT T1.name FROM Menu AS T1 INNER JOIN MenuPage AS T2 ON T1.id = T2.menu_id WHERE T2.image_id = 5189412
[ "To", "which", "menu", "does", "the", "menu", "page", "image", "ID5189412", "belong", "?", "Please", "give", "its", "name", "." ]
[ { "id": 2, "type": "table", "value": "menupage" }, { "id": 3, "type": "column", "value": "image_id" }, { "id": 4, "type": "value", "value": "5189412" }, { "id": 6, "type": "column", "value": "menu_id" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "table", "value": "menu" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 14 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "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", "B-TABLE", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
13,173
works_cycles
bird:train.json:7190
Among the Production Technicians who are single, how many of them are vendor contact?
SELECT COUNT(T1.BusinessEntityID) FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.JobTitle LIKE 'Production Technician%' AND T1.MaritalStatus = 'S' AND T2.PersonType = 'VC'
[ "Among", "the", "Production", "Technicians", "who", "are", "single", ",", "how", "many", "of", "them", "are", "vendor", "contact", "?" ]
[ { "id": 4, "type": "value", "value": "Production Technician%" }, { "id": 2, "type": "column", "value": "businessentityid" }, { "id": 5, "type": "column", "value": "maritalstatus" }, { "id": 7, "type": "column", "value": "persontype" }, { "id": 0, "type": "table", "value": "employee" }, { "id": 3, "type": "column", "value": "jobtitle" }, { "id": 1, "type": "table", "value": "person" }, { "id": 8, "type": "value", "value": "VC" }, { "id": 6, "type": "value", "value": "S" } ]
[ { "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": [ 2, 3 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
13,175
european_football_2
bird:dev.json:1148
What is the percentage of players that are under 180 cm who have an overall strength of more than 70?
SELECT CAST(COUNT(CASE WHEN t2.overall_rating > 70 THEN t1.id ELSE NULL END) AS REAL) * 100 / COUNT(t1.id) percent FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id WHERE t1.height < 180
[ "What", "is", "the", "percentage", "of", "players", "that", "are", "under", "180", "cm", "who", "have", "an", "overall", "strength", "of", "more", "than", "70", "?" ]
[ { "id": 1, "type": "table", "value": "player_attributes" }, { "id": 7, "type": "column", "value": "overall_rating" }, { "id": 4, "type": "column", "value": "player_api_id" }, { "id": 0, "type": "table", "value": "player" }, { "id": 2, "type": "column", "value": "height" }, { "id": 3, "type": "value", "value": "180" }, { "id": 5, "type": "value", "value": "100" }, { "id": 6, "type": "column", "value": "id" }, { "id": 8, "type": "value", "value": "70" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 6, 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 14, 15 ] }, { "entity_id": 8, "token_idxs": [ 19 ] }, { "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-TABLE", "I-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
13,176
company_employee
spider:train_spider.json:4099
Show the names of companies in the banking or retailing industry?
SELECT Name FROM company WHERE Industry = "Banking" OR Industry = "Retailing"
[ "Show", "the", "names", "of", "companies", "in", "the", "banking", "or", "retailing", "industry", "?" ]
[ { "id": 4, "type": "column", "value": "Retailing" }, { "id": 2, "type": "column", "value": "industry" }, { "id": 0, "type": "table", "value": "company" }, { "id": 3, "type": "column", "value": "Banking" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O" ]
13,177
candidate_poll
spider:train_spider.json:2402
Please list support, consider, and oppose rates for each candidate in ascending order by unsure rate.
SELECT Support_rate , Consider_rate , Oppose_rate FROM candidate ORDER BY unsure_rate
[ "Please", "list", "support", ",", "consider", ",", "and", "oppose", "rates", "for", "each", "candidate", "in", "ascending", "order", "by", "unsure", "rate", "." ]
[ { "id": 2, "type": "column", "value": "consider_rate" }, { "id": 1, "type": "column", "value": "support_rate" }, { "id": 3, "type": "column", "value": "oppose_rate" }, { "id": 4, "type": "column", "value": "unsure_rate" }, { "id": 0, "type": "table", "value": "candidate" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 7, 8 ] }, { "entity_id": 4, "token_idxs": [ 16, 17 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
13,178
car_retails
bird:train.json:1556
Which two products has the highest and lowest expected profits? Determine the total price for each product in terms of the largest quantity that was ordered.
SELECT T2.productName, SUM(T1.quantityOrdered * T1.priceEach) FROM orderdetails AS T1 INNER JOIN ( SELECT productCode, productName FROM products ORDER BY MSRP - buyPrice DESC LIMIT 1 ) AS T2 ON T1.productCode = T2.productCode UNION SELECT T2.productName, SUM(quantityOrdered * priceEach) FROM orderdetails AS T1 INNER JOIN ( SELECT productCode, productName FROM products ORDER BY MSRP - buyPrice ASC LIMIT 1 ) AS T2 ON T1.productCode = T2.productCode
[ "Which", "two", "products", "has", "the", "highest", "and", "lowest", "expected", "profits", "?", "Determine", "the", "total", "price", "for", "each", "product", "in", "terms", "of", "the", "largest", "quantity", "that", "was", "ordered", "." ]
[ { "id": 3, "type": "column", "value": "quantityordered" }, { "id": 1, "type": "table", "value": "orderdetails" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 2, "type": "column", "value": "productcode" }, { "id": 4, "type": "column", "value": "priceeach" }, { "id": 5, "type": "table", "value": "products" }, { "id": 7, "type": "column", "value": "buyprice" }, { "id": 6, "type": "column", "value": "msrp" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 17 ] }, { "entity_id": 3, "token_idxs": [ 23, 24, 25, 26 ] }, { "entity_id": 4, "token_idxs": [ 15, 16 ] }, { "entity_id": 5, "token_idxs": [ 2 ] }, { "entity_id": 6, "token_idxs": [] }, { "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", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
13,179
professional_basketball
bird:train.json:2828
Among the players from the NBL league, how many of them were born in Spencer?
SELECT COUNT(DISTINCT T1.playerID) FROM players AS T1 INNER JOIN players_teams AS T2 ON T1.playerID = T2.playerID WHERE T1.birthCity = 'Spencer' AND T2.lgID = 'NBL'
[ "Among", "the", "players", "from", "the", "NBL", "league", ",", "how", "many", "of", "them", "were", "born", "in", "Spencer", "?" ]
[ { "id": 1, "type": "table", "value": "players_teams" }, { "id": 3, "type": "column", "value": "birthcity" }, { "id": 2, "type": "column", "value": "playerid" }, { "id": 0, "type": "table", "value": "players" }, { "id": 4, "type": "value", "value": "Spencer" }, { "id": 5, "type": "column", "value": "lgid" }, { "id": 6, "type": "value", "value": "NBL" } ]
[ { "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": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
13,180
movies_4
bird:train.json:436
What is the percentage of male characters in the movie "Bride Wars"?
SELECT CAST(COUNT(CASE WHEN T3.gender = 'Male' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T3.gender) FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN gender AS T3 ON T2.gender_id = T3.gender_id WHERE T1.title = 'Bride Wars'
[ "What", "is", "the", "percentage", "of", "male", "characters", "in", "the", "movie", "\"", "Bride", "Wars", "\"", "?" ]
[ { "id": 2, "type": "value", "value": "Bride Wars" }, { "id": 4, "type": "table", "value": "movie_cast" }, { "id": 5, "type": "column", "value": "gender_id" }, { "id": 8, "type": "column", "value": "movie_id" }, { "id": 0, "type": "table", "value": "gender" }, { "id": 7, "type": "column", "value": "gender" }, { "id": 1, "type": "column", "value": "title" }, { "id": 3, "type": "table", "value": "movie" }, { "id": 10, "type": "value", "value": "Male" }, { "id": 6, "type": "value", "value": "100" }, { "id": 9, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11, 12 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 5 ] }, { "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", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O" ]
13,181
customers_campaigns_ecommerce
spider:train_spider.json:4630
What are the name and payment method of customers who have both mailshots in 'Order' outcome and mailshots in 'No Response' outcome.
SELECT T2.customer_name , T2.payment_method FROM mailshot_customers AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id WHERE T1.outcome_code = 'Order' INTERSECT SELECT T2.customer_name , T2.payment_method FROM mailshot_customers AS T1 JOIN customers AS T2 ON T1.customer_id = T2.customer_id WHERE T1.outcome_code = 'No Response'
[ "What", "are", "the", "name", "and", "payment", "method", "of", "customers", "who", "have", "both", "mailshots", "in", "'", "Order", "'", "outcome", "and", "mailshots", "in", "'", "No", "Response", "'", "outcome", "." ]
[ { "id": 2, "type": "table", "value": "mailshot_customers" }, { "id": 1, "type": "column", "value": "payment_method" }, { "id": 0, "type": "column", "value": "customer_name" }, { "id": 4, "type": "column", "value": "outcome_code" }, { "id": 6, "type": "value", "value": "No Response" }, { "id": 7, "type": "column", "value": "customer_id" }, { "id": 3, "type": "table", "value": "customers" }, { "id": 5, "type": "value", "value": "Order" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 25 ] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [ 22, 23 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-COLUMN", "O" ]
13,182
movie_2
bird:test.json:1811
Find the number of movies whose rating is ‘G’.
SELECT count(*) FROM movies WHERE rating = 'G'
[ "Find", "the", "number", "of", "movies", "whose", "rating", "is", "‘", "G", "’", "." ]
[ { "id": 0, "type": "table", "value": "movies" }, { "id": 1, "type": "column", "value": "rating" }, { "id": 2, "type": "value", "value": "G" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O" ]
13,183
european_football_1
bird:train.json:2780
How many Eredivisie teams have played in 2008?
SELECT COUNT(DISTINCT T1.HomeTeam) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.name = 'Eredivisie' AND T1.season = 2008
[ "How", "many", "Eredivisie", "teams", "have", "played", "in", "2008", "?" ]
[ { "id": 6, "type": "value", "value": "Eredivisie" }, { "id": 1, "type": "table", "value": "divisions" }, { "id": 2, "type": "column", "value": "hometeam" }, { "id": 4, "type": "column", "value": "division" }, { "id": 0, "type": "table", "value": "matchs" }, { "id": 7, "type": "column", "value": "season" }, { "id": 5, "type": "column", "value": "name" }, { "id": 8, "type": "value", "value": "2008" }, { "id": 3, "type": "column", "value": "div" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 7 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
13,184
college_completion
bird:train.json:3701
How many students graduated from Central Alabama Community College in 2011 in total?
SELECT T2.grad_cohort FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T1.unitid = T2.unitid WHERE T1.chronname = 'Central Alabama Community College' AND T2.year = 2011
[ "How", "many", "students", "graduated", "from", "Central", "Alabama", "Community", "College", "in", "2011", "in", "total", "?" ]
[ { "id": 5, "type": "value", "value": "Central Alabama Community College" }, { "id": 1, "type": "table", "value": "institution_details" }, { "id": 2, "type": "table", "value": "institution_grads" }, { "id": 0, "type": "column", "value": "grad_cohort" }, { "id": 4, "type": "column", "value": "chronname" }, { "id": 3, "type": "column", "value": "unitid" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "2011" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-VALUE", "O", "O", "O" ]
13,185
language_corpus
bird:train.json:5686
List the page number for Catalan language wikipedia pages containing the word 'Art' in the page title.
SELECT page FROM pages WHERE title LIKE 'Art%' OR title LIKE '%Art%' OR title LIKE '%Art'
[ "List", "the", "page", "number", "for", "Catalan", "language", "wikipedia", "pages", "containing", "the", "word", "'", "Art", "'", "in", "the", "page", "title", "." ]
[ { "id": 0, "type": "table", "value": "pages" }, { "id": 2, "type": "column", "value": "title" }, { "id": 4, "type": "value", "value": "%Art%" }, { "id": 1, "type": "column", "value": "page" }, { "id": 3, "type": "value", "value": "Art%" }, { "id": 5, "type": "value", "value": "%Art" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
13,186
disney
bird:train.json:4727
Find out what proportion of total revenue Walt Disney Parks and Resorts received in 2010.
SELECT SUM(`Walt Disney Parks and Resorts`) / SUM(Total) * 100 FROM revenue WHERE year = 2010
[ "Find", "out", "what", "proportion", "of", "total", "revenue", "Walt", "Disney", "Parks", "and", "Resorts", "received", "in", "2010", "." ]
[ { "id": 4, "type": "column", "value": "Walt Disney Parks and Resorts" }, { "id": 0, "type": "table", "value": "revenue" }, { "id": 5, "type": "column", "value": "total" }, { "id": 1, "type": "column", "value": "year" }, { "id": 2, "type": "value", "value": "2010" }, { "id": 3, "type": "value", "value": "100" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
13,187
professional_basketball
bird:train.json:2951
Which team did the all league rebound champion play in 1997? Give the full name of the team.
SELECT T1.name FROM teams AS T1 INNER JOIN players_teams AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T2.year = 1997 GROUP BY T1.name ORDER BY SUM(rebounds + dRebounds) DESC LIMIT 1
[ "Which", "team", "did", "the", "all", "league", "rebound", "champion", "play", "in", "1997", "?", "Give", "the", "full", "name", "of", "the", "team", "." ]
[ { "id": 2, "type": "table", "value": "players_teams" }, { "id": 7, "type": "column", "value": "drebounds" }, { "id": 6, "type": "column", "value": "rebounds" }, { "id": 1, "type": "table", "value": "teams" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "1997" }, { "id": 5, "type": "column", "value": "tmid" } ]
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[ "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
13,188
app_store
bird:train.json:2555
List out the top 3 genre for application with a sentiment review greater than 0.5.
SELECT Genres FROM playstore WHERE App IN ( SELECT App FROM user_reviews WHERE Sentiment = 'Positive' AND Sentiment_Polarity > 0.5 ORDER BY Sentiment_Polarity DESC LIMIT 3 )
[ "List", "out", "the", "top", "3", "genre", "for", "application", "with", "a", "sentiment", "review", "greater", "than", "0.5", "." ]
[ { "id": 4, "type": "column", "value": "sentiment_polarity" }, { "id": 3, "type": "table", "value": "user_reviews" }, { "id": 0, "type": "table", "value": "playstore" }, { "id": 5, "type": "column", "value": "sentiment" }, { "id": 6, "type": "value", "value": "Positive" }, { "id": 1, "type": "column", "value": "genres" }, { "id": 2, "type": "column", "value": "app" }, { "id": 7, "type": "value", "value": "0.5" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "B-VALUE", "O" ]
13,190
city_record
spider:train_spider.json:6302
List venues of all matches in the order of their dates starting from the most recent one.
SELECT venue FROM MATCH ORDER BY date DESC
[ "List", "venues", "of", "all", "matches", "in", "the", "order", "of", "their", "dates", "starting", "from", "the", "most", "recent", "one", "." ]
[ { "id": 0, "type": "table", "value": "match" }, { "id": 1, "type": "column", "value": "venue" }, { "id": 2, "type": "column", "value": "date" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
13,191
gymnast
spider:train_spider.json:1775
What are the ages of the gymnasts, ordered descending by their total points?
SELECT T2.Age FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T1.Total_Points DESC
[ "What", "are", "the", "ages", "of", "the", "gymnasts", ",", "ordered", "descending", "by", "their", "total", "points", "?" ]
[ { "id": 3, "type": "column", "value": "total_points" }, { "id": 4, "type": "column", "value": "gymnast_id" }, { "id": 5, "type": "column", "value": "people_id" }, { "id": 1, "type": "table", "value": "gymnast" }, { "id": 2, "type": "table", "value": "people" }, { "id": 0, "type": "column", "value": "age" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
13,192
retail_world
bird:train.json:6465
What are the product names of Exotic Liquids?
SELECT T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Exotic Liquids'
[ "What", "are", "the", "product", "names", "of", "Exotic", "Liquids", "?" ]
[ { "id": 4, "type": "value", "value": "Exotic Liquids" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 3, "type": "column", "value": "companyname" }, { "id": 5, "type": "column", "value": "supplierid" }, { "id": 2, "type": "table", "value": "suppliers" }, { "id": 1, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
13,193
works_cycles
bird:train.json:7355
Which sales areas are expected to have the highest yearly sales quota?
SELECT T2.Name FROM SalesPerson AS T1 INNER JOIN SalesTerritory AS T2 ON T1.TerritoryID = T2.TerritoryID GROUP BY T1.TerritoryID ORDER BY SUM(T1.SalesQuota) DESC LIMIT 1
[ "Which", "sales", "areas", "are", "expected", "to", "have", "the", "highest", "yearly", "sales", "quota", "?" ]
[ { "id": 3, "type": "table", "value": "salesterritory" }, { "id": 0, "type": "column", "value": "territoryid" }, { "id": 2, "type": "table", "value": "salesperson" }, { "id": 4, "type": "column", "value": "salesquota" }, { "id": 1, "type": "column", "value": "name" } ]
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[ "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
13,194
department_store
spider:train_spider.json:4755
What is id of the staff who had a Staff Department Assignment earlier than any Clerical Staff?
SELECT staff_id FROM Staff_Department_Assignments WHERE date_assigned_to < (SELECT max(date_assigned_to) FROM Staff_Department_Assignments WHERE job_title_code = 'Clerical Staff')
[ "What", "is", "i", "d", "of", "the", "staff", "who", "had", "a", "Staff", "Department", "Assignment", "earlier", "than", "any", "Clerical", "Staff", "?" ]
[ { "id": 0, "type": "table", "value": "staff_department_assignments" }, { "id": 2, "type": "column", "value": "date_assigned_to" }, { "id": 3, "type": "column", "value": "job_title_code" }, { "id": 4, "type": "value", "value": "Clerical Staff" }, { "id": 1, "type": "column", "value": "staff_id" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
13,195
world
bird:train.json:7823
How many countries use Portuguese?
SELECT SUM(CASE WHEN Language = 'Portuguese' THEN 1 ELSE 0 END) FROM CountryLanguage
[ "How", "many", "countries", "use", "Portuguese", "?" ]
[ { "id": 0, "type": "table", "value": "countrylanguage" }, { "id": 4, "type": "value", "value": "Portuguese" }, { "id": 3, "type": "column", "value": "language" }, { "id": 1, "type": "value", "value": "0" }, { "id": 2, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
13,196
college_2
spider:train_spider.json:1487
What are the names and average salaries for departments with average salary higher than 42000?
SELECT dept_name , AVG (salary) FROM instructor GROUP BY dept_name HAVING AVG (salary) > 42000
[ "What", "are", "the", "names", "and", "average", "salaries", "for", "departments", "with", "average", "salary", "higher", "than", "42000", "?" ]
[ { "id": 0, "type": "table", "value": "instructor" }, { "id": 1, "type": "column", "value": "dept_name" }, { "id": 3, "type": "column", "value": "salary" }, { "id": 2, "type": "value", "value": "42000" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
13,197
cre_Doc_and_collections
bird:test.json:701
Which document has most of child? List the document id and the number of child.
SELECT T2.Document_Object_ID , count(*) FROM Document_Objects AS T1 JOIN Document_Objects AS T2 ON T1.Parent_Document_Object_ID = T2.Document_Object_ID GROUP BY T2.Document_Object_ID ORDER BY count(*) DESC LIMIT 1;
[ "Which", "document", "has", "most", "of", "child", "?", "List", "the", "document", "i", "d", "and", "the", "number", "of", "child", "." ]
[ { "id": 2, "type": "column", "value": "parent_document_object_id" }, { "id": 0, "type": "column", "value": "document_object_id" }, { "id": 1, "type": "table", "value": "document_objects" } ]
[ { "entity_id": 0, "token_idxs": [ 10, 11 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O" ]
13,198
club_1
spider:train_spider.json:4309
Count the number of clubs for which the student named "Eric Tai" is a member.
SELECT count(DISTINCT t1.clubname) FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t3.fname = "Eric" AND t3.lname = "Tai"
[ "Count", "the", "number", "of", "clubs", "for", "which", "the", "student", "named", "\"", "Eric", "Tai", "\"", "is", "a", "member", "." ]
[ { "id": 3, "type": "table", "value": "member_of_club" }, { "id": 1, "type": "column", "value": "clubname" }, { "id": 0, "type": "table", "value": "student" }, { "id": 9, "type": "column", "value": "clubid" }, { "id": 4, "type": "column", "value": "stuid" }, { "id": 5, "type": "column", "value": "fname" }, { "id": 7, "type": "column", "value": "lname" }, { "id": 2, "type": "table", "value": "club" }, { "id": 6, "type": "column", "value": "Eric" }, { "id": 8, "type": "column", "value": "Tai" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 2, 3 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 11 ] }, { "entity_id": 7, "token_idxs": [ 9 ] }, { "entity_id": 8, "token_idxs": [ 12 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O" ]
13,199
address
bird:train.json:5185
List all the cities with micro CBSA.
SELECT T2.city FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_type = 'Micro'
[ "List", "all", "the", "cities", "with", "micro", "CBSA", "." ]
[ { "id": 3, "type": "column", "value": "cbsa_type" }, { "id": 2, "type": "table", "value": "zip_data" }, { "id": 4, "type": "value", "value": "Micro" }, { "id": 0, "type": "column", "value": "city" }, { "id": 1, "type": "table", "value": "cbsa" }, { "id": 5, "type": "column", "value": "cbsa" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "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": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-COLUMN", "O" ]
13,200
software_company
bird:train.json:8549
In customers with marital status of never married, what is the percentage of customers with income of 2500 and above?
SELECT CAST(SUM(CASE WHEN T2.INCOME_K > 2500 THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.MARITAL_STATUS = 'Never-married'
[ "In", "customers", "with", "marital", "status", "of", "never", "married", ",", "what", "is", "the", "percentage", "of", "customers", "with", "income", "of", "2500", "and", "above", "?" ]
[ { "id": 2, "type": "column", "value": "marital_status" }, { "id": 3, "type": "value", "value": "Never-married" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 8, "type": "column", "value": "income_k" }, { "id": 1, "type": "table", "value": "demog" }, { "id": 4, "type": "column", "value": "geoid" }, { "id": 9, "type": "value", "value": "2500" }, { "id": 5, "type": "value", "value": "100" }, { "id": 7, "type": "value", "value": "1.0" }, { "id": 6, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3, 4 ] }, { "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": [ 16 ] }, { "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", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O" ]
13,201
beer_factory
bird:train.json:5242
Please list the brands of all the root beer that Frank-Paul Santangelo had purchased on 2014/7/7.
SELECT DISTINCT T4.BrandName FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeer AS T3 ON T2.RootBeerID = T3.RootBeerID INNER JOIN rootbeerbrand AS T4 ON T3.BrandID = T4.BrandID WHERE T1.First = 'Frank-Paul' AND T1.Last = 'Santangelo' AND T2.TransactionDate = '2014-07-07'
[ "Please", "list", "the", "brands", "of", "all", "the", "root", "beer", "that", "Frank", "-", "Paul", "Santangelo", "had", "purchased", "on", "2014/7/7", "." ]
[ { "id": 8, "type": "column", "value": "transactiondate" }, { "id": 1, "type": "table", "value": "rootbeerbrand" }, { "id": 11, "type": "table", "value": "transaction" }, { "id": 5, "type": "value", "value": "Frank-Paul" }, { "id": 7, "type": "value", "value": "Santangelo" }, { "id": 9, "type": "value", "value": "2014-07-07" }, { "id": 12, "type": "column", "value": "rootbeerid" }, { "id": 13, "type": "column", "value": "customerid" }, { "id": 0, "type": "column", "value": "brandname" }, { "id": 10, "type": "table", "value": "customers" }, { "id": 2, "type": "table", "value": "rootbeer" }, { "id": 3, "type": "column", "value": "brandid" }, { "id": 4, "type": "column", "value": "first" }, { "id": 6, "type": "column", "value": "last" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7, 8 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 10, 11, 12 ] }, { "entity_id": 6, "token_idxs": [ 1 ] }, { "entity_id": 7, "token_idxs": [ 13 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 17 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-VALUE", "O", "O", "O", "B-VALUE", "O" ]
13,203
superhero
bird:dev.json:779
How many powers does Amazo hero have?
SELECT COUNT(T1.power_id) FROM hero_power AS T1 INNER JOIN superhero AS T2 ON T1.hero_id = T2.id WHERE T2.superhero_name = 'Amazo'
[ "How", "many", "powers", "does", "Amazo", "hero", "have", "?" ]
[ { "id": 2, "type": "column", "value": "superhero_name" }, { "id": 0, "type": "table", "value": "hero_power" }, { "id": 1, "type": "table", "value": "superhero" }, { "id": 4, "type": "column", "value": "power_id" }, { "id": 5, "type": "column", "value": "hero_id" }, { "id": 3, "type": "value", "value": "Amazo" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-VALUE", "B-COLUMN", "O", "O" ]
13,204
university_basketball
spider:train_spider.json:986
Count the number of schools that have had basketball matches.
SELECT count(DISTINCT school_id) FROM basketball_match
[ "Count", "the", "number", "of", "schools", "that", "have", "had", "basketball", "matches", "." ]
[ { "id": 0, "type": "table", "value": "basketball_match" }, { "id": 1, "type": "column", "value": "school_id" } ]
[ { "entity_id": 0, "token_idxs": [ 8, 9 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
13,205
book_publishing_company
bird:train.json:187
List all employees working for publisher 'GGG&G'. State their name and job description.
SELECT T1.fname, T1.lname, T3.job_desc FROM employee AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN jobs AS T3 ON T1.job_id = T3.job_id WHERE T2.pub_name = 'GGG&G'
[ "List", "all", "employees", "working", "for", "publisher", "'", "GGG&G", "'", ".", "State", "their", "name", "and", "job", "description", "." ]
[ { "id": 7, "type": "table", "value": "publishers" }, { "id": 2, "type": "column", "value": "job_desc" }, { "id": 4, "type": "column", "value": "pub_name" }, { "id": 6, "type": "table", "value": "employee" }, { "id": 8, "type": "column", "value": "job_id" }, { "id": 9, "type": "column", "value": "pub_id" }, { "id": 0, "type": "column", "value": "fname" }, { "id": 1, "type": "column", "value": "lname" }, { "id": 5, "type": "value", "value": "GGG&G" }, { "id": 3, "type": "table", "value": "jobs" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [ 2 ] }, { "entity_id": 7, "token_idxs": [ 5 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O" ]
13,206
warehouse_1
bird:test.json:1709
Find all contents present in warehouses located in Chicago and those located in New York.
SELECT T1.contents FROM boxes AS T1 JOIN warehouses AS T2 ON T1.warehouse = T2.code WHERE T2.location = 'Chicago' INTERSECT SELECT T1.contents FROM boxes AS T1 JOIN warehouses AS T2 ON T1.warehouse = T2.code WHERE T2.location = 'New York'
[ "Find", "all", "contents", "present", "in", "warehouses", "located", "in", "Chicago", "and", "those", "located", "in", "New", "York", "." ]
[ { "id": 2, "type": "table", "value": "warehouses" }, { "id": 6, "type": "column", "value": "warehouse" }, { "id": 0, "type": "column", "value": "contents" }, { "id": 3, "type": "column", "value": "location" }, { "id": 5, "type": "value", "value": "New York" }, { "id": 4, "type": "value", "value": "Chicago" }, { "id": 1, "type": "table", "value": "boxes" }, { "id": 7, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6, 7 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [ 13, 14 ] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O" ]
13,207
driving_school
spider:train_spider.json:6699
How many lessons have been cancelled?
SELECT count(*) FROM Lessons WHERE lesson_status_code = "Cancelled";
[ "How", "many", "lessons", "have", "been", "cancelled", "?" ]
[ { "id": 1, "type": "column", "value": "lesson_status_code" }, { "id": 2, "type": "column", "value": "Cancelled" }, { "id": 0, "type": "table", "value": "lessons" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O" ]
13,208
synthea
bird:train.json:1381
Provide the name of the patient who had a claim on 1947/9/11.
SELECT T1.first, T1.last FROM patients AS T1 INNER JOIN claims AS T2 ON T1.patient = T2.PATIENT WHERE T2.billableperiod = '1947-09-11'
[ "Provide", "the", "name", "of", "the", "patient", "who", "had", "a", "claim", "on", "1947/9/11", "." ]
[ { "id": 4, "type": "column", "value": "billableperiod" }, { "id": 5, "type": "value", "value": "1947-09-11" }, { "id": 2, "type": "table", "value": "patients" }, { "id": 6, "type": "column", "value": "patient" }, { "id": 3, "type": "table", "value": "claims" }, { "id": 0, "type": "column", "value": "first" }, { "id": 1, "type": "column", "value": "last" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
13,209
flight_4
spider:train_spider.json:6859
Find the number of routes for each source airport and the airport name.
SELECT count(*) , T1.name FROM airports AS T1 JOIN routes AS T2 ON T1.apid = T2.src_apid GROUP BY T1.name
[ "Find", "the", "number", "of", "routes", "for", "each", "source", "airport", "and", "the", "airport", "name", "." ]
[ { "id": 1, "type": "table", "value": "airports" }, { "id": 4, "type": "column", "value": "src_apid" }, { "id": 2, "type": "table", "value": "routes" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "apid" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
13,210
chicago_crime
bird:train.json:8605
How many community areas are in the Far North side?
SELECT COUNT(*) FROM Community_Area WHERE side = 'Far North '
[ "How", "many", "community", "areas", "are", "in", "the", "Far", "North", "side", "?" ]
[ { "id": 0, "type": "table", "value": "community_area" }, { "id": 2, "type": "value", "value": "Far North " }, { "id": 1, "type": "column", "value": "side" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 7, 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O" ]
13,211
department_store
spider:train_spider.json:4781
What are the highest and lowest prices of products, grouped by and alphabetically ordered by product type?
SELECT max(product_price) , min(product_price) , product_type_code FROM products GROUP BY product_type_code ORDER BY product_type_code
[ "What", "are", "the", "highest", "and", "lowest", "prices", "of", "products", ",", "grouped", "by", "and", "alphabetically", "ordered", "by", "product", "type", "?" ]
[ { "id": 1, "type": "column", "value": "product_type_code" }, { "id": 2, "type": "column", "value": "product_price" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 16, 17 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
13,212
store_1
spider:train_spider.json:566
What are the states with the most invoices?
SELECT billing_state , COUNT(*) FROM invoices WHERE billing_country = "USA" GROUP BY billing_state ORDER BY COUNT(*) DESC LIMIT 1;
[ "What", "are", "the", "states", "with", "the", "most", "invoices", "?" ]
[ { "id": 2, "type": "column", "value": "billing_country" }, { "id": 1, "type": "column", "value": "billing_state" }, { "id": 0, "type": "table", "value": "invoices" }, { "id": 3, "type": "column", "value": "USA" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
13,215
mondial_geo
bird:train.json:8448
Which United States province is home to the greatest number of corporations' corporate headquarters?
SELECT T1.Province FROM country AS T1 INNER JOIN organization AS T2 ON T1.Code = T2.Country WHERE T1.Name = 'United States' GROUP BY T1.Province ORDER BY COUNT(T1.Name) DESC LIMIT 1
[ "Which", "United", "States", "province", "is", "home", "to", "the", "greatest", "number", "of", "corporations", "'", "corporate", "headquarters", "?" ]
[ { "id": 4, "type": "value", "value": "United States" }, { "id": 2, "type": "table", "value": "organization" }, { "id": 0, "type": "column", "value": "province" }, { "id": 1, "type": "table", "value": "country" }, { "id": 6, "type": "column", "value": "country" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 1, 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-VALUE", "I-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O" ]
13,216
flight_1
spider:train_spider.json:428
What are the names of all employees who can fly both the Boeing 737-800 and the Airbus A340-300?
SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" INTERSECT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Airbus A340-300"
[ "What", "are", "the", "names", "of", "all", "employees", "who", "can", "fly", "both", "the", "Boeing", "737", "-", "800", "and", "the", "Airbus", "A340", "-", "300", "?" ]
[ { "id": 3, "type": "column", "value": "Airbus A340-300" }, { "id": 2, "type": "column", "value": "Boeing 737-800" }, { "id": 5, "type": "table", "value": "certificate" }, { "id": 1, "type": "table", "value": "aircraft" }, { "id": 4, "type": "table", "value": "employee" }, { "id": 0, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "aid" }, { "id": 7, "type": "column", "value": "eid" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
13,217
cre_Doc_Workflow
bird:test.json:2053
How many staff are the document with id 0 and process with id 9.
SELECT count(*) FROM Staff_in_processes WHERE document_id = 0 AND process_id = 9
[ "How", "many", "staff", "are", "the", "document", "with", "i", "d", "0", "and", "process", "with", "i", "d", "9", "." ]
[ { "id": 0, "type": "table", "value": "staff_in_processes" }, { "id": 1, "type": "column", "value": "document_id" }, { "id": 3, "type": "column", "value": "process_id" }, { "id": 2, "type": "value", "value": "0" }, { "id": 4, "type": "value", "value": "9" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
13,219
university
bird:train.json:8068
What is the ID of the university with the most students in 2011?
SELECT university_id FROM university_year WHERE year = 2011 ORDER BY num_students DESC LIMIT 1
[ "What", "is", "the", "ID", "of", "the", "university", "with", "the", "most", "students", "in", "2011", "?" ]
[ { "id": 0, "type": "table", "value": "university_year" }, { "id": 1, "type": "column", "value": "university_id" }, { "id": 4, "type": "column", "value": "num_students" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "value", "value": "2011" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
13,220
products_for_hire
spider:train_spider.json:1973
What are the daily hire costs for the products with substring 'Book' in its name?
SELECT daily_hire_cost FROM Products_for_hire WHERE product_name LIKE '%Book%'
[ "What", "are", "the", "daily", "hire", "costs", "for", "the", "products", "with", "substring", "'", "Book", "'", "in", "its", "name", "?" ]
[ { "id": 0, "type": "table", "value": "products_for_hire" }, { "id": 1, "type": "column", "value": "daily_hire_cost" }, { "id": 2, "type": "column", "value": "product_name" }, { "id": 3, "type": "value", "value": "%Book%" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O" ]
13,221
codebase_community
bird:dev.json:531
Which user has a higher reputation, Harlan or Jarrod Dixon?
SELECT DisplayName FROM users WHERE DisplayName IN ('Harlan', 'Jarrod Dixon') AND Reputation = ( SELECT MAX(Reputation) FROM users WHERE DisplayName IN ('Harlan', 'Jarrod Dixon') )
[ "Which", "user", "has", "a", "higher", "reputation", ",", "Harlan", "or", "Jarrod", "Dixon", "?" ]
[ { "id": 3, "type": "value", "value": "Jarrod Dixon" }, { "id": 1, "type": "column", "value": "displayname" }, { "id": 4, "type": "column", "value": "reputation" }, { "id": 2, "type": "value", "value": "Harlan" }, { "id": 0, "type": "table", "value": "users" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "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-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "I-VALUE", "O" ]
13,222
toxicology
bird:dev.json:336
in molecules with triple bonds, how many of them are not carcinogenic?
SELECT COUNT(DISTINCT T1.molecule_id) FROM molecule AS T1 INNER JOIN bond AS T2 ON T1.molecule_id = T2.molecule_id WHERE T2.bond_type = '#' AND T1.label = '-'
[ "in", "molecules", "with", "triple", "bonds", ",", "how", "many", "of", "them", "are", "not", "carcinogenic", "?" ]
[ { "id": 2, "type": "column", "value": "molecule_id" }, { "id": 3, "type": "column", "value": "bond_type" }, { "id": 0, "type": "table", "value": "molecule" }, { "id": 5, "type": "column", "value": "label" }, { "id": 1, "type": "table", "value": "bond" }, { "id": 4, "type": "value", "value": "#" }, { "id": 6, "type": "value", "value": "-" } ]
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[ "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
13,224
video_games
bird:train.json:3363
What is the average number of sales in Japan?
SELECT AVG(T2.num_sales) * 100000 AS avg_japan FROM region AS T1 INNER JOIN region_sales AS T2 ON T1.id = T2.region_id WHERE T1.region_name = 'Japan'
[ "What", "is", "the", "average", "number", "of", "sales", "in", "Japan", "?" ]
[ { "id": 1, "type": "table", "value": "region_sales" }, { "id": 2, "type": "column", "value": "region_name" }, { "id": 6, "type": "column", "value": "region_id" }, { "id": 7, "type": "column", "value": "num_sales" }, { "id": 0, "type": "table", "value": "region" }, { "id": 4, "type": "value", "value": "100000" }, { "id": 3, "type": "value", "value": "Japan" }, { "id": 5, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O" ]
13,225
talkingdata
bird:train.json:1088
Please list the location coordinates of all the devices with an inactive app user when event no.2 happened.
SELECT DISTINCT T2.longitude, T2.latitude FROM app_events AS T1 INNER JOIN events AS T2 ON T2.event_id = T1.event_id WHERE T2.event_id = 2 AND T1.is_active = 0
[ "Please", "list", "the", "location", "coordinates", "of", "all", "the", "devices", "with", "an", "inactive", "app", "user", "when", "event", "no.2", "happened", "." ]
[ { "id": 2, "type": "table", "value": "app_events" }, { "id": 0, "type": "column", "value": "longitude" }, { "id": 6, "type": "column", "value": "is_active" }, { "id": 1, "type": "column", "value": "latitude" }, { "id": 4, "type": "column", "value": "event_id" }, { "id": 3, "type": "table", "value": "events" }, { "id": 5, "type": "value", "value": "2" }, { "id": 7, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
13,226
school_finance
spider:train_spider.json:1904
How many budget record has a budget amount smaller than the invested amount?
SELECT count(*) FROM budget WHERE budgeted < invested
[ "How", "many", "budget", "record", "has", "a", "budget", "amount", "smaller", "than", "the", "invested", "amount", "?" ]
[ { "id": 1, "type": "column", "value": "budgeted" }, { "id": 2, "type": "column", "value": "invested" }, { "id": 0, "type": "table", "value": "budget" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
13,227
student_club
bird:dev.json:1458
Calculate the difference in the percentage of members in New Jersey and Vermont.
SELECT CAST((SUM(CASE WHEN T2.state = 'New Jersey' THEN 1 ELSE 0 END) - SUM(CASE WHEN T2.state = 'Vermont' THEN 1 ELSE 0 END)) AS REAL) * 100 / COUNT(T1.member_id) AS diff FROM member AS T1 INNER JOIN zip_code AS T2 ON T2.zip_code = T1.zip
[ "Calculate", "the", "difference", "in", "the", "percentage", "of", "members", "in", "New", "Jersey", "and", "Vermont", "." ]
[ { "id": 9, "type": "value", "value": "New Jersey" }, { "id": 5, "type": "column", "value": "member_id" }, { "id": 1, "type": "table", "value": "zip_code" }, { "id": 2, "type": "column", "value": "zip_code" }, { "id": 10, "type": "value", "value": "Vermont" }, { "id": 0, "type": "table", "value": "member" }, { "id": 8, "type": "column", "value": "state" }, { "id": 3, "type": "column", "value": "zip" }, { "id": 4, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O" ]
13,228
store_1
spider:train_spider.json:628
What are the names of the albums that have more than 10 tracks?
SELECT T1.title FROM albums AS T1 JOIN tracks AS T2 ON T1.id = T2.album_id GROUP BY T1.id HAVING count(T1.id) > 10;
[ "What", "are", "the", "names", "of", "the", "albums", "that", "have", "more", "than", "10", "tracks", "?" ]
[ { "id": 5, "type": "column", "value": "album_id" }, { "id": 2, "type": "table", "value": "albums" }, { "id": 3, "type": "table", "value": "tracks" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "column", "value": "id" }, { "id": 4, "type": "value", "value": "10" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
13,229
car_road_race
bird:test.json:1321
Return the different constructors of drivers, ordered by age ascending.
SELECT DISTINCT CONSTRUCTOR FROM driver ORDER BY Age ASC
[ "Return", "the", "different", "constructors", "of", "drivers", ",", "ordered", "by", "age", "ascending", "." ]
[ { "id": 1, "type": "column", "value": "constructor" }, { "id": 0, "type": "table", "value": "driver" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O" ]
13,231
college_2
spider:train_spider.json:1344
Find the title, credit, and department name of courses that have more than one prerequisites?
SELECT T1.title , T1.credits , T1.dept_name FROM course AS T1 JOIN prereq AS T2 ON T1.course_id = T2.course_id GROUP BY T2.course_id HAVING count(*) > 1
[ "Find", "the", "title", ",", "credit", ",", "and", "department", "name", "of", "courses", "that", "have", "more", "than", "one", "prerequisites", "?" ]
[ { "id": 0, "type": "column", "value": "course_id" }, { "id": 3, "type": "column", "value": "dept_name" }, { "id": 2, "type": "column", "value": "credits" }, { "id": 4, "type": "table", "value": "course" }, { "id": 5, "type": "table", "value": "prereq" }, { "id": 1, "type": "column", "value": "title" }, { "id": 6, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
13,232
customers_and_addresses
spider:train_spider.json:6117
How many customers have at least one order with status "Cancelled"?
SELECT count(DISTINCT customer_id) FROM customer_orders WHERE order_status = "Cancelled"
[ "How", "many", "customers", "have", "at", "least", "one", "order", "with", "status", "\"", "Cancelled", "\"", "?" ]
[ { "id": 0, "type": "table", "value": "customer_orders" }, { "id": 1, "type": "column", "value": "order_status" }, { "id": 3, "type": "column", "value": "customer_id" }, { "id": 2, "type": "column", "value": "Cancelled" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O" ]
13,233
soccer_2
spider:train_spider.json:4944
What is the total enrollment number of all colleges?
SELECT sum(enr) FROM College
[ "What", "is", "the", "total", "enrollment", "number", "of", "all", "colleges", "?" ]
[ { "id": 0, "type": "table", "value": "college" }, { "id": 1, "type": "column", "value": "enr" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
13,234
university_basketball
spider:train_spider.json:982
Return the founded year for the school with the largest enrollment.
SELECT founded FROM university ORDER BY enrollment DESC LIMIT 1
[ "Return", "the", "founded", "year", "for", "the", "school", "with", "the", "largest", "enrollment", "." ]
[ { "id": 0, "type": "table", "value": "university" }, { "id": 2, "type": "column", "value": "enrollment" }, { "id": 1, "type": "column", "value": "founded" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
13,235
retail_world
bird:train.json:6337
Who is in charge of the "Santa Monica" territory? Give the full name.
SELECT T1.FirstName, T1.LastName FROM Employees AS T1 INNER JOIN EmployeeTerritories AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Territories AS T3 ON T2.TerritoryID = T3.TerritoryID WHERE T3.TerritoryDescription = 'Santa Monica'
[ "Who", "is", "in", "charge", "of", "the", "\"", "Santa", "Monica", "\"", "territory", "?", "Give", "the", "full", "name", "." ]
[ { "id": 3, "type": "column", "value": "territorydescription" }, { "id": 6, "type": "table", "value": "employeeterritories" }, { "id": 4, "type": "value", "value": "Santa Monica" }, { "id": 2, "type": "table", "value": "territories" }, { "id": 7, "type": "column", "value": "territoryid" }, { "id": 8, "type": "column", "value": "employeeid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 5, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "lastname" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-COLUMN", "B-TABLE", "I-TABLE", "O", "O", "B-COLUMN", "O" ]
13,236
retail_complains
bird:train.json:276
What is the email id of clients whose calls were hung?
SELECT T1.email FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T2.outcome = 'HANG'
[ "What", "is", "the", "email", "i", "d", "of", "clients", "whose", "calls", "were", "hung", "?" ]
[ { "id": 2, "type": "table", "value": "callcenterlogs" }, { "id": 6, "type": "column", "value": "rand client" }, { "id": 5, "type": "column", "value": "client_id" }, { "id": 3, "type": "column", "value": "outcome" }, { "id": 1, "type": "table", "value": "client" }, { "id": 0, "type": "column", "value": "email" }, { "id": 4, "type": "value", "value": "HANG" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
13,237
college_2
spider:train_spider.json:1451
Give the title and credits for the course that is taught in the classroom with the greatest capacity.
SELECT T3.title , T3.credits FROM classroom AS T1 JOIN SECTION AS T2 ON T1.building = T2.building AND T1.room_number = T2.room_number JOIN course AS T3 ON T2.course_id = T3.course_id WHERE T1.capacity = (SELECT max(capacity) FROM classroom)
[ "Give", "the", "title", "and", "credits", "for", "the", "course", "that", "is", "taught", "in", "the", "classroom", "with", "the", "greatest", "capacity", "." ]
[ { "id": 8, "type": "column", "value": "room_number" }, { "id": 4, "type": "table", "value": "classroom" }, { "id": 6, "type": "column", "value": "course_id" }, { "id": 3, "type": "column", "value": "capacity" }, { "id": 7, "type": "column", "value": "building" }, { "id": 1, "type": "column", "value": "credits" }, { "id": 5, "type": "table", "value": "section" }, { "id": 2, "type": "table", "value": "course" }, { "id": 0, "type": "column", "value": "title" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
13,239
airline
bird:train.json:5845
How many planes of Spirit Air Lines took off on 2018/8/7?
SELECT COUNT(T2.Code) FROM Airlines AS T1 INNER JOIN `Air Carriers` AS T2 ON T1.OP_CARRIER_AIRLINE_ID = T2.Code WHERE T1.FL_DATE = '2018/8/7' AND T2.Description = 'Spirit Air Lines: NK'
[ "How", "many", "planes", "of", "Spirit", "Air", "Lines", "took", "off", "on", "2018/8/7", "?" ]
[ { "id": 3, "type": "column", "value": "op_carrier_airline_id" }, { "id": 7, "type": "value", "value": "Spirit Air Lines: NK" }, { "id": 1, "type": "table", "value": "Air Carriers" }, { "id": 6, "type": "column", "value": "description" }, { "id": 0, "type": "table", "value": "airlines" }, { "id": 5, "type": "value", "value": "2018/8/7" }, { "id": 4, "type": "column", "value": "fl_date" }, { "id": 2, "type": "column", "value": "code" } ]
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[ "O", "O", "O", "O", "B-VALUE", "B-TABLE", "I-TABLE", "O", "O", "O", "B-VALUE", "O" ]
13,240
planet_1
bird:test.json:1857
What is the total weight of all the packages that customer Leo Wong sent?
SELECT sum(T1.Weight) FROM PACKAGE AS T1 JOIN Client AS T2 ON T1.Sender = T2.AccountNumber WHERE T2.Name = "Leo Wong";
[ "What", "is", "the", "total", "weight", "of", "all", "the", "packages", "that", "customer", "Leo", "Wong", "sent", "?" ]
[ { "id": 6, "type": "column", "value": "accountnumber" }, { "id": 3, "type": "column", "value": "Leo Wong" }, { "id": 0, "type": "table", "value": "package" }, { "id": 1, "type": "table", "value": "client" }, { "id": 4, "type": "column", "value": "weight" }, { "id": 5, "type": "column", "value": "sender" }, { "id": 2, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
13,241
talkingdata
bird:train.json:1137
What is the ID of the device used by the youngest user?
SELECT device_id FROM gender_age WHERE age = ( SELECT MIN(age) FROM gender_age )
[ "What", "is", "the", "ID", "of", "the", "device", "used", "by", "the", "youngest", "user", "?" ]
[ { "id": 0, "type": "table", "value": "gender_age" }, { "id": 1, "type": "column", "value": "device_id" }, { "id": 2, "type": "column", "value": "age" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
13,242
csu_1
spider:train_spider.json:2362
What campus had more than 400 total enrollment but more than 200 full time enrollment in year 1956?
SELECT T1.campus FROM campuses AS t1 JOIN enrollments AS t2 ON t1.id = t2.campus WHERE t2.year = 1956 AND totalenrollment_ay > 400 AND FTE_AY > 200
[ "What", "campus", "had", "more", "than", "400", "total", "enrollment", "but", "more", "than", "200", "full", "time", "enrollment", "in", "year", "1956", "?" ]
[ { "id": 6, "type": "column", "value": "totalenrollment_ay" }, { "id": 2, "type": "table", "value": "enrollments" }, { "id": 1, "type": "table", "value": "campuses" }, { "id": 0, "type": "column", "value": "campus" }, { "id": 8, "type": "column", "value": "fte_ay" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "1956" }, { "id": 7, "type": "value", "value": "400" }, { "id": 9, "type": "value", "value": "200" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-COLUMN", "B-TABLE", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
13,243
genes
bird:train.json:2490
How many non-essential genes are located in the nucleus?
SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID WHERE T2.Localization = 'nucleus' AND T1.Essential = 'Non-Essential'
[ "How", "many", "non", "-", "essential", "genes", "are", "located", "in", "the", "nucleus", "?" ]
[ { "id": 1, "type": "table", "value": "classification" }, { "id": 6, "type": "value", "value": "Non-Essential" }, { "id": 3, "type": "column", "value": "localization" }, { "id": 5, "type": "column", "value": "essential" }, { "id": 4, "type": "value", "value": "nucleus" }, { "id": 2, "type": "column", "value": "geneid" }, { "id": 0, "type": "table", "value": "genes" } ]
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[ "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
13,244
music_2
spider:train_spider.json:5203
What are the different instruments listed in the database?
SELECT DISTINCT instrument FROM Instruments
[ "What", "are", "the", "different", "instruments", "listed", "in", "the", "database", "?" ]
[ { "id": 0, "type": "table", "value": "instruments" }, { "id": 1, "type": "column", "value": "instrument" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
13,245
hockey
bird:train.json:7742
Which position has won the most awards and who is the most recent player that was awarded with an award in that position? Indicate the name of the award and the full name of the player.
SELECT T1.pos, T2.award, T1.nameGiven, T1.lastName FROM Master AS T1 INNER JOIN AwardsCoaches AS T2 ON T2.coachID = T1.coachID GROUP BY T1.pos, T2.award, T1.nameGiven, T1.lastName ORDER BY COUNT(T2.award) LIMIT 1
[ "Which", "position", "has", "won", "the", "most", "awards", "and", "who", "is", "the", "most", "recent", "player", "that", "was", "awarded", "with", "an", "award", "in", "that", "position", "?", "Indicate", "the", "name", "of", "the", "award", "and", "the", "full", "name", "of", "the", "player", "." ]
[ { "id": 5, "type": "table", "value": "awardscoaches" }, { "id": 2, "type": "column", "value": "namegiven" }, { "id": 3, "type": "column", "value": "lastname" }, { "id": 6, "type": "column", "value": "coachid" }, { "id": 4, "type": "table", "value": "master" }, { "id": 1, "type": "column", "value": "award" }, { "id": 0, "type": "column", "value": "pos" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
13,246
hr_1
spider:train_spider.json:3520
What are the full names and cities of employees who have the letter Z in their first names?
SELECT T1.first_name , T1.last_name , T3.city FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id JOIN locations AS T3 ON T2.location_id = T3.location_id WHERE T1.first_name LIKE '%z%'
[ "What", "are", "the", "full", "names", "and", "cities", "of", "employees", "who", "have", "the", "letter", "Z", "in", "their", "first", "names", "?" ]
[ { "id": 8, "type": "column", "value": "department_id" }, { "id": 6, "type": "table", "value": "departments" }, { "id": 7, "type": "column", "value": "location_id" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 3, "type": "table", "value": "locations" }, { "id": 5, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "city" }, { "id": 4, "type": "value", "value": "%z%" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
13,247
formula_1
spider:train_spider.json:2165
What are the forename and surname of the driver who has the smallest laptime?
SELECT T1.forename , T1.surname FROM drivers AS T1 JOIN laptimes AS T2 ON T1.driverid = T2.driverid ORDER BY T2.milliseconds LIMIT 1
[ "What", "are", "the", "forename", "and", "surname", "of", "the", "driver", "who", "has", "the", "smallest", "laptime", "?" ]
[ { "id": 4, "type": "column", "value": "milliseconds" }, { "id": 0, "type": "column", "value": "forename" }, { "id": 3, "type": "table", "value": "laptimes" }, { "id": 5, "type": "column", "value": "driverid" }, { "id": 1, "type": "column", "value": "surname" }, { "id": 2, "type": "table", "value": "drivers" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O" ]
13,248
public_review_platform
bird:train.json:3935
How many users have no followers in 2014?
SELECT COUNT(user_id) FROM Users WHERE user_yelping_since_year = 2004 AND user_fans LIKE 'None'
[ "How", "many", "users", "have", "no", "followers", "in", "2014", "?" ]
[ { "id": 2, "type": "column", "value": "user_yelping_since_year" }, { "id": 4, "type": "column", "value": "user_fans" }, { "id": 1, "type": "column", "value": "user_id" }, { "id": 0, "type": "table", "value": "users" }, { "id": 3, "type": "value", "value": "2004" }, { "id": 5, "type": "value", "value": "None" } ]
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[ "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "B-VALUE", "O" ]
13,249
company_employee
spider:train_spider.json:4110
List the names of people that are not employed by any company
SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM employment)
[ "List", "the", "names", "of", "people", "that", "are", "not", "employed", "by", "any", "company" ]
[ { "id": 3, "type": "table", "value": "employment" }, { "id": 2, "type": "column", "value": "people_id" }, { "id": 0, "type": "table", "value": "people" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
13,250
superstore
bird:train.json:2384
From which city and state does the customer that bought the product with the highest sales?
SELECT T5.City, T5.State FROM west_superstore AS T1 INNER JOIN east_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN central_superstore AS T3 ON T3.`Customer ID` = T2.`Customer ID` INNER JOIN south_superstore AS T4 ON T4.`Customer ID` = T3.`Customer ID` INNER JOIN people AS T5 ON T5.`Customer ID` = T4.`Customer ID` ORDER BY T2.Sales DESC LIMIT 1
[ "From", "which", "city", "and", "state", "does", "the", "customer", "that", "bought", "the", "product", "with", "the", "highest", "sales", "?" ]
[ { "id": 6, "type": "table", "value": "central_superstore" }, { "id": 4, "type": "table", "value": "south_superstore" }, { "id": 7, "type": "table", "value": "west_superstore" }, { "id": 8, "type": "table", "value": "east_superstore" }, { "id": 5, "type": "column", "value": "Customer ID" }, { "id": 2, "type": "table", "value": "people" }, { "id": 1, "type": "column", "value": "state" }, { "id": 3, "type": "column", "value": "sales" }, { "id": 0, "type": "column", "value": "city" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
13,251
university
bird:train.json:8016
Calculate the total number of students in universities located in Sweden.
SELECT SUM(T2.num_students) FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id INNER JOIN country AS T3 ON T3.id = T1.country_id WHERE T3.country_name = 'Sweden'
[ "Calculate", "the", "total", "number", "of", "students", "in", "universities", "located", "in", "Sweden", "." ]
[ { "id": 5, "type": "table", "value": "university_year" }, { "id": 8, "type": "column", "value": "university_id" }, { "id": 1, "type": "column", "value": "country_name" }, { "id": 3, "type": "column", "value": "num_students" }, { "id": 4, "type": "table", "value": "university" }, { "id": 7, "type": "column", "value": "country_id" }, { "id": 0, "type": "table", "value": "country" }, { "id": 2, "type": "value", "value": "Sweden" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
13,252
works_cycles
bird:train.json:7084
List, by ProductID, all products whose profit, relative to the standard price, is negative.
SELECT DISTINCT ProductID FROM ProductVendor WHERE StandardPrice - LastReceiptCost < 0
[ "List", ",", "by", "ProductID", ",", "all", "products", "whose", "profit", ",", "relative", "to", "the", "standard", "price", ",", "is", "negative", "." ]
[ { "id": 4, "type": "column", "value": "lastreceiptcost" }, { "id": 0, "type": "table", "value": "productvendor" }, { "id": 3, "type": "column", "value": "standardprice" }, { "id": 1, "type": "column", "value": "productid" }, { "id": 2, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 13, 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
13,253
products_gen_characteristics
spider:train_spider.json:5537
Return the category code and typical price of 'cumin'.
SELECT product_category_code , typical_buying_price FROM products WHERE product_name = "cumin"
[ "Return", "the", "category", "code", "and", "typical", "price", "of", "'", "cumin", "'", "." ]
[ { "id": 1, "type": "column", "value": "product_category_code" }, { "id": 2, "type": "column", "value": "typical_buying_price" }, { "id": 3, "type": "column", "value": "product_name" }, { "id": 0, "type": "table", "value": "products" }, { "id": 4, "type": "column", "value": "cumin" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
13,254
soccer_2016
bird:train.json:1863
How many times did Yuvraj Singh receive the Man of the Match award?
SELECT SUM(CASE WHEN T2.Player_Name = 'Yuvraj Singh' THEN 1 ELSE 0 END) FROM Match AS T1 INNER JOIN Player AS T2 ON T2.Player_Id = T1.Man_of_the_Match
[ "How", "many", "times", "did", "Yuvraj", "Singh", "receive", "the", "Man", "of", "the", "Match", "award", "?" ]
[ { "id": 3, "type": "column", "value": "man_of_the_match" }, { "id": 7, "type": "value", "value": "Yuvraj Singh" }, { "id": 6, "type": "column", "value": "player_name" }, { "id": 2, "type": "column", "value": "player_id" }, { "id": 1, "type": "table", "value": "player" }, { "id": 0, "type": "table", "value": "match" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 4, 5 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-TABLE", "O", "O" ]
13,255
department_store
spider:train_spider.json:4726
Return the average price for each product type.
SELECT product_type_code , avg(product_price) FROM products GROUP BY product_type_code
[ "Return", "the", "average", "price", "for", "each", "product", "type", "." ]
[ { "id": 1, "type": "column", "value": "product_type_code" }, { "id": 2, "type": "column", "value": "product_price" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
13,256
retail_complains
bird:train.json:364
What is the average age of clients whose complaint type is "TT"?
SELECT AVG(T1.age) FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T2.type = 'TT'
[ "What", "is", "the", "average", "age", "of", "clients", "whose", "complaint", "type", "is", "\"", "TT", "\"", "?" ]
[ { "id": 1, "type": "table", "value": "callcenterlogs" }, { "id": 6, "type": "column", "value": "rand client" }, { "id": 5, "type": "column", "value": "client_id" }, { "id": 0, "type": "table", "value": "client" }, { "id": 2, "type": "column", "value": "type" }, { "id": 4, "type": "column", "value": "age" }, { "id": 3, "type": "value", "value": "TT" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O" ]
13,257
bike_share_1
bird:train.json:9094
What is the average duration of trips for the starting station of Santa Clara at Almaden and what is the latitude and longitude of this station?
SELECT AVG(T1.duration), T2.lat, T2.long FROM trip AS T1 LEFT JOIN station AS T2 ON T2.name = T1.start_station_name LEFT JOIN station AS T3 ON T3.name = T1.end_station_name WHERE T1.start_station_name = 'Santa Clara at Almaden'
[ "What", "is", "the", "average", "duration", "of", "trips", "for", "the", "starting", "station", "of", "Santa", "Clara", "at", "Almaden", "and", "what", "is", "the", "latitude", "and", "longitude", "of", "this", "station", "?" ]
[ { "id": 4, "type": "value", "value": "Santa Clara at Almaden" }, { "id": 3, "type": "column", "value": "start_station_name" }, { "id": 8, "type": "column", "value": "end_station_name" }, { "id": 5, "type": "column", "value": "duration" }, { "id": 2, "type": "table", "value": "station" }, { "id": 1, "type": "column", "value": "long" }, { "id": 6, "type": "table", "value": "trip" }, { "id": 7, "type": "column", "value": "name" }, { "id": 0, "type": "column", "value": "lat" } ]
[ { "entity_id": 0, "token_idxs": [ 14 ] }, { "entity_id": 1, "token_idxs": [ 22 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 12, 13, 15 ] }, { "entity_id": 5, "token_idxs": [ 4 ] }, { "entity_id": 6, "token_idxs": [ 6 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 25 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-TABLE", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
13,258
driving_school
spider:train_spider.json:6651
How many employees live in Georgia?
SELECT count(*) FROM Addresses WHERE state_province_county = "Georgia";
[ "How", "many", "employees", "live", "in", "Georgia", "?" ]
[ { "id": 1, "type": "column", "value": "state_province_county" }, { "id": 0, "type": "table", "value": "addresses" }, { "id": 2, "type": "column", "value": "Georgia" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "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", "O", "O", "O", "B-COLUMN", "O" ]
13,259
public_review_platform
bird:train.json:3802
Please indicate the review count of the "active life" businesses in Phoenix.
SELECT COUNT(*) FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T1.category_name = 'Active Life' AND T3.city = 'Phoenix'
[ "Please", "indicate", "the", "review", "count", "of", "the", "\"", "active", "life", "\"", "businesses", "in", "Phoenix", "." ]
[ { "id": 2, "type": "table", "value": "business_categories" }, { "id": 4, "type": "column", "value": "category_name" }, { "id": 3, "type": "column", "value": "business_id" }, { "id": 5, "type": "value", "value": "Active Life" }, { "id": 8, "type": "column", "value": "category_id" }, { "id": 1, "type": "table", "value": "categories" }, { "id": 0, "type": "table", "value": "business" }, { "id": 7, "type": "value", "value": "Phoenix" }, { "id": 6, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "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": [ 8, 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 13 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-TABLE", "O", "B-VALUE", "O" ]
13,260
tracking_grants_for_research
spider:train_spider.json:4347
What is the total amount of grant money given to each organization and what is its id?
SELECT sum(grant_amount) , organisation_id FROM Grants GROUP BY organisation_id
[ "What", "is", "the", "total", "amount", "of", "grant", "money", "given", "to", "each", "organization", "and", "what", "is", "its", "i", "d", "?" ]
[ { "id": 1, "type": "column", "value": "organisation_id" }, { "id": 2, "type": "column", "value": "grant_amount" }, { "id": 0, "type": "table", "value": "grants" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
13,262
public_review_platform
bird:train.json:3825
How long was the review for business number 2 that user number 612 wrote?
SELECT review_length FROM Reviews WHERE user_id = 612 AND review_stars = 5 AND business_id = 2
[ "How", "long", "was", "the", "review", "for", "business", "number", "2", "that", "user", "number", "612", "wrote", "?" ]
[ { "id": 1, "type": "column", "value": "review_length" }, { "id": 4, "type": "column", "value": "review_stars" }, { "id": 6, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "reviews" }, { "id": 2, "type": "column", "value": "user_id" }, { "id": 3, "type": "value", "value": "612" }, { "id": 5, "type": "value", "value": "5" }, { "id": 7, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 6 ] }, { "entity_id": 7, "token_idxs": [ 8 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
13,263
retail_world
bird:train.json:6642
Who was taking charge of orders from Morristown?
SELECT T1.FirstName, T1.LastName FROM Employees AS T1 INNER JOIN EmployeeTerritories AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Territories AS T3 ON T2.TerritoryID = T3.TerritoryID WHERE T3.TerritoryDescription = 'Morristown'
[ "Who", "was", "taking", "charge", "of", "orders", "from", "Morristown", "?" ]
[ { "id": 3, "type": "column", "value": "territorydescription" }, { "id": 6, "type": "table", "value": "employeeterritories" }, { "id": 2, "type": "table", "value": "territories" }, { "id": 7, "type": "column", "value": "territoryid" }, { "id": 4, "type": "value", "value": "Morristown" }, { "id": 8, "type": "column", "value": "employeeid" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 5, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "lastname" } ]
[ { "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": [ 7 ] }, { "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" ]
13,264
real_estate_rentals
bird:test.json:1400
In which states are each of the the properties located?
SELECT DISTINCT T1.county_state_province FROM Addresses AS T1 JOIN Properties AS T2 ON T1.address_id = T2.property_address_id;
[ "In", "which", "states", "are", "each", "of", "the", "the", "properties", "located", "?" ]
[ { "id": 0, "type": "column", "value": "county_state_province" }, { "id": 4, "type": "column", "value": "property_address_id" }, { "id": 2, "type": "table", "value": "properties" }, { "id": 3, "type": "column", "value": "address_id" }, { "id": 1, "type": "table", "value": "addresses" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O" ]
13,265
gas_company
spider:train_spider.json:2029
Show all locations where a gas station for company with market value greater than 100 is located.
SELECT T3.location FROM station_company AS T1 JOIN company AS T2 ON T1.company_id = T2.company_id JOIN gas_station AS T3 ON T1.station_id = T3.station_id WHERE T2.market_value > 100
[ "Show", "all", "locations", "where", "a", "gas", "station", "for", "company", "with", "market", "value", "greater", "than", "100", "is", "located", "." ]
[ { "id": 4, "type": "table", "value": "station_company" }, { "id": 2, "type": "column", "value": "market_value" }, { "id": 1, "type": "table", "value": "gas_station" }, { "id": 6, "type": "column", "value": "station_id" }, { "id": 7, "type": "column", "value": "company_id" }, { "id": 0, "type": "column", "value": "location" }, { "id": 5, "type": "table", "value": "company" }, { "id": 3, "type": "value", "value": "100" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "B-TABLE", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O", "O", "O" ]
13,266
driving_school
spider:train_spider.json:6661
What are the email addresses and date of births for all customers who have a first name of Carole?
SELECT email_address , date_of_birth FROM Customers WHERE first_name = "Carole"
[ "What", "are", "the", "email", "addresses", "and", "date", "of", "births", "for", "all", "customers", "who", "have", "a", "first", "name", "of", "Carole", "?" ]
[ { "id": 1, "type": "column", "value": "email_address" }, { "id": 2, "type": "column", "value": "date_of_birth" }, { "id": 3, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 4, "type": "column", "value": "Carole" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O" ]
13,267
county_public_safety
spider:train_spider.json:2565
What are the names of counties that do not contain any cities?
SELECT Name FROM county_public_safety WHERE County_ID NOT IN (SELECT County_ID FROM city)
[ "What", "are", "the", "names", "of", "counties", "that", "do", "not", "contain", "any", "cities", "?" ]
[ { "id": 0, "type": "table", "value": "county_public_safety" }, { "id": 2, "type": "column", "value": "county_id" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "table", "value": "city" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
13,268
works_cycles
bird:train.json:7269
What product has the fewest online orders from one customer? List the product's class, line of business, and list price.
SELECT T2.Class, T2.ProductLine, T2.ListPrice FROM ShoppingCartItem AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID GROUP BY T1.ProductID ORDER BY SUM(Quantity) LIMIT 1
[ "What", "product", "has", "the", "fewest", "online", "orders", "from", "one", "customer", "?", "List", "the", "product", "'s", "class", ",", "line", "of", "business", ",", "and", "list", "price", "." ]
[ { "id": 4, "type": "table", "value": "shoppingcartitem" }, { "id": 2, "type": "column", "value": "productline" }, { "id": 0, "type": "column", "value": "productid" }, { "id": 3, "type": "column", "value": "listprice" }, { "id": 6, "type": "column", "value": "quantity" }, { "id": 5, "type": "table", "value": "product" }, { "id": 1, "type": "column", "value": "class" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
13,269
flight_4
spider:train_spider.json:6853
How many cities are there that have more than 3 airports?
SELECT count(*) FROM (SELECT city FROM airports GROUP BY city HAVING count(*) > 3)
[ "How", "many", "cities", "are", "there", "that", "have", "more", "than", "3", "airports", "?" ]
[ { "id": 0, "type": "table", "value": "airports" }, { "id": 1, "type": "column", "value": "city" }, { "id": 2, "type": "value", "value": "3" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]