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14,232
student_club
bird:dev.json:1365
What are the expenses of the budget with the lowest remaining?
SELECT T2.expense_description FROM budget AS T1 INNER JOIN expense AS T2 ON T1.budget_id = T2.link_to_budget ORDER BY T1.remaining LIMIT 1
[ "What", "are", "the", "expenses", "of", "the", "budget", "with", "the", "lowest", "remaining", "?" ]
[ { "id": 0, "type": "column", "value": "expense_description" }, { "id": 5, "type": "column", "value": "link_to_budget" }, { "id": 3, "type": "column", "value": "remaining" }, { "id": 4, "type": "column", "value": "budget_id" }, { "id": 2, "type": "table", "value": "expense" }, { "id": 1, "type": "table", "value": "budget" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
14,233
talkingdata
bird:train.json:1125
Give the number of "game-Fishing" apps.
SELECT COUNT(T2.app_id) FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T1.category = 'game-Fishing'
[ "Give", "the", "number", "of", "\"", "game", "-", "Fishing", "\"", "apps", "." ]
[ { "id": 0, "type": "table", "value": "label_categories" }, { "id": 3, "type": "value", "value": "game-Fishing" }, { "id": 1, "type": "table", "value": "app_labels" }, { "id": 2, "type": "column", "value": "category" }, { "id": 5, "type": "column", "value": "label_id" }, { "id": 4, "type": "column", "value": "app_id" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "B-COLUMN", "O" ]
14,234
driving_school
spider:train_spider.json:6663
What are the phone numbers and email addresses of all customers who have an outstanding balance of more than 2000?
SELECT phone_number , email_address FROM Customers WHERE amount_outstanding > 2000;
[ "What", "are", "the", "phone", "numbers", "and", "email", "addresses", "of", "all", "customers", "who", "have", "an", "outstanding", "balance", "of", "more", "than", "2000", "?" ]
[ { "id": 3, "type": "column", "value": "amount_outstanding" }, { "id": 2, "type": "column", "value": "email_address" }, { "id": 1, "type": "column", "value": "phone_number" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 4, "type": "value", "value": "2000" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 6, 7 ] }, { "entity_id": 3, "token_idxs": [ 13, 14 ] }, { "entity_id": 4, "token_idxs": [ 19 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-VALUE", "O" ]
14,235
planet_1
bird:test.json:1898
What are the ids of all shipments on the planet Mars that are managed by Turanga Leela?
SELECT T1.ShipmentID FROM Shipment AS T1 JOIN Planet AS T2 ON T1.Planet = T2.PlanetID JOIN Employee AS T3 ON T3.EmployeeID = T1.Manager WHERE T2.Name = "Mars" AND T3.Name = "Turanga Leela";
[ "What", "are", "the", "ids", "of", "all", "shipments", "on", "the", "planet", "Mars", "that", "are", "managed", "by", "Turanga", "Leela", "?" ]
[ { "id": 8, "type": "column", "value": "Turanga Leela" }, { "id": 0, "type": "column", "value": "shipmentid" }, { "id": 4, "type": "column", "value": "employeeid" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 2, "type": "table", "value": "shipment" }, { "id": 10, "type": "column", "value": "planetid" }, { "id": 5, "type": "column", "value": "manager" }, { "id": 3, "type": "table", "value": "planet" }, { "id": 9, "type": "column", "value": "planet" }, { "id": 6, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "Mars" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 10 ] }, { "entity_id": 8, "token_idxs": [ 15, 16 ] }, { "entity_id": 9, "token_idxs": [ 9 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,236
store_1
spider:train_spider.json:581
What country does Roberto Almeida live?
SELECT country FROM customers WHERE first_name = "Roberto" AND last_name = "Almeida";
[ "What", "country", "does", "Roberto", "Almeida", "live", "?" ]
[ { "id": 2, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 4, "type": "column", "value": "last_name" }, { "id": 1, "type": "column", "value": "country" }, { "id": 3, "type": "column", "value": "Roberto" }, { "id": 5, "type": "column", "value": "Almeida" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 4 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "O" ]
14,237
simpson_episodes
bird:train.json:4358
List the episode ID and title of episode where casting was credited to Bonita Pietila.
SELECT T1.episode_id, T1.title FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T2.credited = 'true' AND T2.person = 'Bonita Pietila' AND T2.role = 'casting';
[ "List", "the", "episode", "ID", "and", "title", "of", "episode", "where", "casting", "was", "credited", "to", "Bonita", "Pietila", "." ]
[ { "id": 7, "type": "value", "value": "Bonita Pietila" }, { "id": 0, "type": "column", "value": "episode_id" }, { "id": 4, "type": "column", "value": "credited" }, { "id": 2, "type": "table", "value": "episode" }, { "id": 9, "type": "value", "value": "casting" }, { "id": 3, "type": "table", "value": "credit" }, { "id": 6, "type": "column", "value": "person" }, { "id": 1, "type": "column", "value": "title" }, { "id": 5, "type": "value", "value": "true" }, { "id": 8, "type": "column", "value": "role" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "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": [ 13, 14 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 9 ] }, { "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", "O", "O", "B-VALUE", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
14,238
assets_maintenance
spider:train_spider.json:3152
Which company started the earliest the maintenance contract? Show the company name.
SELECT T1.company_name FROM Third_Party_Companies AS T1 JOIN Maintenance_Contracts AS T2 ON T1.company_id = T2.maintenance_contract_company_id ORDER BY T2.contract_start_date ASC LIMIT 1
[ "Which", "company", "started", "the", "earliest", "the", "maintenance", "contract", "?", "Show", "the", "company", "name", "." ]
[ { "id": 5, "type": "column", "value": "maintenance_contract_company_id" }, { "id": 1, "type": "table", "value": "third_party_companies" }, { "id": 2, "type": "table", "value": "maintenance_contracts" }, { "id": 3, "type": "column", "value": "contract_start_date" }, { "id": 0, "type": "column", "value": "company_name" }, { "id": 4, "type": "column", "value": "company_id" } ]
[ { "entity_id": 0, "token_idxs": [ 11, 12 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 1 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,239
activity_1
spider:train_spider.json:6765
What activities do we have?
SELECT activity_name FROM Activity
[ "What", "activities", "do", "we", "have", "?" ]
[ { "id": 1, "type": "column", "value": "activity_name" }, { "id": 0, "type": "table", "value": "activity" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "O" ]
14,240
advertising_agencies
bird:test.json:2133
Show the staff id and the number of meetings attended by the staff who attended some meeting but had the lowest attendance.
SELECT staff_id , count(*) FROM Staff_in_meetings GROUP BY staff_id ORDER BY count(*) ASC LIMIT 1;
[ "Show", "the", "staff", "i", "d", "and", "the", "number", "of", "meetings", "attended", "by", "the", "staff", "who", "attended", "some", "meeting", "but", "had", "the", "lowest", "attendance", "." ]
[ { "id": 0, "type": "table", "value": "staff_in_meetings" }, { "id": 1, "type": "column", "value": "staff_id" } ]
[ { "entity_id": 0, "token_idxs": [ 8, 9 ] }, { "entity_id": 1, "token_idxs": [ 2, 3, 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", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,241
works_cycles
bird:train.json:7421
Please list the credit card numbers of all the employees who have left the Finance Department.
SELECT T3.CardNumber FROM EmployeeDepartmentHistory AS T1 INNER JOIN Department AS T2 ON T1.DepartmentID = T2.DepartmentID INNER JOIN CreditCard AS T3 ON T1.ModifiedDate = T3.ModifiedDate INNER JOIN PersonCreditCard AS T4 ON T3.CreditCardID = T4.CreditCardID WHERE T2.Name = 'Finance' AND T1.EndDate IS NOT NULL
[ "Please", "list", "the", "credit", "card", "numbers", "of", "all", "the", "employees", "who", "have", "left", "the", "Finance", "Department", "." ]
[ { "id": 7, "type": "table", "value": "employeedepartmenthistory" }, { "id": 1, "type": "table", "value": "personcreditcard" }, { "id": 3, "type": "column", "value": "creditcardid" }, { "id": 9, "type": "column", "value": "modifieddate" }, { "id": 10, "type": "column", "value": "departmentid" }, { "id": 0, "type": "column", "value": "cardnumber" }, { "id": 2, "type": "table", "value": "creditcard" }, { "id": 8, "type": "table", "value": "department" }, { "id": 5, "type": "value", "value": "Finance" }, { "id": 6, "type": "column", "value": "enddate" }, { "id": 4, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
14,243
wine_1
spider:train_spider.json:6522
What are the names of all wines produced in 2008?
SELECT Name FROM WINE WHERE YEAR = "2008"
[ "What", "are", "the", "names", "of", "all", "wines", "produced", "in", "2008", "?" ]
[ { "id": 0, "type": "table", "value": "wine" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "year" }, { "id": 3, "type": "column", "value": "2008" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
14,244
movie_3
bird:train.json:9160
How many addresses are there in Woodridge city?
SELECT COUNT(T1.address_id) FROM address AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T2.city = 'Woodridge'
[ "How", "many", "addresses", "are", "there", "in", "Woodridge", "city", "?" ]
[ { "id": 4, "type": "column", "value": "address_id" }, { "id": 3, "type": "value", "value": "Woodridge" }, { "id": 0, "type": "table", "value": "address" }, { "id": 5, "type": "column", "value": "city_id" }, { "id": 1, "type": "table", "value": "city" }, { "id": 2, "type": "column", "value": "city" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,245
hockey
bird:train.json:7622
List all goalies from year 2000 to 2010 for team COL. State their given name, height, weight and age of today.
SELECT T1.nameGiven, T1.height , T1.weight, STRFTIME('%Y', CURRENT_TIMESTAMP) - birthYear FROM Master AS T1 INNER JOIN Goalies AS T2 ON T1.playerID = T2.playerID WHERE T2.tmID = 'COL' AND T2.year >= 2000 AND T2.year <= 2010 GROUP BY T1.playerID
[ "List", "all", "goalies", "from", "year", "2000", "to", "2010", "for", "team", "COL", ".", "State", "their", "given", "name", ",", "height", ",", "weight", "and", "age", "of", "today", "." ]
[ { "id": 1, "type": "column", "value": "namegiven" }, { "id": 6, "type": "column", "value": "birthyear" }, { "id": 0, "type": "column", "value": "playerid" }, { "id": 5, "type": "table", "value": "goalies" }, { "id": 2, "type": "column", "value": "height" }, { "id": 3, "type": "column", "value": "weight" }, { "id": 4, "type": "table", "value": "master" }, { "id": 7, "type": "column", "value": "tmid" }, { "id": 9, "type": "column", "value": "year" }, { "id": 10, "type": "value", "value": "2000" }, { "id": 11, "type": "value", "value": "2010" }, { "id": 8, "type": "value", "value": "COL" }, { "id": 12, "type": "value", "value": "%Y" } ]
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[ "O", "O", "B-TABLE", "O", "B-COLUMN", "B-VALUE", "O", "B-VALUE", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
14,246
computer_student
bird:train.json:987
Please list the IDs of the teachers who have advised more than 4 others to teach.
SELECT p_id_dummy FROM advisedBy GROUP BY p_id_dummy HAVING COUNT(p_id_dummy) > 4
[ "Please", "list", "the", "IDs", "of", "the", "teachers", "who", "have", "advised", "more", "than", "4", "others", "to", "teach", "." ]
[ { "id": 1, "type": "column", "value": "p_id_dummy" }, { "id": 0, "type": "table", "value": "advisedby" }, { "id": 2, "type": "value", "value": "4" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
14,247
device
spider:train_spider.json:5052
List the carriers of devices in ascending alphabetical order.
SELECT Carrier FROM device ORDER BY Carrier ASC
[ "List", "the", "carriers", "of", "devices", "in", "ascending", "alphabetical", "order", "." ]
[ { "id": 1, "type": "column", "value": "carrier" }, { "id": 0, "type": "table", "value": "device" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
14,248
professional_basketball
bird:train.json:2852
From 1950 to 1970, what is the maximum point of players whose teams were ranked 1?
SELECT MAX(T2.points) FROM teams AS T1 INNER JOIN players_teams AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.year BETWEEN 1950 AND 1970 AND T1.rank = 1
[ "From", "1950", "to", "1970", ",", "what", "is", "the", "maximum", "point", "of", "players", "whose", "teams", "were", "ranked", "1", "?" ]
[ { "id": 1, "type": "table", "value": "players_teams" }, { "id": 2, "type": "column", "value": "points" }, { "id": 0, "type": "table", "value": "teams" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "1950" }, { "id": 5, "type": "value", "value": "1970" }, { "id": 6, "type": "column", "value": "rank" }, { "id": 8, "type": "column", "value": "tmid" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "B-TABLE", "O", "B-COLUMN", "B-VALUE", "O" ]
14,249
customers_card_transactions
spider:train_spider.json:733
Show all transaction types.
SELECT DISTINCT transaction_type FROM Financial_Transactions
[ "Show", "all", "transaction", "types", "." ]
[ { "id": 0, "type": "table", "value": "financial_transactions" }, { "id": 1, "type": "column", "value": "transaction_type" } ]
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[ "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O" ]
14,250
food_inspection
bird:train.json:8853
Among the violations in 2016, how many of them have unscheduled inspections?
SELECT COUNT(T2.business_id) FROM violations AS T1 INNER JOIN inspections AS T2 ON T1.business_id = T2.business_id WHERE STRFTIME('%Y', T1.`date`) = '2016' AND T2.type = 'Routine - Unscheduled'
[ "Among", "the", "violations", "in", "2016", ",", "how", "many", "of", "them", "have", "unscheduled", "inspections", "?" ]
[ { "id": 5, "type": "value", "value": "Routine - Unscheduled" }, { "id": 1, "type": "table", "value": "inspections" }, { "id": 2, "type": "column", "value": "business_id" }, { "id": 0, "type": "table", "value": "violations" }, { "id": 3, "type": "value", "value": "2016" }, { "id": 4, "type": "column", "value": "type" }, { "id": 7, "type": "column", "value": "date" }, { "id": 6, "type": "value", "value": "%Y" } ]
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[ "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O" ]
14,251
tracking_software_problems
spider:train_spider.json:5374
What are the ids of the problems which are reported before 1978-06-26?
SELECT problem_id FROM problems WHERE date_problem_reported < "1978-06-26"
[ "What", "are", "the", "ids", "of", "the", "problems", "which", "are", "reported", "before", "1978", "-", "06", "-", "26", "?" ]
[ { "id": 2, "type": "column", "value": "date_problem_reported" }, { "id": 1, "type": "column", "value": "problem_id" }, { "id": 3, "type": "column", "value": "1978-06-26" }, { "id": 0, "type": "table", "value": "problems" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
14,252
student_1
spider:train_spider.json:4034
What are the first names of students studying in room 107?
SELECT DISTINCT firstname FROM list WHERE classroom = 107
[ "What", "are", "the", "first", "names", "of", "students", "studying", "in", "room", "107", "?" ]
[ { "id": 1, "type": "column", "value": "firstname" }, { "id": 2, "type": "column", "value": "classroom" }, { "id": 0, "type": "table", "value": "list" }, { "id": 3, "type": "value", "value": "107" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
14,253
game_1
spider:train_spider.json:6052
What are the first names and ages of all students who are playing both Football and Lacrosse?
SELECT fname , age FROM Student WHERE StuID IN (SELECT StuID FROM Sportsinfo WHERE SportName = "Football" INTERSECT SELECT StuID FROM Sportsinfo WHERE SportName = "Lacrosse")
[ "What", "are", "the", "first", "names", "and", "ages", "of", "all", "students", "who", "are", "playing", "both", "Football", "and", "Lacrosse", "?" ]
[ { "id": 4, "type": "table", "value": "sportsinfo" }, { "id": 5, "type": "column", "value": "sportname" }, { "id": 6, "type": "column", "value": "Football" }, { "id": 7, "type": "column", "value": "Lacrosse" }, { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "fname" }, { "id": 3, "type": "column", "value": "stuid" }, { "id": 2, "type": "column", "value": "age" } ]
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[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
14,254
driving_school
spider:train_spider.json:6671
How many customers are there?
SELECT count(*) FROM Customers;
[ "How", "many", "customers", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "customers" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O" ]
14,255
cre_Theme_park
spider:train_spider.json:5904
Find all the locations whose names contain the word "film".
SELECT Location_Name FROM LOCATIONS WHERE Location_Name LIKE "%film%"
[ "Find", "all", "the", "locations", "whose", "names", "contain", "the", "word", "\"", "film", "\"", "." ]
[ { "id": 1, "type": "column", "value": "location_name" }, { "id": 0, "type": "table", "value": "locations" }, { "id": 2, "type": "column", "value": "%film%" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,256
toxicology
bird:dev.json:226
What is the percentage of double bonds in the molecule TR008? Please provide your answer as a percentage with five decimal places.
SELECT ROUND(CAST(COUNT(CASE WHEN T.bond_type = '=' THEN T.bond_id ELSE NULL END) AS REAL) * 100 / COUNT(T.bond_id),5) FROM bond AS T WHERE T.molecule_id = 'TR008'
[ "What", "is", "the", "percentage", "of", "double", "bonds", "in", "the", "molecule", "TR008", "?", "Please", "provide", "your", "answer", "as", "a", "percentage", "with", "five", "decimal", "places", "." ]
[ { "id": 1, "type": "column", "value": "molecule_id" }, { "id": 6, "type": "column", "value": "bond_type" }, { "id": 5, "type": "column", "value": "bond_id" }, { "id": 2, "type": "value", "value": "TR008" }, { "id": 0, "type": "table", "value": "bond" }, { "id": 4, "type": "value", "value": "100" }, { "id": 3, "type": "value", "value": "5" }, { "id": 7, "type": "value", "value": "=" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,257
shakespeare
bird:train.json:3040
What are the character names in paragraph 3?
SELECT DISTINCT T1.CharName FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T2.ParagraphNum = 3
[ "What", "are", "the", "character", "names", "in", "paragraph", "3", "?" ]
[ { "id": 3, "type": "column", "value": "paragraphnum" }, { "id": 6, "type": "column", "value": "character_id" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 2, "type": "table", "value": "paragraphs" }, { "id": 0, "type": "column", "value": "charname" }, { "id": 5, "type": "column", "value": "id" }, { "id": 4, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "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", "B-COLUMN", "O", "O", "B-TABLE", "B-VALUE", "O" ]
14,258
device
spider:train_spider.json:5073
What is the name of the shop that has the most different kinds of devices in stock?
SELECT T2.Shop_Name FROM stock AS T1 JOIN shop AS T2 ON T1.Shop_ID = T2.Shop_ID GROUP BY T1.Shop_ID ORDER BY COUNT(*) DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "shop", "that", "has", "the", "most", "different", "kinds", "of", "devices", "in", "stock", "?" ]
[ { "id": 1, "type": "column", "value": "shop_name" }, { "id": 0, "type": "column", "value": "shop_id" }, { "id": 2, "type": "table", "value": "stock" }, { "id": 3, "type": "table", "value": "shop" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 16 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,259
olympics
bird:train.json:5010
How many games has Prithipal Singh participated in?
SELECT COUNT(T2.games_id) FROM person AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.person_id WHERE T1.full_name = 'Prithipal Singh'
[ "How", "many", "games", "has", "Prithipal", "Singh", "participated", "in", "?" ]
[ { "id": 1, "type": "table", "value": "games_competitor" }, { "id": 3, "type": "value", "value": "Prithipal Singh" }, { "id": 2, "type": "column", "value": "full_name" }, { "id": 6, "type": "column", "value": "person_id" }, { "id": 4, "type": "column", "value": "games_id" }, { "id": 0, "type": "table", "value": "person" }, { "id": 5, "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, 5 ] }, { "entity_id": 4, "token_idxs": [ 2 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O", "O" ]
14,260
boat_1
bird:test.json:891
What are the average rating and max age of all sailors?
SELECT AVG(rating) , MAX(age) FROM Sailors
[ "What", "are", "the", "average", "rating", "and", "max", "age", "of", "all", "sailors", "?" ]
[ { "id": 0, "type": "table", "value": "sailors" }, { "id": 1, "type": "column", "value": "rating" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "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", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,261
donor
bird:train.json:3273
In which cities are Los Angeles County Suburban Metro Schools located?
SELECT school_city FROM projects WHERE school_metro = 'suburban' AND school_county = 'Los Angeles'
[ "In", "which", "cities", "are", "Los", "Angeles", "County", "Suburban", "Metro", "Schools", "located", "?" ]
[ { "id": 4, "type": "column", "value": "school_county" }, { "id": 2, "type": "column", "value": "school_metro" }, { "id": 1, "type": "column", "value": "school_city" }, { "id": 5, "type": "value", "value": "Los Angeles" }, { "id": 0, "type": "table", "value": "projects" }, { "id": 3, "type": "value", "value": "suburban" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [ 4, 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", "O", "O", "B-VALUE", "I-VALUE", "B-COLUMN", "B-VALUE", "O", "B-COLUMN", "O", "O" ]
14,263
college_completion
bird:train.json:3683
State the name and website of the institutes from the state with 209 graduate cohort in 2011.
SELECT T1.chronname, T1.site FROM institution_details AS T1 INNER JOIN state_sector_grads AS T2 ON T1.state = T2.state WHERE T2.year = 2011 AND T2.grad_cohort = 209
[ "State", "the", "name", "and", "website", "of", "the", "institutes", "from", "the", "state", "with", "209", "graduate", "cohort", "in", "2011", "." ]
[ { "id": 2, "type": "table", "value": "institution_details" }, { "id": 3, "type": "table", "value": "state_sector_grads" }, { "id": 7, "type": "column", "value": "grad_cohort" }, { "id": 0, "type": "column", "value": "chronname" }, { "id": 4, "type": "column", "value": "state" }, { "id": 1, "type": "column", "value": "site" }, { "id": 5, "type": "column", "value": "year" }, { "id": 6, "type": "value", "value": "2011" }, { "id": 8, "type": "value", "value": "209" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
14,264
retails
bird:train.json:6807
What is the difference between the number of returned items and not returned items with the full price of under 16947.7?
SELECT SUM(IIF(l_returnflag = 'A', 1, 0)) - SUM(IIF(l_returnflag = 'N', 1, 0)) AS diff FROM lineitem WHERE l_extendedprice < 16947.7
[ "What", "is", "the", "difference", "between", "the", "number", "of", "returned", "items", "and", "not", "returned", "items", "with", "the", "full", "price", "of", "under", "16947.7", "?" ]
[ { "id": 1, "type": "column", "value": "l_extendedprice" }, { "id": 5, "type": "column", "value": "l_returnflag" }, { "id": 0, "type": "table", "value": "lineitem" }, { "id": 2, "type": "value", "value": "16947.7" }, { "id": 3, "type": "value", "value": "1" }, { "id": 4, "type": "value", "value": "0" }, { "id": 6, "type": "value", "value": "A" }, { "id": 7, "type": "value", "value": "N" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
14,265
college_2
spider:train_spider.json:1375
Given the titles of all courses, in order of titles and credits.
SELECT title FROM course ORDER BY title , credits
[ "Given", "the", "titles", "of", "all", "courses", ",", "in", "order", "of", "titles", "and", "credits", "." ]
[ { "id": 2, "type": "column", "value": "credits" }, { "id": 0, "type": "table", "value": "course" }, { "id": 1, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,266
law_episode
bird:train.json:1316
What percentage of people have worked on the True North episode as additional crew?
SELECT CAST(SUM(CASE WHEN T2.role = 'Additional Crew' THEN 1 ELSE 0 END) AS REAL ) * 100 / COUNT(T1.episode_id) FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'True North'
[ "What", "percentage", "of", "people", "have", "worked", "on", "the", "True", "North", "episode", "as", "additional", "crew", "?" ]
[ { "id": 9, "type": "value", "value": "Additional Crew" }, { "id": 3, "type": "value", "value": "True North" }, { "id": 4, "type": "column", "value": "episode_id" }, { "id": 0, "type": "table", "value": "episode" }, { "id": 1, "type": "table", "value": "credit" }, { "id": 2, "type": "column", "value": "title" }, { "id": 8, "type": "column", "value": "role" }, { "id": 5, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8, 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": [ 3 ] }, { "entity_id": 9, "token_idxs": [ 12, 13 ] }, { "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-VALUE", "I-VALUE", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
14,267
donor
bird:train.json:3225
Among the projects whose donators are teachers, what is the percentage of projects that affected more than 30 students?
SELECT CAST(SUM(CASE WHEN T1.students_reached > 30 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.projectid) FROM projects AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T2.is_teacher_acct = 't'
[ "Among", "the", "projects", "whose", "donators", "are", "teachers", ",", "what", "is", "the", "percentage", "of", "projects", "that", "affected", "more", "than", "30", "students", "?" ]
[ { "id": 8, "type": "column", "value": "students_reached" }, { "id": 2, "type": "column", "value": "is_teacher_acct" }, { "id": 1, "type": "table", "value": "donations" }, { "id": 4, "type": "column", "value": "projectid" }, { "id": 0, "type": "table", "value": "projects" }, { "id": 5, "type": "value", "value": "100" }, { "id": 9, "type": "value", "value": "30" }, { "id": 3, "type": "value", "value": "t" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
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[ "O", "O", "B-TABLE", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,268
scientist_1
spider:train_spider.json:6494
What are the names of all the scientists in alphabetical order?
SELECT name FROM scientists ORDER BY name
[ "What", "are", "the", "names", "of", "all", "the", "scientists", "in", "alphabetical", "order", "?" ]
[ { "id": 0, "type": "table", "value": "scientists" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "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", "B-TABLE", "O", "O", "O", "O" ]
14,269
book_1
bird:test.json:573
What are sale prices of books written by Plato?
SELECT saleprice FROM Book AS T1 JOIN Author_book AS T2 ON T1.isbn = T2.isbn JOIN Author AS T3 ON T2.Author = T3.idAuthor WHERE T3.name = "Plato"
[ "What", "are", "sale", "prices", "of", "books", "written", "by", "Plato", "?" ]
[ { "id": 5, "type": "table", "value": "author_book" }, { "id": 0, "type": "column", "value": "saleprice" }, { "id": 7, "type": "column", "value": "idauthor" }, { "id": 1, "type": "table", "value": "author" }, { "id": 6, "type": "column", "value": "author" }, { "id": 3, "type": "column", "value": "Plato" }, { "id": 2, "type": "column", "value": "name" }, { "id": 4, "type": "table", "value": "book" }, { "id": 8, "type": "column", "value": "isbn" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "B-COLUMN", "O" ]
14,270
card_games
bird:dev.json:424
What proportion of cards do not have a text box with a normal layout?
SELECT CAST(SUM(CASE WHEN isTextless = 1 AND layout = 'normal' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM cards
[ "What", "proportion", "of", "cards", "do", "not", "have", "a", "text", "box", "with", "a", "normal", "layout", "?" ]
[ { "id": 4, "type": "column", "value": "istextless" }, { "id": 5, "type": "column", "value": "layout" }, { "id": 6, "type": "value", "value": "normal" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 1, "type": "value", "value": "100" }, { "id": 2, "type": "value", "value": "0" }, { "id": 3, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,271
language_corpus
bird:train.json:5752
What is the percentage of the words that have been repeated under 180 times in the Catalan language?
SELECT CAST(COUNT(CASE WHEN T2.occurrences < 180 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.lid) FROM langs AS T1 INNER JOIN langs_words AS T2 ON T1.lid = T2.lid WHERE T1.lang = 'ca'
[ "What", "is", "the", "percentage", "of", "the", "words", "that", "have", "been", "repeated", "under", "180", "times", "in", "the", "Catalan", "language", "?" ]
[ { "id": 1, "type": "table", "value": "langs_words" }, { "id": 7, "type": "column", "value": "occurrences" }, { "id": 0, "type": "table", "value": "langs" }, { "id": 2, "type": "column", "value": "lang" }, { "id": 4, "type": "column", "value": "lid" }, { "id": 5, "type": "value", "value": "100" }, { "id": 8, "type": "value", "value": "180" }, { "id": 3, "type": "value", "value": "ca" }, { "id": 6, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 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": [ 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", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,272
thrombosis_prediction
bird:dev.json:1189
What number of patients with a degree of thrombosis level 2 and ANA pattern of only S, have a level of anti-Cardiolip in antibody (IgM) 20% higher than average?
SELECT COUNT(*) FROM Examination WHERE Thrombosis = 2 AND `ANA Pattern` = 'S' AND `aCL IgM` > (SELECT AVG(`aCL IgM`) * 1.2 FROM Examination WHERE Thrombosis = 2 AND `ANA Pattern` = 'S')
[ "What", "number", "of", "patients", "with", "a", "degree", "of", "thrombosis", "level", "2", "and", "ANA", "pattern", "of", "only", "S", ",", "have", "a", "level", "of", "anti", "-", "Cardiolip", "in", "antibody", "(", "IgM", ")", "20", "%", "higher", "than", "average", "?" ]
[ { "id": 0, "type": "table", "value": "examination" }, { "id": 3, "type": "column", "value": "ANA Pattern" }, { "id": 1, "type": "column", "value": "thrombosis" }, { "id": 5, "type": "column", "value": "aCL IgM" }, { "id": 6, "type": "value", "value": "1.2" }, { "id": 2, "type": "value", "value": "2" }, { "id": 4, "type": "value", "value": "S" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
14,273
shop_membership
spider:train_spider.json:5431
What are the member names and hometowns of those who registered at a branch in 2016?
SELECT T2.name , T2.hometown FROM membership_register_branch AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T1.register_year = 2016
[ "What", "are", "the", "member", "names", "and", "hometowns", "of", "those", "who", "registered", "at", "a", "branch", "in", "2016", "?" ]
[ { "id": 2, "type": "table", "value": "membership_register_branch" }, { "id": 4, "type": "column", "value": "register_year" }, { "id": 6, "type": "column", "value": "member_id" }, { "id": 1, "type": "column", "value": "hometown" }, { "id": 3, "type": "table", "value": "member" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "2016" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "B-TABLE", "I-TABLE", "I-TABLE", "O", "B-VALUE", "O" ]
14,274
mental_health_survey
bird:train.json:4616
How many respondents who participated in the survey in 2019 have ever sought treatment for a mental health disorder from a mental health professional?
SELECT COUNT(T1.UserID) FROM Answer AS T1 INNER JOIN Question AS T2 ON T1.QuestionID = T2.questionid WHERE T1.QuestionID = 7 AND T1.SurveyID = 2019 AND T1.AnswerText = 1
[ "How", "many", "respondents", "who", "participated", "in", "the", "survey", "in", "2019", "have", "ever", "sought", "treatment", "for", "a", "mental", "health", "disorder", "from", "a", "mental", "health", "professional", "?" ]
[ { "id": 3, "type": "column", "value": "questionid" }, { "id": 7, "type": "column", "value": "answertext" }, { "id": 1, "type": "table", "value": "question" }, { "id": 5, "type": "column", "value": "surveyid" }, { "id": 0, "type": "table", "value": "answer" }, { "id": 2, "type": "column", "value": "userid" }, { "id": 6, "type": "value", "value": "2019" }, { "id": 4, "type": "value", "value": "7" }, { "id": 8, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,276
law_episode
bird:train.json:1300
What is the title of the 3 worst rated episodes?
SELECT title FROM Episode ORDER BY rating LIMIT 3
[ "What", "is", "the", "title", "of", "the", "3", "worst", "rated", "episodes", "?" ]
[ { "id": 0, "type": "table", "value": "episode" }, { "id": 2, "type": "column", "value": "rating" }, { "id": 1, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "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", "O", "O", "B-TABLE", "O" ]
14,277
club_1
spider:train_spider.json:4260
Who are the members of the club named "Hopkins Student Enterprises"? Show the last name.
SELECT t3.lname 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 t1.clubname = "Hopkins Student Enterprises"
[ "Who", "are", "the", "members", "of", "the", "club", "named", "\"", "Hopkins", "Student", "Enterprises", "\"", "?", "Show", "the", "last", "name", "." ]
[ { "id": 3, "type": "column", "value": "Hopkins Student Enterprises" }, { "id": 5, "type": "table", "value": "member_of_club" }, { "id": 2, "type": "column", "value": "clubname" }, { "id": 1, "type": "table", "value": "student" }, { "id": 7, "type": "column", "value": "clubid" }, { "id": 0, "type": "column", "value": "lname" }, { "id": 6, "type": "column", "value": "stuid" }, { "id": 4, "type": "table", "value": "club" } ]
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[ "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,278
institution_sports
bird:test.json:1649
What are the maximum and minimum enrollment of all institutions?
SELECT max(Enrollment) , min(Enrollment) FROM institution
[ "What", "are", "the", "maximum", "and", "minimum", "enrollment", "of", "all", "institutions", "?" ]
[ { "id": 0, "type": "table", "value": "institution" }, { "id": 1, "type": "column", "value": "enrollment" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
14,279
storm_record
spider:train_spider.json:2711
What are the names of regions that were not affected?
SELECT region_name FROM region WHERE region_id NOT IN (SELECT region_id FROM affected_region)
[ "What", "are", "the", "names", "of", "regions", "that", "were", "not", "affected", "?" ]
[ { "id": 3, "type": "table", "value": "affected_region" }, { "id": 1, "type": "column", "value": "region_name" }, { "id": 2, "type": "column", "value": "region_id" }, { "id": 0, "type": "table", "value": "region" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
14,280
card_games
bird:dev.json:472
Among the sets in the block "Ice Age", how many of them have an Italian translation?
SELECT COUNT(DISTINCT T1.id) FROM sets AS T1 INNER JOIN set_translations AS T2 ON T2.setCode = T1.code WHERE T1.block = 'Ice Age' AND T2.language = 'Italian' AND T2.translation IS NOT NULL
[ "Among", "the", "sets", "in", "the", "block", "\"", "Ice", "Age", "\"", ",", "how", "many", "of", "them", "have", "an", "Italian", "translation", "?" ]
[ { "id": 1, "type": "table", "value": "set_translations" }, { "id": 9, "type": "column", "value": "translation" }, { "id": 7, "type": "column", "value": "language" }, { "id": 3, "type": "column", "value": "setcode" }, { "id": 6, "type": "value", "value": "Ice Age" }, { "id": 8, "type": "value", "value": "Italian" }, { "id": 5, "type": "column", "value": "block" }, { "id": 0, "type": "table", "value": "sets" }, { "id": 4, "type": "column", "value": "code" }, { "id": 2, "type": "column", "value": "id" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,281
menu
bird:train.json:5495
List the names and menu page IDs of the dishes that first appeared in 1861.
SELECT T2.name, T1.dish_id FROM MenuItem AS T1 INNER JOIN Dish AS T2 ON T2.id = T1.dish_id WHERE T2.first_appeared = 1861
[ "List", "the", "names", "and", "menu", "page", "IDs", "of", "the", "dishes", "that", "first", "appeared", "in", "1861", "." ]
[ { "id": 4, "type": "column", "value": "first_appeared" }, { "id": 2, "type": "table", "value": "menuitem" }, { "id": 1, "type": "column", "value": "dish_id" }, { "id": 0, "type": "column", "value": "name" }, { "id": 3, "type": "table", "value": "dish" }, { "id": 5, "type": "value", "value": "1861" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
14,282
financial
bird:dev.json:172
How many owner and disponent dispositions are there from account number 1 to account number 10?
SELECT SUM(type = 'OWNER') , SUM(type = 'DISPONENT') FROM disp WHERE account_id BETWEEN 1 AND 10
[ "How", "many", "owner", "and", "disponent", "dispositions", "are", "there", "from", "account", "number", "1", "to", "account", "number", "10", "?" ]
[ { "id": 1, "type": "column", "value": "account_id" }, { "id": 6, "type": "value", "value": "DISPONENT" }, { "id": 5, "type": "value", "value": "OWNER" }, { "id": 0, "type": "table", "value": "disp" }, { "id": 4, "type": "column", "value": "type" }, { "id": 3, "type": "value", "value": "10" }, { "id": 2, "type": "value", "value": "1" } ]
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[ "O", "O", "B-VALUE", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
14,283
soccer_2016
bird:train.json:1798
What is the bowling skill used by most players?
SELECT T1.Bowling_Skill FROM Bowling_Style AS T1 INNER JOIN Player AS T2 ON T2.Bowling_skill = T1.Bowling_Id GROUP BY T1.Bowling_Skill ORDER BY COUNT(T1.Bowling_Skill) DESC LIMIT 1
[ "What", "is", "the", "bowling", "skill", "used", "by", "most", "players", "?" ]
[ { "id": 0, "type": "column", "value": "bowling_skill" }, { "id": 1, "type": "table", "value": "bowling_style" }, { "id": 3, "type": "column", "value": "bowling_id" }, { "id": 2, "type": "table", "value": "player" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
14,284
election_representative
spider:train_spider.json:1187
What are the different parties of representative? Show the party name and the number of representatives in each party.
SELECT Party , COUNT(*) FROM representative GROUP BY Party
[ "What", "are", "the", "different", "parties", "of", "representative", "?", "Show", "the", "party", "name", "and", "the", "number", "of", "representatives", "in", "each", "party", "." ]
[ { "id": 0, "type": "table", "value": "representative" }, { "id": 1, "type": "column", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,285
toxicology
bird:dev.json:239
How many connections does the atom 19 have?
SELECT COUNT(T.bond_id) FROM connected AS T WHERE SUBSTR(T.atom_id, -2) = '19'
[ "How", "many", "connections", "does", "the", "atom", "19", "have", "?" ]
[ { "id": 0, "type": "table", "value": "connected" }, { "id": 2, "type": "column", "value": "bond_id" }, { "id": 3, "type": "column", "value": "atom_id" }, { "id": 1, "type": "value", "value": "19" }, { "id": 4, "type": "value", "value": "-2" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-VALUE", "O", "O" ]
14,286
retail_world
bird:train.json:6441
Which product is the most expensive?
SELECT ProductName FROM Products WHERE UnitPrice = ( SELECT MAX(UnitPrice) FROM Products )
[ "Which", "product", "is", "the", "most", "expensive", "?" ]
[ { "id": 1, "type": "column", "value": "productname" }, { "id": 2, "type": "column", "value": "unitprice" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "O", "O" ]
14,287
chicago_crime
bird:train.json:8636
What is the legislative district's office address where 010XX W LAKE ST is located?
SELECT T1.ward_office_address FROM Ward AS T1 INNER JOIN Crime AS T2 ON T1.ward_no = T2.ward_no WHERE T2.block = '010XX W LAKE ST' GROUP BY T1.ward_office_address
[ "What", "is", "the", "legislative", "district", "'s", "office", "address", "where", "010XX", "W", "LAKE", "ST", "is", "located", "?" ]
[ { "id": 0, "type": "column", "value": "ward_office_address" }, { "id": 4, "type": "value", "value": "010XX W LAKE ST" }, { "id": 5, "type": "column", "value": "ward_no" }, { "id": 2, "type": "table", "value": "crime" }, { "id": 3, "type": "column", "value": "block" }, { "id": 1, "type": "table", "value": "ward" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O" ]
14,288
college_3
spider:train_spider.json:4638
Count the number of courses with more than 2 credits.
SELECT count(*) FROM COURSE WHERE Credits > 2
[ "Count", "the", "number", "of", "courses", "with", "more", "than", "2", "credits", "." ]
[ { "id": 1, "type": "column", "value": "credits" }, { "id": 0, "type": "table", "value": "course" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
14,290
works_cycles
bird:train.json:7052
Please list the job titles of the employees who has a document that has been approved.
SELECT DISTINCT T2.BusinessEntityID, T2.JobTitle FROM Document AS T1 INNER JOIN Employee AS T2 ON T1.Owner = T2.BusinessEntityID WHERE T1.Status = 2
[ "Please", "list", "the", "job", "titles", "of", "the", "employees", "who", "has", "a", "document", "that", "has", "been", "approved", "." ]
[ { "id": 0, "type": "column", "value": "businessentityid" }, { "id": 1, "type": "column", "value": "jobtitle" }, { "id": 2, "type": "table", "value": "document" }, { "id": 3, "type": "table", "value": "employee" }, { "id": 4, "type": "column", "value": "status" }, { "id": 6, "type": "column", "value": "owner" }, { "id": 5, "type": "value", "value": "2" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O" ]
14,291
soccer_2
spider:train_spider.json:4983
What are the different names of the colleges involved in the tryout in alphabetical order?
SELECT DISTINCT cName FROM tryout ORDER BY cName
[ "What", "are", "the", "different", "names", "of", "the", "colleges", "involved", "in", "the", "tryout", "in", "alphabetical", "order", "?" ]
[ { "id": 0, "type": "table", "value": "tryout" }, { "id": 1, "type": "column", "value": "cname" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "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", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
14,292
flight_1
spider:train_spider.json:409
Which destination has least number of flights?
SELECT destination FROM Flight GROUP BY destination ORDER BY count(*) LIMIT 1
[ "Which", "destination", "has", "least", "number", "of", "flights", "?" ]
[ { "id": 1, "type": "column", "value": "destination" }, { "id": 0, "type": "table", "value": "flight" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
14,294
law_episode
bird:train.json:1286
Who is the narrator of the "Flight" episode?
SELECT T3.name FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T1.title = 'Flight' AND T2.role = 'Narrator'
[ "Who", "is", "the", "narrator", "of", "the", "\"", "Flight", "\"", "episode", "?" ]
[ { "id": 9, "type": "column", "value": "episode_id" }, { "id": 4, "type": "column", "value": "person_id" }, { "id": 8, "type": "value", "value": "Narrator" }, { "id": 2, "type": "table", "value": "episode" }, { "id": 1, "type": "table", "value": "person" }, { "id": 3, "type": "table", "value": "credit" }, { "id": 6, "type": "value", "value": "Flight" }, { "id": 5, "type": "column", "value": "title" }, { "id": 0, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "role" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 7 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 3 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O", "B-TABLE", "O" ]
14,295
world_development_indicators
bird:train.json:2137
From 1960 to 1965, which country had the highest Death rate, crude (per 1,000 people)?
SELECT CountryName FROM Indicators WHERE Year BETWEEN 1960 AND 1965 AND IndicatorName = 'Death rate, crude (per 1,000 people)' ORDER BY Value DESC LIMIT 1
[ "From", "1960", "to", "1965", ",", "which", "country", "had", "the", "highest", "Death", "rate", ",", "crude", "(", "per", "1,000", "people", ")", "?" ]
[ { "id": 7, "type": "value", "value": "Death rate, crude (per 1,000 people)" }, { "id": 6, "type": "column", "value": "indicatorname" }, { "id": 1, "type": "column", "value": "countryname" }, { "id": 0, "type": "table", "value": "indicators" }, { "id": 2, "type": "column", "value": "value" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "1960" }, { "id": 5, "type": "value", "value": "1965" } ]
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[ "O", "B-VALUE", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,296
student_club
bird:dev.json:1400
Among all events hold by the Student_Club in 2019, find the percentage share of events related to 'Community Service'
SELECT CAST(SUM(CASE WHEN type = 'Community Service' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(type) FROM event WHERE SUBSTR(event_date, 1, 4) = '2019'
[ "Among", "all", "events", "hold", "by", "the", "Student_Club", "in", "2019", ",", "find", "the", "percentage", "share", "of", "events", "related", "to", "'", "Community", "Service", "'" ]
[ { "id": 8, "type": "value", "value": "Community Service" }, { "id": 2, "type": "column", "value": "event_date" }, { "id": 0, "type": "table", "value": "event" }, { "id": 1, "type": "value", "value": "2019" }, { "id": 6, "type": "column", "value": "type" }, { "id": 5, "type": "value", "value": "100" }, { "id": 3, "type": "value", "value": "1" }, { "id": 4, "type": "value", "value": "4" }, { "id": 7, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O" ]
14,297
apartment_rentals
spider:train_spider.json:1246
Show the apartment type codes and apartment numbers in the buildings managed by "Kyle".
SELECT T2.apt_type_code , T2.apt_number FROM Apartment_Buildings AS T1 JOIN Apartments AS T2 ON T1.building_id = T2.building_id WHERE T1.building_manager = "Kyle"
[ "Show", "the", "apartment", "type", "codes", "and", "apartment", "numbers", "in", "the", "buildings", "managed", "by", "\"", "Kyle", "\"", "." ]
[ { "id": 2, "type": "table", "value": "apartment_buildings" }, { "id": 4, "type": "column", "value": "building_manager" }, { "id": 0, "type": "column", "value": "apt_type_code" }, { "id": 6, "type": "column", "value": "building_id" }, { "id": 1, "type": "column", "value": "apt_number" }, { "id": 3, "type": "table", "value": "apartments" }, { "id": 5, "type": "column", "value": "Kyle" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
14,298
college_2
spider:train_spider.json:1327
Give the name and building of the departments with greater than average budget.
SELECT dept_name , building FROM department WHERE budget > (SELECT avg(budget) FROM department)
[ "Give", "the", "name", "and", "building", "of", "the", "departments", "with", "greater", "than", "average", "budget", "." ]
[ { "id": 0, "type": "table", "value": "department" }, { "id": 1, "type": "column", "value": "dept_name" }, { "id": 2, "type": "column", "value": "building" }, { "id": 3, "type": "column", "value": "budget" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
14,299
card_games
bird:dev.json:445
What is the language and flavor text of the card that has colorpie watermark? List out the type of this card.
SELECT DISTINCT T2.language, T2.flavorText FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T2.uuid = T1.uuid WHERE T1.watermark = 'colorpie'
[ "What", "is", "the", "language", "and", "flavor", "text", "of", "the", "card", "that", "has", "colorpie", "watermark", "?", "List", "out", "the", "type", "of", "this", "card", "." ]
[ { "id": 3, "type": "table", "value": "foreign_data" }, { "id": 1, "type": "column", "value": "flavortext" }, { "id": 4, "type": "column", "value": "watermark" }, { "id": 0, "type": "column", "value": "language" }, { "id": 5, "type": "value", "value": "colorpie" }, { "id": 2, "type": "table", "value": "cards" }, { "id": 6, "type": "column", "value": "uuid" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5, 6 ] }, { "entity_id": 2, "token_idxs": [ 21 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 13 ] }, { "entity_id": 5, "token_idxs": [ 12 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,300
products_gen_characteristics
spider:train_spider.json:5527
What are the different names of the product characteristics?
SELECT DISTINCT characteristic_name FROM CHARACTERISTICS
[ "What", "are", "the", "different", "names", "of", "the", "product", "characteristics", "?" ]
[ { "id": 1, "type": "column", "value": "characteristic_name" }, { "id": 0, "type": "table", "value": "characteristics" } ]
[ { "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" ]
14,301
movie_1
spider:train_spider.json:2505
For each reviewer id, what is the title and rating for the movie with the smallest rating?
SELECT T2.title , T1.rID , T1.stars , min(T1.stars) FROM Rating AS T1 JOIN Movie AS T2 ON T1.mID = T2.mID GROUP BY T1.rID
[ "For", "each", "reviewer", "i", "d", ",", "what", "is", "the", "title", "and", "rating", "for", "the", "movie", "with", "the", "smallest", "rating", "?" ]
[ { "id": 3, "type": "table", "value": "rating" }, { "id": 1, "type": "column", "value": "title" }, { "id": 2, "type": "column", "value": "stars" }, { "id": 4, "type": "table", "value": "movie" }, { "id": 0, "type": "column", "value": "rid" }, { "id": 5, "type": "column", "value": "mid" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 18 ] }, { "entity_id": 4, "token_idxs": [ 14 ] }, { "entity_id": 5, "token_idxs": [ 3, 4 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
14,302
retails
bird:train.json:6894
What is the profit for part no.98768 in order no.1?
SELECT T1.l_extendedprice * (1 - T1.l_discount) - T2.ps_supplycost * T1.l_quantity FROM lineitem AS T1 INNER JOIN partsupp AS T2 ON T1.l_suppkey = T2.ps_suppkey WHERE T1.l_orderkey = 1 AND T1.l_partkey = 98768
[ "What", "is", "the", "profit", "for", "part", "no.98768", "in", "order", "no.1", "?" ]
[ { "id": 8, "type": "column", "value": "l_extendedprice" }, { "id": 9, "type": "column", "value": "ps_supplycost" }, { "id": 3, "type": "column", "value": "ps_suppkey" }, { "id": 4, "type": "column", "value": "l_orderkey" }, { "id": 10, "type": "column", "value": "l_quantity" }, { "id": 11, "type": "column", "value": "l_discount" }, { "id": 2, "type": "column", "value": "l_suppkey" }, { "id": 6, "type": "column", "value": "l_partkey" }, { "id": 0, "type": "table", "value": "lineitem" }, { "id": 1, "type": "table", "value": "partsupp" }, { "id": 7, "type": "value", "value": "98768" }, { "id": 5, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-VALUE", "O", "B-COLUMN", "O", "O" ]
14,303
card_games
bird:dev.json:456
What's the list of all types for the card "Molimo, Maro-Sorcerer"?
SELECT DISTINCT subtypes, supertypes FROM cards WHERE name = 'Molimo, Maro-Sorcerer'
[ "What", "'s", "the", "list", "of", "all", "types", "for", "the", "card", "\"", "Molimo", ",", "Maro", "-", "Sorcerer", "\"", "?" ]
[ { "id": 4, "type": "value", "value": "Molimo, Maro-Sorcerer" }, { "id": 2, "type": "column", "value": "supertypes" }, { "id": 1, "type": "column", "value": "subtypes" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 3, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 11, 12, 13, 14, 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
14,304
authors
bird:train.json:3610
How many papers are published under the conference "Mathematics of Program Construction "?
SELECT COUNT(T1.Id) FROM Paper AS T1 INNER JOIN Conference AS T2 ON T1.ConferenceId = T2.Id WHERE T2.FullName = 'Mathematics of Program Construction'
[ "How", "many", "papers", "are", "published", "under", "the", "conference", "\"", "Mathematics", "of", "Program", "Construction", "\n", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "Mathematics of Program Construction" }, { "id": 5, "type": "column", "value": "conferenceid" }, { "id": 1, "type": "table", "value": "conference" }, { "id": 2, "type": "column", "value": "fullname" }, { "id": 0, "type": "table", "value": "paper" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10, 11, 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O" ]
14,305
works_cycles
bird:train.json:7151
Name cellphone number's Type ID?
SELECT PhoneNumberTypeID FROM PhoneNumberType WHERE Name = 'Cell'
[ "Name", "cellphone", "number", "'s", "Type", "ID", "?" ]
[ { "id": 1, "type": "column", "value": "phonenumbertypeid" }, { "id": 0, "type": "table", "value": "phonenumbertype" }, { "id": 2, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "Cell" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 0 ] }, { "entity_id": 3, "token_idxs": [ 1 ] }, { "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": [] } ]
[ "B-COLUMN", "B-VALUE", "B-TABLE", "I-TABLE", "I-TABLE", "B-COLUMN", "O" ]
14,306
cre_Docs_and_Epenses
spider:train_spider.json:6385
How many accounts do we have?
SELECT count(*) FROM Accounts
[ "How", "many", "accounts", "do", "we", "have", "?" ]
[ { "id": 0, "type": "table", "value": "accounts" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O" ]
14,307
books
bird:train.json:6012
How many customers use a Yahoo! Mail e-mail address?
SELECT COUNT(*) FROM customer WHERE email LIKE '%@yahoo.com'
[ "How", "many", "customers", "use", "a", "Yahoo", "!", "Mail", "e", "-", "mail", "address", "?" ]
[ { "id": 2, "type": "value", "value": "%@yahoo.com" }, { "id": 0, "type": "table", "value": "customer" }, { "id": 1, "type": "column", "value": "email" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 8, 9, 10 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
14,308
party_host
spider:train_spider.json:2683
Which parties have hosts of age above 50? Give me the party locations.
SELECT T3.Location FROM party_host AS T1 JOIN HOST AS T2 ON T1.Host_ID = T2.Host_ID JOIN party AS T3 ON T1.Party_ID = T3.Party_ID WHERE T2.Age > 50
[ "Which", "parties", "have", "hosts", "of", "age", "above", "50", "?", "Give", "me", "the", "party", "locations", "." ]
[ { "id": 4, "type": "table", "value": "party_host" }, { "id": 0, "type": "column", "value": "location" }, { "id": 6, "type": "column", "value": "party_id" }, { "id": 7, "type": "column", "value": "host_id" }, { "id": 1, "type": "table", "value": "party" }, { "id": 5, "type": "table", "value": "host" }, { "id": 2, "type": "column", "value": "age" }, { "id": 3, "type": "value", "value": "50" } ]
[ { "entity_id": 0, "token_idxs": [ 13 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
14,309
assets_maintenance
spider:train_spider.json:3151
Which part has the least chargeable amount? List the part id and amount.
SELECT part_id , chargeable_amount FROM Parts ORDER BY chargeable_amount ASC LIMIT 1
[ "Which", "part", "has", "the", "least", "chargeable", "amount", "?", "List", "the", "part", "i", "d", "and", "amount", "." ]
[ { "id": 2, "type": "column", "value": "chargeable_amount" }, { "id": 1, "type": "column", "value": "part_id" }, { "id": 0, "type": "table", "value": "parts" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 10, 11, 12 ] }, { "entity_id": 2, "token_idxs": [ 5, 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O" ]
14,310
legislator
bird:train.json:4882
Who is the Lutheran representative that served in the state of Ohio for 14 years before becoming a senator?
SELECT CASE WHEN SUM(CAST(strftime('%Y', T2.end) AS int) - CAST(strftime('%Y', T2.start) AS int)) = 14 THEN official_full_name END FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.religion_bio = 'Lutheran' AND T2.state = 'OH' AND T2.type = 'rep'
[ "Who", "is", "the", "Lutheran", "representative", "that", "served", "in", "the", "state", "of", "Ohio", "for", "14", "years", "before", "becoming", "a", "senator", "?" ]
[ { "id": 10, "type": "column", "value": "official_full_name" }, { "id": 1, "type": "table", "value": "current-terms" }, { "id": 4, "type": "column", "value": "religion_bio" }, { "id": 2, "type": "column", "value": "bioguide_id" }, { "id": 3, "type": "column", "value": "bioguide" }, { "id": 5, "type": "value", "value": "Lutheran" }, { "id": 0, "type": "table", "value": "current" }, { "id": 6, "type": "column", "value": "state" }, { "id": 14, "type": "column", "value": "start" }, { "id": 8, "type": "column", "value": "type" }, { "id": 9, "type": "value", "value": "rep" }, { "id": 13, "type": "column", "value": "end" }, { "id": 7, "type": "value", "value": "OH" }, { "id": 11, "type": "value", "value": "14" }, { "id": 12, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 11 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [ 13 ] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [ 9 ] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O" ]
14,311
products_gen_characteristics
spider:train_spider.json:5562
List all characteristics of product named "sesame" with type code "Grade".
SELECT t3.characteristic_name FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN CHARACTERISTICS AS t3 ON t2.characteristic_id = t3.characteristic_id WHERE t1.product_name = "sesame" AND t3.characteristic_type_code = "Grade"
[ "List", "all", "characteristics", "of", "product", "named", "\"", "sesame", "\"", "with", "type", "code", "\"", "Grade", "\"", "." ]
[ { "id": 7, "type": "column", "value": "characteristic_type_code" }, { "id": 3, "type": "table", "value": "product_characteristics" }, { "id": 0, "type": "column", "value": "characteristic_name" }, { "id": 4, "type": "column", "value": "characteristic_id" }, { "id": 1, "type": "table", "value": "characteristics" }, { "id": 5, "type": "column", "value": "product_name" }, { "id": 9, "type": "column", "value": "product_id" }, { "id": 2, "type": "table", "value": "products" }, { "id": 6, "type": "column", "value": "sesame" }, { "id": 8, "type": "column", "value": "Grade" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [ 7 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 13 ] }, { "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-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
14,312
cre_Doc_Control_Systems
spider:train_spider.json:2114
List the document ids for any documents with the status code done and the type code paper.
SELECT document_id FROM Documents WHERE document_status_code = "done" AND document_type_code = "Paper";
[ "List", "the", "document", "ids", "for", "any", "documents", "with", "the", "status", "code", "done", "and", "the", "type", "code", "paper", "." ]
[ { "id": 2, "type": "column", "value": "document_status_code" }, { "id": 4, "type": "column", "value": "document_type_code" }, { "id": 1, "type": "column", "value": "document_id" }, { "id": 0, "type": "table", "value": "documents" }, { "id": 5, "type": "column", "value": "Paper" }, { "id": 3, "type": "column", "value": "done" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [ 7, 8, 9, 10 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 12, 13, 14, 15 ] }, { "entity_id": 5, "token_idxs": [ 16 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "O" ]
14,313
theme_gallery
spider:train_spider.json:1649
How many artists do we have?
SELECT count(*) FROM artist
[ "How", "many", "artists", "do", "we", "have", "?" ]
[ { "id": 0, "type": "table", "value": "artist" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O" ]
14,314
match_season
spider:train_spider.json:1084
Show the positions of the players from the team with name "Ryley Goldner".
SELECT T1.Position FROM match_season AS T1 JOIN team AS T2 ON T1.Team = T2.Team_id WHERE T2.Name = "Ryley Goldner"
[ "Show", "the", "positions", "of", "the", "players", "from", "the", "team", "with", "name", "\"", "Ryley", "Goldner", "\"", "." ]
[ { "id": 4, "type": "column", "value": "Ryley Goldner" }, { "id": 1, "type": "table", "value": "match_season" }, { "id": 0, "type": "column", "value": "position" }, { "id": 6, "type": "column", "value": "team_id" }, { "id": 2, "type": "table", "value": "team" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "team" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [ 12, 13 ] }, { "entity_id": 5, "token_idxs": [ 8 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
14,315
citeseer
bird:train.json:4146
List all the paper ID and its class type that cited the word 'word1002'.
SELECT T1.paper_id, T1.class_label FROM paper AS T1 INNER JOIN content AS T2 ON T1.paper_id = T2.paper_id WHERE T2.word_cited_id = 'word1002'
[ "List", "all", "the", "paper", "ID", "and", "its", "class", "type", "that", "cited", "the", "word", "'", "word1002", "'", "." ]
[ { "id": 4, "type": "column", "value": "word_cited_id" }, { "id": 1, "type": "column", "value": "class_label" }, { "id": 0, "type": "column", "value": "paper_id" }, { "id": 5, "type": "value", "value": "word1002" }, { "id": 3, "type": "table", "value": "content" }, { "id": 2, "type": "table", "value": "paper" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
14,316
cookbook
bird:train.json:8906
List the ingredients in Tomato-Cucumber Relish.
SELECT T3.name FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id WHERE T1.title = 'Tomato-Cucumber Relish'
[ "List", "the", "ingredients", "in", "Tomato", "-", "Cucumber", "Relish", "." ]
[ { "id": 3, "type": "value", "value": "Tomato-Cucumber Relish" }, { "id": 6, "type": "column", "value": "ingredient_id" }, { "id": 1, "type": "table", "value": "ingredient" }, { "id": 7, "type": "column", "value": "recipe_id" }, { "id": 5, "type": "table", "value": "quantity" }, { "id": 4, "type": "table", "value": "recipe" }, { "id": 2, "type": "column", "value": "title" }, { "id": 0, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4, 5, 6, 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O" ]
14,317
retail_world
bird:train.json:6542
List the full name of employees and titles who have to report to Sales Manager.
SELECT FirstName, LastName, Title FROM Employees WHERE ReportsTo = ( SELECT EmployeeID FROM Employees WHERE Title = 'Sales Manager' )
[ "List", "the", "full", "name", "of", "employees", "and", "titles", "who", "have", "to", "report", "to", "Sales", "Manager", "." ]
[ { "id": 6, "type": "value", "value": "Sales Manager" }, { "id": 5, "type": "column", "value": "employeeid" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 1, "type": "column", "value": "firstname" }, { "id": 4, "type": "column", "value": "reportsto" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 3, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 11, 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 13, 14 ] }, { "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", "B-COLUMN", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "I-VALUE", "O" ]
14,318
student_loan
bird:train.json:4431
List out the number of female students who enlisted in the air force.
SELECT COUNT(name) FROM enlist WHERE organ = 'air_force' AND name NOT IN ( SELECT name FROM male )
[ "List", "out", "the", "number", "of", "female", "students", "who", "enlisted", "in", "the", "air", "force", "." ]
[ { "id": 3, "type": "value", "value": "air_force" }, { "id": 0, "type": "table", "value": "enlist" }, { "id": 2, "type": "column", "value": "organ" }, { "id": 1, "type": "column", "value": "name" }, { "id": 4, "type": "table", "value": "male" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 11, 12 ] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "O" ]
14,319
cre_Doc_and_collections
bird:test.json:668
What are the details on the document subsets that are named 'Best for 2000'?
SELECT Document_Subset_Details FROM Document_Subsets WHERE Document_Subset_Name = "Best for 2000";
[ "What", "are", "the", "details", "on", "the", "document", "subsets", "that", "are", "named", "'", "Best", "for", "2000", "'", "?" ]
[ { "id": 1, "type": "column", "value": "document_subset_details" }, { "id": 2, "type": "column", "value": "document_subset_name" }, { "id": 0, "type": "table", "value": "document_subsets" }, { "id": 3, "type": "column", "value": "Best for 2000" } ]
[ { "entity_id": 0, "token_idxs": [ 6, 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12, 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", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O" ]
14,320
retail_complains
bird:train.json:406
List the product and its issues of the complains of clients with age greater than the 60% of average age of all clients.
SELECT DISTINCT T2.Product, T2.Issue FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.age * 100 > ( SELECT AVG(age) * 60 FROM client )
[ "List", "the", "product", "and", "its", "issues", "of", "the", "complains", "of", "clients", "with", "age", "greater", "than", "the", "60", "%", "of", "average", "age", "of", "all", "clients", "." ]
[ { "id": 4, "type": "column", "value": "client_id" }, { "id": 0, "type": "column", "value": "product" }, { "id": 2, "type": "table", "value": "client" }, { "id": 3, "type": "table", "value": "events" }, { "id": 1, "type": "column", "value": "issue" }, { "id": 5, "type": "column", "value": "age" }, { "id": 6, "type": "value", "value": "100" }, { "id": 7, "type": "value", "value": "60" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 23 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 12 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 16 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
14,321
cre_Students_Information_Systems
bird:test.json:480
Which students have 'Suite' as a substring in their details? Give me their biographical information.
SELECT bio_data FROM Students WHERE student_details LIKE '%Suite%'
[ "Which", "students", "have", "'", "Suite", "'", "as", "a", "substring", "in", "their", "details", "?", "Give", "me", "their", "biographical", "information", "." ]
[ { "id": 2, "type": "column", "value": "student_details" }, { "id": 0, "type": "table", "value": "students" }, { "id": 1, "type": "column", "value": "bio_data" }, { "id": 3, "type": "value", "value": "%Suite%" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,322
formula_1
spider:train_spider.json:2216
What are the ids and locations of all circuits in France or Belgium?
SELECT circuitid , LOCATION FROM circuits WHERE country = "France" OR country = "Belgium"
[ "What", "are", "the", "ids", "and", "locations", "of", "all", "circuits", "in", "France", "or", "Belgium", "?" ]
[ { "id": 1, "type": "column", "value": "circuitid" }, { "id": 0, "type": "table", "value": "circuits" }, { "id": 2, "type": "column", "value": "location" }, { "id": 3, "type": "column", "value": "country" }, { "id": 5, "type": "column", "value": "Belgium" }, { "id": 4, "type": "column", "value": "France" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
14,323
music_2
spider:train_spider.json:5211
What are the instruments are used in the song "Le Pop"?
SELECT instrument FROM instruments AS T1 JOIN songs AS T2 ON T1.songid = T2.songid WHERE title = "Le Pop"
[ "What", "are", "the", "instruments", "are", "used", "in", "the", "song", "\"", "Le", "Pop", "\"", "?" ]
[ { "id": 1, "type": "table", "value": "instruments" }, { "id": 0, "type": "column", "value": "instrument" }, { "id": 4, "type": "column", "value": "Le Pop" }, { "id": 5, "type": "column", "value": "songid" }, { "id": 2, "type": "table", "value": "songs" }, { "id": 3, "type": "column", "value": "title" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
14,324
mondial_geo
bird:train.json:8234
Calculate the service of GDP for Brazil.
SELECT T2.Service * T2.GDP FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country WHERE T1.Name = 'Brazil'
[ "Calculate", "the", "service", "of", "GDP", "for", "Brazil", "." ]
[ { "id": 0, "type": "table", "value": "country" }, { "id": 1, "type": "table", "value": "economy" }, { "id": 4, "type": "column", "value": "service" }, { "id": 7, "type": "column", "value": "country" }, { "id": 3, "type": "value", "value": "Brazil" }, { "id": 2, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "code" }, { "id": 5, "type": "column", "value": "gdp" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
14,325
student_assessment
spider:train_spider.json:60
what are the first name and last name of all candidates?
SELECT T2.first_name , T2.last_name FROM candidates AS T1 JOIN people AS T2 ON T1.candidate_id = T2.person_id
[ "what", "are", "the", "first", "name", "and", "last", "name", "of", "all", "candidates", "?" ]
[ { "id": 4, "type": "column", "value": "candidate_id" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 2, "type": "table", "value": "candidates" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 5, "type": "column", "value": "person_id" }, { "id": 3, "type": "table", "value": "people" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O" ]
14,326
behavior_monitoring
spider:train_spider.json:3089
How many distinct incident type codes are there?
SELECT count(DISTINCT incident_type_code) FROM Behavior_Incident
[ "How", "many", "distinct", "incident", "type", "codes", "are", "there", "?" ]
[ { "id": 1, "type": "column", "value": "incident_type_code" }, { "id": 0, "type": "table", "value": "behavior_incident" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O" ]
14,328
store_1
spider:train_spider.json:594
What is the full name of the employee who has the most customers?
SELECT T1.first_name , T1.last_name FROM employees AS T1 JOIN customers AS T2 ON T1.id = T2.support_rep_id GROUP BY T1.id ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "full", "name", "of", "the", "employee", "who", "has", "the", "most", "customers", "?" ]
[ { "id": 5, "type": "column", "value": "support_rep_id" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 3, "type": "table", "value": "employees" }, { "id": 4, "type": "table", "value": "customers" }, { "id": 0, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O" ]
14,329
tracking_software_problems
spider:train_spider.json:5391
Find the ids of the problems reported after the date of any problems reported by the staff Rylan Homenick.
SELECT T1.problem_id FROM problems AS T1 JOIN staff AS T2 ON T1.reported_by_staff_id = T2.staff_id WHERE date_problem_reported > ( SELECT max(date_problem_reported) FROM problems AS T3 JOIN staff AS T4 ON T3.reported_by_staff_id = T4.staff_id WHERE T4.staff_first_name = "Rylan" AND T4.staff_last_name = "Homenick" )
[ "Find", "the", "ids", "of", "the", "problems", "reported", "after", "the", "date", "of", "any", "problems", "reported", "by", "the", "staff", "Rylan", "Homenick", "." ]
[ { "id": 3, "type": "column", "value": "date_problem_reported" }, { "id": 4, "type": "column", "value": "reported_by_staff_id" }, { "id": 6, "type": "column", "value": "staff_first_name" }, { "id": 8, "type": "column", "value": "staff_last_name" }, { "id": 0, "type": "column", "value": "problem_id" }, { "id": 1, "type": "table", "value": "problems" }, { "id": 5, "type": "column", "value": "staff_id" }, { "id": 9, "type": "column", "value": "Homenick" }, { "id": 2, "type": "table", "value": "staff" }, { "id": 7, "type": "column", "value": "Rylan" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-TABLE", "B-COLUMN", "B-COLUMN", "O" ]
14,330
movie_platform
bird:train.json:11
For all ratings which are rated in year 2020, name the movies which has the rating scored 4 and above.
SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE CAST(SUBSTR(T1.rating_timestamp_utc, 1, 4) AS INTEGER) = 2020 AND CAST(SUBSTR(T1.rating_timestamp_utc, 6, 2) AS INTEGER) > 4
[ "For", "all", "ratings", "which", "are", "rated", "in", "year", "2020", ",", "name", "the", "movies", "which", "has", "the", "rating", "scored", "4", "and", "above", "." ]
[ { "id": 6, "type": "column", "value": "rating_timestamp_utc" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 3, "type": "column", "value": "movie_id" }, { "id": 1, "type": "table", "value": "ratings" }, { "id": 2, "type": "table", "value": "movies" }, { "id": 4, "type": "value", "value": "2020" }, { "id": 5, "type": "value", "value": "4" }, { "id": 7, "type": "value", "value": "1" }, { "id": 8, "type": "value", "value": "6" }, { "id": 9, "type": "value", "value": "2" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
14,332
talkingdata
bird:train.json:1177
How many females use ZUK Z1 phones in the age group under 23?
SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.gender = 'F' AND T2.device_model = 'Z1' AND T1.`group` = 'F23-' AND T2.phone_brand = 'ZUK'
[ "How", "many", "females", "use", "ZUK", "Z1", "phones", "in", "the", "age", "group", "under", "23", "?" ]
[ { "id": 1, "type": "table", "value": "phone_brand_device_model2" }, { "id": 5, "type": "column", "value": "device_model" }, { "id": 9, "type": "column", "value": "phone_brand" }, { "id": 0, "type": "table", "value": "gender_age" }, { "id": 2, "type": "column", "value": "device_id" }, { "id": 3, "type": "column", "value": "gender" }, { "id": 7, "type": "column", "value": "group" }, { "id": 8, "type": "value", "value": "F23-" }, { "id": 10, "type": "value", "value": "ZUK" }, { "id": 6, "type": "value", "value": "Z1" }, { "id": 4, "type": "value", "value": "F" } ]
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[ "O", "O", "O", "O", "B-VALUE", "B-VALUE", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "B-COLUMN", "B-VALUE", "O" ]
14,333
thrombosis_prediction
bird:dev.json:1265
How many patients have a normal level of anti-ribonuclear protein and have been admitted to the hospital?
SELECT COUNT(DISTINCT T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.RNP = 'negative' OR T2.RNP = '0' AND T1.Admission = '+'
[ "How", "many", "patients", "have", "a", "normal", "level", "of", "anti", "-", "ribonuclear", "protein", "and", "have", "been", "admitted", "to", "the", "hospital", "?" ]
[ { "id": 1, "type": "table", "value": "laboratory" }, { "id": 6, "type": "column", "value": "admission" }, { "id": 4, "type": "value", "value": "negative" }, { "id": 0, "type": "table", "value": "patient" }, { "id": 3, "type": "column", "value": "rnp" }, { "id": 2, "type": "column", "value": "id" }, { "id": 5, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "+" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
14,334
professional_basketball
bird:train.json:2863
Who is the tallest player in Denver Nuggets since 1980?
SELECT T1.firstName, T1.lastName FROM players AS T1 INNER JOIN players_teams AS T2 ON T1.playerID = T2.playerID INNER JOIN teams AS T3 ON T3.tmID = T2.tmID WHERE T3.name = 'Denver Nuggets' AND T2.year > 1980 ORDER BY T1.height DESC LIMIT 1
[ "Who", "is", "the", "tallest", "player", "in", "Denver", "Nuggets", "since", "1980", "?" ]
[ { "id": 8, "type": "value", "value": "Denver Nuggets" }, { "id": 5, "type": "table", "value": "players_teams" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 1, "type": "column", "value": "lastname" }, { "id": 11, "type": "column", "value": "playerid" }, { "id": 4, "type": "table", "value": "players" }, { "id": 3, "type": "column", "value": "height" }, { "id": 2, "type": "table", "value": "teams" }, { "id": 6, "type": "column", "value": "tmid" }, { "id": 7, "type": "column", "value": "name" }, { "id": 9, "type": "column", "value": "year" }, { "id": 10, "type": "value", "value": "1980" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O" ]
14,335
retail_world
bird:train.json:6471
List down the company names that have the highest reorder level.
SELECT DISTINCT T2.CompanyName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.ReorderLevel = ( SELECT MAX(ReorderLevel) FROM Products )
[ "List", "down", "the", "company", "names", "that", "have", "the", "highest", "reorder", "level", "." ]
[ { "id": 3, "type": "column", "value": "reorderlevel" }, { "id": 0, "type": "column", "value": "companyname" }, { "id": 4, "type": "column", "value": "supplierid" }, { "id": 2, "type": "table", "value": "suppliers" }, { "id": 1, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
14,336
movie_3
bird:train.json:9218
Among the films rented by Natalie Meyer, describe the titles and categories of the films which were rented in February 2006.
SELECT T3.title, T2.name FROM film_category AS T1 INNER JOIN category AS T2 ON T1.category_id = T2.category_id INNER JOIN film AS T3 ON T1.film_id = T3.film_id INNER JOIN inventory AS T4 ON T3.film_id = T4.film_id INNER JOIN customer AS T5 ON T4.store_id = T5.store_id INNER JOIN rental AS T6 ON T4.inventory_id = T6.inventory_id WHERE T5.first_name = 'Natalie' AND T5.last_name = 'Meyer' AND STRFTIME('%Y',T3.rental_rate) = '2006' AND STRFTIME('%m',T3.rental_rate) = '2'
[ "Among", "the", "films", "rented", "by", "Natalie", "Meyer", ",", "describe", "the", "titles", "and", "categories", "of", "the", "films", "which", "were", "rented", "in", "February", "2006", "." ]
[ { "id": 18, "type": "table", "value": "film_category" }, { "id": 4, "type": "column", "value": "inventory_id" }, { "id": 14, "type": "column", "value": "rental_rate" }, { "id": 20, "type": "column", "value": "category_id" }, { "id": 5, "type": "column", "value": "first_name" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 11, "type": "table", "value": "inventory" }, { "id": 3, "type": "table", "value": "customer" }, { "id": 12, "type": "column", "value": "store_id" }, { "id": 19, "type": "table", "value": "category" }, { "id": 6, "type": "value", "value": "Natalie" }, { "id": 17, "type": "column", "value": "film_id" }, { "id": 2, "type": "table", "value": "rental" }, { "id": 0, "type": "column", "value": "title" }, { "id": 8, "type": "value", "value": "Meyer" }, { "id": 1, "type": "column", "value": "name" }, { "id": 9, "type": "value", "value": "2006" }, { "id": 16, "type": "table", "value": "film" }, { "id": 13, "type": "value", "value": "%Y" }, { "id": 15, "type": "value", "value": "%m" }, { "id": 10, "type": "value", "value": "2" } ]
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[ "O", "O", "B-TABLE", "B-TABLE", "O", "B-VALUE", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
14,337
match_season
spider:train_spider.json:1078
What are the official languages of the countries of players from Maryland or Duke college?
SELECT T1.Official_native_language FROM country AS T1 JOIN match_season AS T2 ON T1.Country_id = T2.Country WHERE T2.College = "Maryland" OR T2.College = "Duke"
[ "What", "are", "the", "official", "languages", "of", "the", "countries", "of", "players", "from", "Maryland", "or", "Duke", "college", "?" ]
[ { "id": 0, "type": "column", "value": "official_native_language" }, { "id": 2, "type": "table", "value": "match_season" }, { "id": 3, "type": "column", "value": "country_id" }, { "id": 6, "type": "column", "value": "Maryland" }, { "id": 1, "type": "table", "value": "country" }, { "id": 4, "type": "column", "value": "country" }, { "id": 5, "type": "column", "value": "college" }, { "id": 7, "type": "column", "value": "Duke" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O" ]
14,338
shakespeare
bird:train.json:2989
In the year 1500s, how many tragedies did Shakespeare write?
SELECT COUNT(id) FROM works WHERE GenreType = 'Tragedy' AND Date BETWEEN 1500 AND 1599
[ "In", "the", "year", "1500s", ",", "how", "many", "tragedies", "did", "Shakespeare", "write", "?" ]
[ { "id": 2, "type": "column", "value": "genretype" }, { "id": 3, "type": "value", "value": "Tragedy" }, { "id": 0, "type": "table", "value": "works" }, { "id": 4, "type": "column", "value": "date" }, { "id": 5, "type": "value", "value": "1500" }, { "id": 6, "type": "value", "value": "1599" }, { "id": 1, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O" ]