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2,462
|
donor
|
bird:train.json:3254
|
How many donations were paid via credit card to Memphis City School District?
|
SELECT COUNT(T1.projectid) FROM donations AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T1.payment_method = 'creditcard' AND T2.school_district = 'Memphis City School District'
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2,463
|
formula_1
|
bird:dev.json:947
|
How many British drivers were born after 1980?
|
SELECT COUNT(driverId) FROM drivers WHERE nationality = 'British' AND STRFTIME('%Y', dob) > '1980'
|
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2,464
|
local_govt_and_lot
|
spider:train_spider.json:4846
|
What is the maximum number that a certain service is provided? List the service id, details and number.
|
SELECT T1.service_id , T1.service_details , count(*) FROM Services AS T1 JOIN Residents_Services AS T2 ON T1.service_id = T2.service_id GROUP BY T1.service_id ORDER BY count(*) DESC LIMIT 1
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"I-COLUMN",
"O",
"O",
"O"
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2,465
|
driving_school
|
spider:train_spider.json:6714
|
What is the id and detail of the vehicle used in lessons for most of the times?
|
SELECT T1.vehicle_id , T1.vehicle_details FROM Vehicles AS T1 JOIN Lessons AS T2 ON T1.vehicle_id = T2.vehicle_id GROUP BY T1.vehicle_id ORDER BY count(*) DESC LIMIT 1
|
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"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,466
|
synthea
|
bird:train.json:1508
|
What are the medical encounter ids of patients who were born in Pembroke MA US?
|
SELECT DISTINCT T1.ENCOUNTER FROM careplans AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE T2.birthplace = 'Pembroke MA US'
|
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"type": "table",
"value": "patients"
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"type": "column",
"value": "patient"
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"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
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2,467
|
professional_basketball
|
bird:train.json:2872
|
What is the first and last name of the player with the highest field goal made rate in 1973?
|
SELECT T1.firstName, T1.lastName FROM players AS T1 INNER JOIN players_teams AS T2 ON T1.playerID = T2.playerID WHERE year = 1973 ORDER BY CAST(T2.fgMade AS REAL) / T2.fgAttempted DESC LIMIT 1
|
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{
"id": 4,
"type": "column",
"value": "year"
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{
"id": 5,
"type": "value",
"value": "1973"
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2,468
|
olympics
|
bird:train.json:4913
|
Please list the names of all the Olympic games that John Aalberg has taken part in.
|
SELECT T1.games_name FROM games AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.games_id INNER JOIN person AS T3 ON T2.person_id = T3.id WHERE T3.full_name = 'John Aalberg'
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"O",
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2,469
|
cre_Theme_park
|
spider:train_spider.json:5953
|
Show the names and ids of tourist attractions that are visited at least two times.
|
SELECT T1.Name , T2.Tourist_Attraction_ID FROM Tourist_Attractions AS T1 JOIN VISITS AS T2 ON T1.Tourist_Attraction_ID = T2.Tourist_Attraction_ID GROUP BY T2.Tourist_Attraction_ID HAVING count(*) >= 2
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"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
2,470
|
formula_1
|
bird:dev.json:921
|
Please give more information about the Formula_1 races that used the Silverstone Circuit.
|
SELECT DISTINCT T1.url FROM circuits AS T1 INNER JOIN races AS T2 ON T2.circuitID = T1.circuitId WHERE T1.name = 'Silverstone Circuit'
|
[
"Please",
"give",
"more",
"information",
"about",
"the",
"Formula_1",
"races",
"that",
"used",
"the",
"Silverstone",
"Circuit",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Silverstone Circuit"
},
{
"id": 5,
"type": "column",
"value": "circuitid"
},
{
"id": 1,
"type": "table",
"value": "circuits"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "url"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,472
|
books
|
bird:train.json:6011
|
How many authors are named Adam?
|
SELECT COUNT(*) FROM author WHERE author_name LIKE 'Adam%'
|
[
"How",
"many",
"authors",
"are",
"named",
"Adam",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "author_name"
},
{
"id": 0,
"type": "table",
"value": "author"
},
{
"id": 2,
"type": "value",
"value": "Adam%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,473
|
hockey
|
bird:train.json:7720
|
For the goalie who had the highest defensive success rate in the postseason of 2011, what's his legends ID ?
|
SELECT T2.legendsID FROM Goalies AS T1 INNER JOIN Master AS T2 ON T1.playerID = T2.playerID WHERE T1.year = 2011 ORDER BY 1 - CAST(T1.PostGA AS REAL) / T1.PostSA DESC LIMIT 1
|
[
"For",
"the",
"goalie",
"who",
"had",
"the",
"highest",
"defensive",
"success",
"rate",
"in",
"the",
"postseason",
"of",
"2011",
",",
"what",
"'s",
"his",
"legends",
"ID",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "legendsid"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 1,
"type": "table",
"value": "goalies"
},
{
"id": 2,
"type": "table",
"value": "master"
},
{
"id": 7,
"type": "column",
"value": "postsa"
},
{
"id": 8,
"type": "column",
"value": "postga"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "2011"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19,
20
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
12
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,474
|
public_review_platform
|
bird:train.json:4124
|
What is the review length of user 11021 to business with business ID 3?
|
SELECT review_length FROM Reviews WHERE user_id = 11021 AND business_id = 3
|
[
"What",
"is",
"the",
"review",
"length",
"of",
"user",
"11021",
"to",
"business",
"with",
"business",
"ID",
"3",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "review_length"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "reviews"
},
{
"id": 2,
"type": "column",
"value": "user_id"
},
{
"id": 3,
"type": "value",
"value": "11021"
},
{
"id": 5,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
2,475
|
video_games
|
bird:train.json:3438
|
How many games are not of the genres 'Role-Playing', 'Shooter' and 'Simulation'?
|
SELECT COUNT(T2.id) FROM genre AS T1 INNER JOIN game AS T2 ON T1.id = T2.genre_id WHERE T1.genre_name NOT IN ('Role-Playing', 'Shooter', 'Simulation')
|
[
"How",
"many",
"games",
"are",
"not",
"of",
"the",
"genres",
"'",
"Role",
"-",
"Playing",
"'",
",",
"'",
"Shooter",
"'",
"and",
"'",
"Simulation",
"'",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Role-Playing"
},
{
"id": 2,
"type": "column",
"value": "genre_name"
},
{
"id": 5,
"type": "value",
"value": "Simulation"
},
{
"id": 7,
"type": "column",
"value": "genre_id"
},
{
"id": 4,
"type": "value",
"value": "Shooter"
},
{
"id": 0,
"type": "table",
"value": "genre"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
19
]
},
{
"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",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,476
|
gas_company
|
spider:train_spider.json:2021
|
Show all headquarters without a company in banking industry.
|
SELECT headquarters FROM company EXCEPT SELECT headquarters FROM company WHERE main_industry = 'Banking'
|
[
"Show",
"all",
"headquarters",
"without",
"a",
"company",
"in",
"banking",
"industry",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "main_industry"
},
{
"id": 1,
"type": "column",
"value": "headquarters"
},
{
"id": 0,
"type": "table",
"value": "company"
},
{
"id": 3,
"type": "value",
"value": "Banking"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,477
|
image_and_language
|
bird:train.json:7499
|
How many samples of food object are there in image no.6?
|
SELECT COUNT(T2.OBJ_SAMPLE_ID) FROM OBJ_CLASSES AS T1 INNER JOIN IMG_OBJ AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T2.IMG_ID = 6 AND T1.OBJ_CLASS = 'food'
|
[
"How",
"many",
"samples",
"of",
"food",
"object",
"are",
"there",
"in",
"image",
"no.6",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "obj_sample_id"
},
{
"id": 3,
"type": "column",
"value": "obj_class_id"
},
{
"id": 0,
"type": "table",
"value": "obj_classes"
},
{
"id": 6,
"type": "column",
"value": "obj_class"
},
{
"id": 1,
"type": "table",
"value": "img_obj"
},
{
"id": 4,
"type": "column",
"value": "img_id"
},
{
"id": 7,
"type": "value",
"value": "food"
},
{
"id": 5,
"type": "value",
"value": "6"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,478
|
document_management
|
spider:train_spider.json:4509
|
What is the structure of the document with the least number of accesses?
|
SELECT t2.document_structure_description FROM documents AS t1 JOIN document_structures AS t2 ON t1.document_structure_code = t2.document_structure_code GROUP BY t1.document_structure_code ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"structure",
"of",
"the",
"document",
"with",
"the",
"least",
"number",
"of",
"accesses",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "document_structure_description"
},
{
"id": 0,
"type": "column",
"value": "document_structure_code"
},
{
"id": 3,
"type": "table",
"value": "document_structures"
},
{
"id": 2,
"type": "table",
"value": "documents"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"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-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,479
|
simpson_episodes
|
bird:train.json:4216
|
Among the casts who were born in Los Angeles, describe the name and birth date of who have 1.8 m and above in height.
|
SELECT name, birthdate FROM Person WHERE birth_place = 'Los Angeles' AND height_meters >= 1.8;
|
[
"Among",
"the",
"casts",
"who",
"were",
"born",
"in",
"Los",
"Angeles",
",",
"describe",
"the",
"name",
"and",
"birth",
"date",
"of",
"who",
"have",
"1.8",
"m",
"and",
"above",
"in",
"height",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "height_meters"
},
{
"id": 3,
"type": "column",
"value": "birth_place"
},
{
"id": 4,
"type": "value",
"value": "Los Angeles"
},
{
"id": 2,
"type": "column",
"value": "birthdate"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "1.8"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
14,
15
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7,
8
]
},
{
"entity_id": 5,
"token_idxs": [
24
]
},
{
"entity_id": 6,
"token_idxs": [
19
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
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{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,480
|
retails
|
bird:train.json:6700
|
Calculates the profit processed by Supplier No. 7414 on order No. 817154.
|
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_suppkey = 7414 AND T1.l_orderkey = 817154
|
[
"Calculates",
"the",
"profit",
"processed",
"by",
"Supplier",
"No",
".",
"7414",
"on",
"order",
"No",
".",
"817154",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "l_extendedprice"
},
{
"id": 8,
"type": "column",
"value": "ps_supplycost"
},
{
"id": 3,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 5,
"type": "column",
"value": "l_orderkey"
},
{
"id": 9,
"type": "column",
"value": "l_quantity"
},
{
"id": 11,
"type": "column",
"value": "l_discount"
},
{
"id": 2,
"type": "column",
"value": "l_suppkey"
},
{
"id": 0,
"type": "table",
"value": "lineitem"
},
{
"id": 1,
"type": "table",
"value": "partsupp"
},
{
"id": 6,
"type": "value",
"value": "817154"
},
{
"id": 4,
"type": "value",
"value": "7414"
},
{
"id": 10,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,481
|
soccer_3
|
bird:test.json:38
|
Show the earnings of players from country "Australia" or "Zimbabwe".
|
SELECT Earnings FROM player WHERE Country = "Australia" OR Country = "Zimbabwe"
|
[
"Show",
"the",
"earnings",
"of",
"players",
"from",
"country",
"\"",
"Australia",
"\"",
"or",
"\"",
"Zimbabwe",
"\"",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "Australia"
},
{
"id": 1,
"type": "column",
"value": "earnings"
},
{
"id": 4,
"type": "column",
"value": "Zimbabwe"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,482
|
sales
|
bird:train.json:5375
|
What is the last name of the customer who placed an order for sales id 178?
|
SELECT T1.LastName FROM Customers AS T1 INNER JOIN Sales AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.SalesID = 178
|
[
"What",
"is",
"the",
"last",
"name",
"of",
"the",
"customer",
"who",
"placed",
"an",
"order",
"for",
"sales",
"i",
"d",
"178",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "column",
"value": "salesid"
},
{
"id": 2,
"type": "table",
"value": "sales"
},
{
"id": 4,
"type": "value",
"value": "178"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
14,
15
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
2,483
|
products_gen_characteristics
|
spider:train_spider.json:5595
|
Return the name of the characteristic that is most common across all products.
|
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 GROUP BY t3.characteristic_name ORDER BY count(*) DESC LIMIT 1
|
[
"Return",
"the",
"name",
"of",
"the",
"characteristic",
"that",
"is",
"most",
"common",
"across",
"all",
"products",
"."
] |
[
{
"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_id"
},
{
"id": 2,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,484
|
shipping
|
bird:train.json:5613
|
How many shipments with weight of no more than 1,000 pounds were shipped by the oldest truck?
|
SELECT COUNT(*) FROM truck AS T1 INNER JOIN shipment AS T2 ON T1.truck_id = T2.truck_id WHERE T2.weight < 1000 ORDER BY T1.model_year ASC LIMIT 1
|
[
"How",
"many",
"shipments",
"with",
"weight",
"of",
"no",
"more",
"than",
"1,000",
"pounds",
"were",
"shipped",
"by",
"the",
"oldest",
"truck",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "model_year"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 5,
"type": "column",
"value": "truck_id"
},
{
"id": 2,
"type": "column",
"value": "weight"
},
{
"id": 0,
"type": "table",
"value": "truck"
},
{
"id": 3,
"type": "value",
"value": "1000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,485
|
regional_sales
|
bird:train.json:2734
|
Identify the store location and sales team who processed the sales order 'SO - 0001004'.
|
SELECT T3.`Sales Team`, T1.`City Name` FROM `Store Locations` AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._StoreID = T1.StoreID INNER JOIN `Sales Team` AS T3 ON T3.SalesTeamID = T2._SalesTeamID WHERE T2.OrderNumber = 'SO - 0001004'
|
[
"Identify",
"the",
"store",
"location",
"and",
"sales",
"team",
"who",
"processed",
"the",
"sales",
"order",
"'",
"SO",
"-",
"0001004",
"'",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "Store Locations"
},
{
"id": 4,
"type": "value",
"value": "SO - 0001004"
},
{
"id": 6,
"type": "table",
"value": "Sales Orders"
},
{
"id": 8,
"type": "column",
"value": "_salesteamid"
},
{
"id": 3,
"type": "column",
"value": "ordernumber"
},
{
"id": 7,
"type": "column",
"value": "salesteamid"
},
{
"id": 0,
"type": "column",
"value": "Sales Team"
},
{
"id": 2,
"type": "table",
"value": "Sales Team"
},
{
"id": 1,
"type": "column",
"value": "City Name"
},
{
"id": 9,
"type": "column",
"value": "_storeid"
},
{
"id": 10,
"type": "column",
"value": "storeid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"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": [
2
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,486
|
climbing
|
spider:train_spider.json:1115
|
What are the names of climbers who are not from the country of Switzerland?
|
SELECT Name FROM climber WHERE Country != "Switzerland"
|
[
"What",
"are",
"the",
"names",
"of",
"climbers",
"who",
"are",
"not",
"from",
"the",
"country",
"of",
"Switzerland",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Switzerland"
},
{
"id": 0,
"type": "table",
"value": "climber"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,487
|
codebase_comments
|
bird:train.json:674
|
What is the task method of the tokenized name "string extensions to pascal case
"?
|
SELECT DISTINCT SUBSTR(SUBSTR(Name, INSTR(Name, '.') + 1), 1, INSTR(SUBSTR(Name, INSTR(Name, '.') + 1), '.') - 1) task FROM Method WHERE NameTokenized = 'string extensions to pascal case'
|
[
"What",
"is",
"the",
"task",
"method",
"of",
"the",
"tokenized",
"name",
"\"",
"string",
"extensions",
"to",
"pascal",
"case",
"\n",
"\"",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "string extensions to pascal case"
},
{
"id": 1,
"type": "column",
"value": "nametokenized"
},
{
"id": 0,
"type": "table",
"value": "method"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "1"
},
{
"id": 5,
"type": "value",
"value": "."
}
] |
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},
{
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"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
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"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
2,488
|
restaurant
|
bird:train.json:1711
|
What kind of restaurants can be found at "106 E 25th Ave"?
|
SELECT T1.food_type FROM generalinfo AS T1 INNER JOIN location AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T2.street_num = 106 AND T2.street_name = 'e 25th ave'
|
[
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"restaurants",
"can",
"be",
"found",
"at",
"\"",
"106",
"E",
"25th",
"Ave",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "id_restaurant"
},
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 6,
"type": "column",
"value": "street_name"
},
{
"id": 4,
"type": "column",
"value": "street_num"
},
{
"id": 7,
"type": "value",
"value": "e 25th ave"
},
{
"id": 0,
"type": "column",
"value": "food_type"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 5,
"type": "value",
"value": "106"
}
] |
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},
{
"entity_id": 18,
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},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,489
|
activity_1
|
spider:train_spider.json:6735
|
Show all the buildings along with the number of faculty members the buildings have.
|
SELECT building , count(*) FROM Faculty GROUP BY building
|
[
"Show",
"all",
"the",
"buildings",
"along",
"with",
"the",
"number",
"of",
"faculty",
"members",
"the",
"buildings",
"have",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "building"
},
{
"id": 0,
"type": "table",
"value": "faculty"
}
] |
[
{
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"entity_id": 16,
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},
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"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",
"O",
"O",
"O",
"O"
] |
2,490
|
inn_1
|
spider:train_spider.json:2625
|
How many rooms cost more than 120, for each different decor?
|
SELECT decor , count(*) FROM Rooms WHERE basePrice > 120 GROUP BY decor;
|
[
"How",
"many",
"rooms",
"cost",
"more",
"than",
"120",
",",
"for",
"each",
"different",
"decor",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "baseprice"
},
{
"id": 0,
"type": "table",
"value": "rooms"
},
{
"id": 1,
"type": "column",
"value": "decor"
},
{
"id": 3,
"type": "value",
"value": "120"
}
] |
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{
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2
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{
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},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,491
|
party_host
|
spider:train_spider.json:2664
|
What are the themes and locations of parties?
|
SELECT Party_Theme , LOCATION FROM party
|
[
"What",
"are",
"the",
"themes",
"and",
"locations",
"of",
"parties",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "party_theme"
},
{
"id": 2,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "party"
}
] |
[
{
"entity_id": 0,
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7
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{
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1,
2,
3
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
2,492
|
legislator
|
bird:train.json:4789
|
What is the ratio of males and females among historical legislators?
|
SELECT CAST(SUM(CASE WHEN gender_bio = 'M' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN gender_bio = 'F' THEN 1 ELSE 0 END) FROM historical
|
[
"What",
"is",
"the",
"ratio",
"of",
"males",
"and",
"females",
"among",
"historical",
"legislators",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "historical"
},
{
"id": 3,
"type": "column",
"value": "gender_bio"
},
{
"id": 1,
"type": "value",
"value": "0"
},
{
"id": 2,
"type": "value",
"value": "1"
},
{
"id": 4,
"type": "value",
"value": "F"
},
{
"id": 5,
"type": "value",
"value": "M"
}
] |
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{
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{
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
2,493
|
cookbook
|
bird:train.json:8877
|
How many cups of 1% lowfat milk should be added to no.1436 recipe?
|
SELECT COUNT(*) FROM Ingredient AS T1 INNER JOIN Quantity AS T2 ON T1.ingredient_id = T2.ingredient_id WHERE T1.name = '1% lowfat milk' AND T2.unit = 'cup(s)' AND T2.recipe_id = 1436
|
[
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"of",
"1",
"%",
"lowfat",
"milk",
"should",
"be",
"added",
"to",
"no.1436",
"recipe",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "1% lowfat milk"
},
{
"id": 2,
"type": "column",
"value": "ingredient_id"
},
{
"id": 0,
"type": "table",
"value": "ingredient"
},
{
"id": 7,
"type": "column",
"value": "recipe_id"
},
{
"id": 1,
"type": "table",
"value": "quantity"
},
{
"id": 6,
"type": "value",
"value": "cup(s)"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "unit"
},
{
"id": 8,
"type": "value",
"value": "1436"
}
] |
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{
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{
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"token_idxs": []
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"token_idxs": []
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{
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"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,494
|
chicago_crime
|
bird:train.json:8608
|
Where is the coordinate (41.66236555, -87.63470194) located? Give the name of the district.
|
SELECT T2.district_name FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T1.longitude = '-87.63470194' AND T1.latitude = '41.66236555'
|
[
"Where",
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"coordinate",
"(",
"41.66236555",
",",
"-87.63470194",
")",
"located",
"?",
"Give",
"the",
"name",
"of",
"the",
"district",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "district_name"
},
{
"id": 5,
"type": "value",
"value": "-87.63470194"
},
{
"id": 3,
"type": "column",
"value": "district_no"
},
{
"id": 7,
"type": "value",
"value": "41.66236555"
},
{
"id": 4,
"type": "column",
"value": "longitude"
},
{
"id": 2,
"type": "table",
"value": "district"
},
{
"id": 6,
"type": "column",
"value": "latitude"
},
{
"id": 1,
"type": "table",
"value": "crime"
}
] |
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{
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{
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{
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{
"entity_id": 16,
"token_idxs": []
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{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,495
|
professional_basketball
|
bird:train.json:2899
|
How many players, in games played in 1990, achieved 50% or less of oRebounds than dRebounds.
|
SELECT COUNT(playerID) FROM players_teams WHERE CAST(oRebounds AS REAL) * 100 / dRebounds <= 50 AND year = 1990
|
[
"How",
"many",
"players",
",",
"in",
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"played",
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"1990",
",",
"achieved",
"50",
"%",
"or",
"less",
"of",
"oRebounds",
"than",
"dRebounds",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "players_teams"
},
{
"id": 5,
"type": "column",
"value": "drebounds"
},
{
"id": 7,
"type": "column",
"value": "orebounds"
},
{
"id": 1,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "1990"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 2,
"type": "value",
"value": "50"
}
] |
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6
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},
{
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11
]
},
{
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},
{
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8
]
},
{
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18
]
},
{
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},
{
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16
]
},
{
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},
{
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},
{
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},
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},
{
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},
{
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},
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},
{
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,496
|
public_review_platform
|
bird:train.json:4035
|
Which year has the most elite users?
|
SELECT year_id FROM Elite GROUP BY year_id ORDER BY COUNT(user_id) DESC LIMIT 1
|
[
"Which",
"year",
"has",
"the",
"most",
"elite",
"users",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "year_id"
},
{
"id": 2,
"type": "column",
"value": "user_id"
},
{
"id": 0,
"type": "table",
"value": "elite"
}
] |
[
{
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5
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1
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6
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},
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{
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},
{
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
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}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
2,497
|
college_1
|
spider:train_spider.json:3274
|
What are the first names of all professors not teaching any classes?
|
SELECT emp_fname FROM employee WHERE emp_jobcode = 'PROF' EXCEPT SELECT T1.emp_fname FROM employee AS T1 JOIN CLASS AS T2 ON T1.emp_num = T2.prof_num
|
[
"What",
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"first",
"names",
"of",
"all",
"professors",
"not",
"teaching",
"any",
"classes",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "emp_jobcode"
},
{
"id": 1,
"type": "column",
"value": "emp_fname"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 6,
"type": "column",
"value": "prof_num"
},
{
"id": 5,
"type": "column",
"value": "emp_num"
},
{
"id": 4,
"type": "table",
"value": "class"
},
{
"id": 3,
"type": "value",
"value": "PROF"
}
] |
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{
"entity_id": 0,
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{
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5
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},
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},
{
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"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,498
|
olympics
|
bird:train.json:4990
|
How many Men's 200 Metres Freestyle events did Ian James Thorpe compete in?
|
SELECT COUNT(T1.id) FROM person AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.person_id INNER JOIN competitor_event AS T3 ON T2.id = T3.competitor_id INNER JOIN event AS T4 ON T3.event_id = T4.id WHERE T1.full_name = 'Ian James Thorpe' AND T4.event_name LIKE 'Swimming Men%s 200 metres Freestyle'
|
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"events",
"did",
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"James",
"Thorpe",
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"in",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Swimming Men%s 200 metres Freestyle"
},
{
"id": 2,
"type": "table",
"value": "competitor_event"
},
{
"id": 5,
"type": "value",
"value": "Ian James Thorpe"
},
{
"id": 9,
"type": "table",
"value": "games_competitor"
},
{
"id": 10,
"type": "column",
"value": "competitor_id"
},
{
"id": 6,
"type": "column",
"value": "event_name"
},
{
"id": 4,
"type": "column",
"value": "full_name"
},
{
"id": 11,
"type": "column",
"value": "person_id"
},
{
"id": 3,
"type": "column",
"value": "event_id"
},
{
"id": 8,
"type": "table",
"value": "person"
},
{
"id": 0,
"type": "table",
"value": "event"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
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},
{
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"token_idxs": []
}
] |
[
"O",
"B-VALUE",
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"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,499
|
game_1
|
spider:train_spider.json:6023
|
Show student ids who are on scholarship and have major 600.
|
SELECT StuID FROM Student WHERE major = 600 INTERSECT SELECT StuID FROM Sportsinfo WHERE onscholarship = 'Y'
|
[
"Show",
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"ids",
"who",
"are",
"on",
"scholarship",
"and",
"have",
"major",
"600",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "onscholarship"
},
{
"id": 1,
"type": "table",
"value": "sportsinfo"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 2,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "column",
"value": "major"
},
{
"id": 4,
"type": "value",
"value": "600"
},
{
"id": 6,
"type": "value",
"value": "Y"
}
] |
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{
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{
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{
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9
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6
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{
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{
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{
"entity_id": 13,
"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
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"entity_id": 15,
"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,500
|
university
|
bird:train.json:8046
|
What is the difference in overall student enrollment and international student enrollment at the Harvard university from 2011 to 2012?
|
SELECT SUM(T1.num_students) - SUM(CAST(T1.num_students * T1.pct_international_students AS REAL) / 100) FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T2.university_name = 'Harvard University' AND T1.year BETWEEN 2011 AND 2012
|
[
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"student",
"enrollment",
"at",
"the",
"Harvard",
"university",
"from",
"2011",
"to",
"2012",
"?"
] |
[
{
"id": 11,
"type": "column",
"value": "pct_international_students"
},
{
"id": 5,
"type": "value",
"value": "Harvard University"
},
{
"id": 0,
"type": "table",
"value": "university_year"
},
{
"id": 4,
"type": "column",
"value": "university_name"
},
{
"id": 2,
"type": "column",
"value": "university_id"
},
{
"id": 9,
"type": "column",
"value": "num_students"
},
{
"id": 1,
"type": "table",
"value": "university"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "2011"
},
{
"id": 8,
"type": "value",
"value": "2012"
},
{
"id": 10,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
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15
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{
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{
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{
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10
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9
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"entity_id": 15,
"token_idxs": []
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"entity_id": 16,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
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"B-COLUMN",
"B-COLUMN",
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"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,501
|
simpson_episodes
|
bird:train.json:4257
|
Which episode id did award Outstanding Animated Program (For Programming Less Than One Hour) with an episode star score of 10?
|
SELECT DISTINCT T1.episode_id FROM Award AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE T1.award = 'Outstanding Animated Program (For Programming Less Than One Hour)' AND T2.stars = 10;
|
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"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Outstanding Animated Program (For Programming Less Than One Hour)"
},
{
"id": 0,
"type": "column",
"value": "episode_id"
},
{
"id": 1,
"type": "table",
"value": "award"
},
{
"id": 3,
"type": "column",
"value": "award"
},
{
"id": 5,
"type": "column",
"value": "stars"
},
{
"id": 2,
"type": "table",
"value": "vote"
},
{
"id": 6,
"type": "value",
"value": "10"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
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[
"O",
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"B-COLUMN",
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"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,502
|
works_cycles
|
bird:train.json:7061
|
Among the active male employees, how many of them are paid with the highest frequency?
|
SELECT COUNT(T1.BusinessEntityID) FROM EmployeePayHistory AS T1 INNER JOIN Employee AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T2.CurrentFlag = 1 AND T2.Gender = 'M' AND T1.PayFrequency = 2
|
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"?"
] |
[
{
"id": 0,
"type": "table",
"value": "employeepayhistory"
},
{
"id": 2,
"type": "column",
"value": "businessentityid"
},
{
"id": 7,
"type": "column",
"value": "payfrequency"
},
{
"id": 3,
"type": "column",
"value": "currentflag"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 5,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "M"
},
{
"id": 8,
"type": "value",
"value": "2"
}
] |
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,505
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4184
|
What are the name and description for location code x?
|
SELECT location_name , location_description FROM Ref_locations WHERE location_code = "x"
|
[
"What",
"are",
"the",
"name",
"and",
"description",
"for",
"location",
"code",
"x",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "location_description"
},
{
"id": 0,
"type": "table",
"value": "ref_locations"
},
{
"id": 1,
"type": "column",
"value": "location_name"
},
{
"id": 3,
"type": "column",
"value": "location_code"
},
{
"id": 4,
"type": "column",
"value": "x"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
2,506
|
formula_1
|
bird:dev.json:884
|
List the names of all races that occurred in the earliest recorded year and month.
|
SELECT name FROM races WHERE STRFTIME('%Y', date) = ( SELECT STRFTIME('%Y', date) FROM races ORDER BY date ASC LIMIT 1 ) AND STRFTIME('%m', date) = ( SELECT STRFTIME('%m', date) FROM races ORDER BY date ASC LIMIT 1 )
|
[
"List",
"the",
"names",
"of",
"all",
"races",
"that",
"occurred",
"in",
"the",
"earliest",
"recorded",
"year",
"and",
"month",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "races"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "date"
},
{
"id": 2,
"type": "value",
"value": "%Y"
},
{
"id": 4,
"type": "value",
"value": "%m"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,507
|
law_episode
|
bird:train.json:1254
|
Who was credited as "technical advisor" in the episode titled "Cherished"?
|
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 = 'Cherished' AND T2.credited = 'true' AND T2.role = 'technical advisor'
|
[
"Who",
"was",
"credited",
"as",
"\"",
"technical",
"advisor",
"\"",
"in",
"the",
"episode",
"titled",
"\"",
"Cherished",
"\"",
"?"
] |
[
{
"id": 10,
"type": "value",
"value": "technical advisor"
},
{
"id": 11,
"type": "column",
"value": "episode_id"
},
{
"id": 4,
"type": "column",
"value": "person_id"
},
{
"id": 6,
"type": "value",
"value": "Cherished"
},
{
"id": 7,
"type": "column",
"value": "credited"
},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "table",
"value": "credit"
},
{
"id": 5,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "value",
"value": "true"
},
{
"id": 9,
"type": "column",
"value": "role"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
5,
6
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"I-VALUE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
2,508
|
music_1
|
spider:train_spider.json:3532
|
Find the id of the song that lasts the longest.
|
SELECT f_id FROM files ORDER BY duration DESC LIMIT 1
|
[
"Find",
"the",
"i",
"d",
"of",
"the",
"song",
"that",
"lasts",
"the",
"longest",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "duration"
},
{
"id": 0,
"type": "table",
"value": "files"
},
{
"id": 1,
"type": "column",
"value": "f_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0
]
},
{
"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": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,509
|
farm
|
spider:train_spider.json:16
|
How many farms are there?
|
SELECT count(*) FROM farm
|
[
"How",
"many",
"farms",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "farm"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
2,510
|
customers_card_transactions
|
spider:train_spider.json:736
|
How many different types of transactions are there?
|
SELECT count(DISTINCT transaction_type) FROM Financial_Transactions
|
[
"How",
"many",
"different",
"types",
"of",
"transactions",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "financial_transactions"
},
{
"id": 1,
"type": "column",
"value": "transaction_type"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
2,511
|
financial
|
bird:dev.json:127
|
List the account IDs with monthly issuance of statements.
|
SELECT account_id FROM account WHERE Frequency = 'POPLATEK MESICNE'
|
[
"List",
"the",
"account",
"IDs",
"with",
"monthly",
"issuance",
"of",
"statements",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "POPLATEK MESICNE"
},
{
"id": 1,
"type": "column",
"value": "account_id"
},
{
"id": 2,
"type": "column",
"value": "frequency"
},
{
"id": 0,
"type": "table",
"value": "account"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,512
|
world_development_indicators
|
bird:train.json:2122
|
What are the sources for the data of children who finished primary school education in Latin America & Caribbean countries?
|
SELECT DISTINCT T2.Source FROM Footnotes AS T1 INNER JOIN Series AS T2 ON T1.Seriescode = T2.SeriesCode INNER JOIN Country AS T3 ON T1.Countrycode = T3.CountryCode WHERE T3.Region = 'Latin America & Caribbean' AND T2.IndicatorName = 'Children out of school, primary'
|
[
"What",
"are",
"the",
"sources",
"for",
"the",
"data",
"of",
"children",
"who",
"finished",
"primary",
"school",
"education",
"in",
"Latin",
"America",
"&",
"Caribbean",
"countries",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Children out of school, primary"
},
{
"id": 6,
"type": "value",
"value": "Latin America & Caribbean"
},
{
"id": 7,
"type": "column",
"value": "indicatorname"
},
{
"id": 4,
"type": "column",
"value": "countrycode"
},
{
"id": 9,
"type": "column",
"value": "seriescode"
},
{
"id": 2,
"type": "table",
"value": "footnotes"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "source"
},
{
"id": 3,
"type": "table",
"value": "series"
},
{
"id": 5,
"type": "column",
"value": "region"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
19
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
15,
16,
17,
18
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8,
9,
10,
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O"
] |
2,513
|
regional_sales
|
bird:train.json:2673
|
Calculate the average monthly order and percentage of warehouse "WARE-NMK1003" in 2019. Among them, mention number of orders for floor lamps.
|
SELECT CAST(SUM(CASE WHEN T2.WarehouseCode = 'WARE-NMK1003' THEN 1 ELSE 0 END) AS REAL) / 12 , CAST(SUM(CASE WHEN T2.WarehouseCode = 'WARE-NMK1003' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.OrderNumber), COUNT(CASE WHEN T1.`Product Name` = 'Floor Lamps' AND T2.WarehouseCode = 'WARE-NMK1003' THEN T2.`Order Quantity` ELSE NULL END) FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID WHERE T2.OrderDate LIKE '%/%/19'
|
[
"Calculate",
"the",
"average",
"monthly",
"order",
"and",
"percentage",
"of",
"warehouse",
"\"",
"WARE",
"-",
"NMK1003",
"\"",
"in",
"2019",
".",
"Among",
"them",
",",
"mention",
"number",
"of",
"orders",
"for",
"floor",
"lamps",
"."
] |
[
{
"id": 9,
"type": "column",
"value": "Order Quantity"
},
{
"id": 14,
"type": "column",
"value": "warehousecode"
},
{
"id": 1,
"type": "table",
"value": "Sales Orders"
},
{
"id": 12,
"type": "column",
"value": "Product Name"
},
{
"id": 15,
"type": "value",
"value": "WARE-NMK1003"
},
{
"id": 8,
"type": "column",
"value": "ordernumber"
},
{
"id": 13,
"type": "value",
"value": "Floor Lamps"
},
{
"id": 5,
"type": "column",
"value": "_productid"
},
{
"id": 2,
"type": "column",
"value": "orderdate"
},
{
"id": 6,
"type": "column",
"value": "productid"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "value",
"value": "%/%/19"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "12"
},
{
"id": 10,
"type": "value",
"value": "0"
},
{
"id": 11,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
22,
23
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": [
21
]
},
{
"entity_id": 9,
"token_idxs": [
5
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": [
25,
26
]
},
{
"entity_id": 14,
"token_idxs": [
8
]
},
{
"entity_id": 15,
"token_idxs": [
10,
11
]
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,514
|
formula_1
|
spider:train_spider.json:2189
|
What are the numbers of races for each constructor id?
|
SELECT count(*) , constructorid FROM constructorStandings GROUP BY constructorid
|
[
"What",
"are",
"the",
"numbers",
"of",
"races",
"for",
"each",
"constructor",
"i",
"d",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "constructorstandings"
},
{
"id": 1,
"type": "column",
"value": "constructorid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8,
9,
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",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
2,515
|
e_learning
|
spider:train_spider.json:3802
|
Find the login name of the course author that teaches the course with name "advanced database".
|
SELECT T1.login_name FROM Course_Authors_and_Tutors AS T1 JOIN Courses AS T2 ON T1.author_id = T2.author_id WHERE T2.course_name = "advanced database"
|
[
"Find",
"the",
"login",
"name",
"of",
"the",
"course",
"author",
"that",
"teaches",
"the",
"course",
"with",
"name",
"\"",
"advanced",
"database",
"\"",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "course_authors_and_tutors"
},
{
"id": 4,
"type": "column",
"value": "advanced database"
},
{
"id": 3,
"type": "column",
"value": "course_name"
},
{
"id": 0,
"type": "column",
"value": "login_name"
},
{
"id": 5,
"type": "column",
"value": "author_id"
},
{
"id": 2,
"type": "table",
"value": "courses"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6,
8
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
15,
16
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"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",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
2,516
|
student_club
|
bird:dev.json:1349
|
Provide the total number of the budget amount for "September Speaker" event.
|
SELECT SUM(T1.amount) FROM budget AS T1 INNER JOIN event AS T2 ON T1.link_to_event = T2.event_id WHERE T2.event_name = 'September Speaker'
|
[
"Provide",
"the",
"total",
"number",
"of",
"the",
"budget",
"amount",
"for",
"\"",
"September",
"Speaker",
"\"",
"event",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "September Speaker"
},
{
"id": 5,
"type": "column",
"value": "link_to_event"
},
{
"id": 2,
"type": "column",
"value": "event_name"
},
{
"id": 6,
"type": "column",
"value": "event_id"
},
{
"id": 0,
"type": "table",
"value": "budget"
},
{
"id": 4,
"type": "column",
"value": "amount"
},
{
"id": 1,
"type": "table",
"value": "event"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
2,517
|
food_inspection_2
|
bird:train.json:6118
|
Please list the assumed name of all the facilities that failed an inspection in 2010.
|
SELECT DISTINCT T2.dba_name FROM inspection AS T1 INNER JOIN establishment AS T2 ON T1.license_no = T2.license_no WHERE T1.results = 'Fail' AND strftime('%Y', T1.inspection_date) = '2010'
|
[
"Please",
"list",
"the",
"assumed",
"name",
"of",
"all",
"the",
"facilities",
"that",
"failed",
"an",
"inspection",
"in",
"2010",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "inspection_date"
},
{
"id": 2,
"type": "table",
"value": "establishment"
},
{
"id": 1,
"type": "table",
"value": "inspection"
},
{
"id": 3,
"type": "column",
"value": "license_no"
},
{
"id": 0,
"type": "column",
"value": "dba_name"
},
{
"id": 4,
"type": "column",
"value": "results"
},
{
"id": 5,
"type": "value",
"value": "Fail"
},
{
"id": 6,
"type": "value",
"value": "2010"
},
{
"id": 7,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
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",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,518
|
public_review_platform
|
bird:train.json:3953
|
How many actively running Yelp businesses are there located in "Phoenix" city?
|
SELECT COUNT(business_id) FROM Business WHERE active = 'true' AND city = 'Phoenix'
|
[
"How",
"many",
"actively",
"running",
"Yelp",
"businesses",
"are",
"there",
"located",
"in",
"\"",
"Phoenix",
"\"",
"city",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 5,
"type": "value",
"value": "Phoenix"
},
{
"id": 2,
"type": "column",
"value": "active"
},
{
"id": 3,
"type": "value",
"value": "true"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O"
] |
2,520
|
products_gen_characteristics
|
spider:train_spider.json:5553
|
Return the names and typical buying and selling prices for products that have 'yellow' as their color description.
|
SELECT t1.product_name , t1.typical_buying_price , t1.typical_selling_price FROM products AS t1 JOIN ref_colors AS t2 ON t1.color_code = t2.color_code WHERE t2.color_description = "yellow"
|
[
"Return",
"the",
"names",
"and",
"typical",
"buying",
"and",
"selling",
"prices",
"for",
"products",
"that",
"have",
"'",
"yellow",
"'",
"as",
"their",
"color",
"description",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "typical_selling_price"
},
{
"id": 1,
"type": "column",
"value": "typical_buying_price"
},
{
"id": 5,
"type": "column",
"value": "color_description"
},
{
"id": 0,
"type": "column",
"value": "product_name"
},
{
"id": 4,
"type": "table",
"value": "ref_colors"
},
{
"id": 7,
"type": "column",
"value": "color_code"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 6,
"type": "column",
"value": "yellow"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
19
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
18
]
},
{
"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",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,521
|
authors
|
bird:train.json:3611
|
Who is the author of the paper titled "Open Sourcing Social Solutions (Building Communities of Change)"?
|
SELECT T2.Name FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Title = 'Open Sourcing Social Solutions (Building Communities of Change)'
|
[
"Who",
"is",
"the",
"author",
"of",
"the",
"paper",
"titled",
"\"",
"Open",
"Sourcing",
"Social",
"Solutions",
"(",
"Building",
"Communities",
"of",
"Change",
")",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Open Sourcing Social Solutions (Building Communities of Change)"
},
{
"id": 2,
"type": "table",
"value": "paperauthor"
},
{
"id": 6,
"type": "column",
"value": "paperid"
},
{
"id": 1,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9,
10,
11,
12,
13,
14,
15,
16,
17,
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,522
|
social_media
|
bird:train.json:791
|
What is the gender of the user who has posted the tweet that is seen by the most number of unique users?
|
SELECT T2.Gender FROM twitter AS T1 INNER JOIN user AS T2 ON T1.UserID = T2.UserID ORDER BY T1.Reach DESC LIMIT 1
|
[
"What",
"is",
"the",
"gender",
"of",
"the",
"user",
"who",
"has",
"posted",
"the",
"tweet",
"that",
"is",
"seen",
"by",
"the",
"most",
"number",
"of",
"unique",
"users",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "twitter"
},
{
"id": 0,
"type": "column",
"value": "gender"
},
{
"id": 3,
"type": "column",
"value": "userid"
},
{
"id": 2,
"type": "column",
"value": "reach"
}
] |
[
{
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{
"entity_id": 16,
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,523
|
driving_school
|
spider:train_spider.json:6636
|
How many staff have the first name Ludie?
|
SELECT count(*) FROM Staff WHERE first_name = "Ludie";
|
[
"How",
"many",
"staff",
"have",
"the",
"first",
"name",
"Ludie",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "staff"
},
{
"id": 2,
"type": "column",
"value": "Ludie"
}
] |
[
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2
]
},
{
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5,
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7
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},
{
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{
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},
{
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},
{
"entity_id": 14,
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},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
2,524
|
soccer_2016
|
bird:train.json:1865
|
Who got the Man of the Series Award in 2010?
|
SELECT T1.Player_Name FROM Player AS T1 INNER JOIN Match AS T2 ON T2.Man_of_the_Match = T1.Player_Id INNER JOIN Season AS T3 ON T3.Season_Id = T2.Season_Id WHERE T3.Season_Year = 2010 GROUP BY T1.Player_Name
|
[
"Who",
"got",
"the",
"Man",
"of",
"the",
"Series",
"Award",
"in",
"2010",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "man_of_the_match"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 2,
"type": "column",
"value": "season_year"
},
{
"id": 6,
"type": "column",
"value": "season_id"
},
{
"id": 8,
"type": "column",
"value": "player_id"
},
{
"id": 1,
"type": "table",
"value": "season"
},
{
"id": 4,
"type": "table",
"value": "player"
},
{
"id": 5,
"type": "table",
"value": "match"
},
{
"id": 3,
"type": "value",
"value": "2010"
}
] |
[
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"entity_id": 0,
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},
{
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},
{
"entity_id": 2,
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{
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{
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},
{
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},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,525
|
books
|
bird:train.json:6064
|
Who is the publisher of Hitchhiker's Guide To The Galaxy: The Filming of the Douglas Adams classic?
|
SELECT T2.publisher_name FROM book AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.publisher_id WHERE T1.title = 'Hitchhiker''s Guide To The Galaxy: The Filming of the Douglas Adams classic'
|
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"publisher",
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"Hitchhiker",
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"Guide",
"To",
"The",
"Galaxy",
":",
"The",
"Filming",
"of",
"the",
"Douglas",
"Adams",
"classic",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Hitchhiker's Guide To The Galaxy: The Filming of the Douglas Adams classic"
},
{
"id": 0,
"type": "column",
"value": "publisher_name"
},
{
"id": 5,
"type": "column",
"value": "publisher_id"
},
{
"id": 2,
"type": "table",
"value": "publisher"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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},
{
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{
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5,
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7,
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12,
13,
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16,
17,
18
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},
{
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},
{
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},
{
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},
{
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},
{
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},
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},
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{
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},
{
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},
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},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,526
|
retail_complains
|
bird:train.json:337
|
What is the name of the state that the client with the email "skylar.ramirez@gmail.com" lives in?
|
SELECT T3.state FROM state AS T1 INNER JOIN district AS T2 ON T1.StateCode = T2.state_abbrev INNER JOIN client AS T3 ON T2.district_id = T3.district_id WHERE T3.email = 'skylar.ramirez@gmail.com'
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"state",
"that",
"the",
"client",
"with",
"the",
"email",
"\"",
"skylar.ramirez@gmail.com",
"\"",
"lives",
"in",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "skylar.ramirez@gmail.com"
},
{
"id": 8,
"type": "column",
"value": "state_abbrev"
},
{
"id": 6,
"type": "column",
"value": "district_id"
},
{
"id": 7,
"type": "column",
"value": "statecode"
},
{
"id": 5,
"type": "table",
"value": "district"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 2,
"type": "column",
"value": "email"
},
{
"id": 4,
"type": "table",
"value": "state"
}
] |
[
{
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"token_idxs": []
},
{
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9
]
},
{
"entity_id": 2,
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12
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
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"token_idxs": []
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{
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},
{
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
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{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
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},
{
"entity_id": 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-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
2,527
|
college_1
|
spider:train_spider.json:3174
|
How many professors are in the accounting dept?
|
SELECT count(*) FROM professor AS T1 JOIN department AS T2 ON T1.dept_code = T2.dept_code WHERE DEPT_NAME = "Accounting"
|
[
"How",
"many",
"professors",
"are",
"in",
"the",
"accounting",
"dept",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "department"
},
{
"id": 3,
"type": "column",
"value": "Accounting"
},
{
"id": 0,
"type": "table",
"value": "professor"
},
{
"id": 2,
"type": "column",
"value": "dept_name"
},
{
"id": 4,
"type": "column",
"value": "dept_code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
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6
]
},
{
"entity_id": 4,
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7
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,528
|
european_football_2
|
bird:dev.json:1109
|
How was the build up play dribbling class for "LEI" on 2015/9/10?
|
SELECT t2.buildUpPlayDribblingClass FROM Team AS t1 INNER JOIN Team_Attributes AS t2 ON t1.team_api_id = t2.team_api_id WHERE t1.team_short_name = 'LEI' AND SUBSTR(t2.`date`, 1, 10) = '2015-09-10'
|
[
"How",
"was",
"the",
"build",
"up",
"play",
"dribbling",
"class",
"for",
"\"",
"LEI",
"\"",
"on",
"2015/9/10",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "buildupplaydribblingclass"
},
{
"id": 2,
"type": "table",
"value": "team_attributes"
},
{
"id": 4,
"type": "column",
"value": "team_short_name"
},
{
"id": 3,
"type": "column",
"value": "team_api_id"
},
{
"id": 6,
"type": "value",
"value": "2015-09-10"
},
{
"id": 1,
"type": "table",
"value": "team"
},
{
"id": 7,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "value",
"value": "LEI"
},
{
"id": 9,
"type": "value",
"value": "10"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
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{
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3,
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{
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{
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{
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{
"entity_id": 4,
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},
{
"entity_id": 5,
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10
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{
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{
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{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
2,529
|
movielens
|
bird:train.json:2344
|
What is the total amount male and female actors who were casted in movie ID 1684910 and what is the proportion between the highest quality actors against the worst quality of actors? Indicate your answer in percentage. List the the director as well as the genre.
|
SELECT SUM(IIF(a_gender = 'M', 1, 0)) , SUM(IIF(a_gender = 'F', 1, 0)) , CAST(SUM(IIF(a_quality = 5, 1, 0)) AS REAL) * 100 / COUNT(*) , CAST(SUM(IIF(a_quality = 0, 1, 0)) AS REAL) * 100 / COUNT(*), ( SELECT directorid FROM movies2directors WHERE movieid = 1684910 ) , ( SELECT genre FROM movies2directors WHERE movieid = 1684910 ) FROM actors WHERE actorid IN ( SELECT actorid FROM movies2actors WHERE movieid = 1684910 )
|
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"."
] |
[
{
"id": 6,
"type": "table",
"value": "movies2directors"
},
{
"id": 2,
"type": "table",
"value": "movies2actors"
},
{
"id": 12,
"type": "column",
"value": "directorid"
},
{
"id": 14,
"type": "column",
"value": "a_quality"
},
{
"id": 9,
"type": "column",
"value": "a_gender"
},
{
"id": 1,
"type": "column",
"value": "actorid"
},
{
"id": 7,
"type": "column",
"value": "movieid"
},
{
"id": 8,
"type": "value",
"value": "1684910"
},
{
"id": 0,
"type": "table",
"value": "actors"
},
{
"id": 13,
"type": "column",
"value": "genre"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "1"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "M"
},
{
"id": 11,
"type": "value",
"value": "F"
},
{
"id": 15,
"type": "value",
"value": "5"
}
] |
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{
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8
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},
{
"entity_id": 6,
"token_idxs": [
43
]
},
{
"entity_id": 7,
"token_idxs": [
13,
14
]
},
{
"entity_id": 8,
"token_idxs": [
15
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
30
]
},
{
"entity_id": 12,
"token_idxs": [
42
]
},
{
"entity_id": 13,
"token_idxs": [
47
]
},
{
"entity_id": 14,
"token_idxs": [
24
]
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,530
|
public_review_platform
|
bird:train.json:4004
|
How many active businesses from Casa Grande are registered in the database?
|
SELECT COUNT(business_id) FROM Business WHERE active = 'true' AND city = 'Casa Grande'
|
[
"How",
"many",
"active",
"businesses",
"from",
"Casa",
"Grande",
"are",
"registered",
"in",
"the",
"database",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 5,
"type": "value",
"value": "Casa Grande"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 2,
"type": "column",
"value": "active"
},
{
"id": 3,
"type": "value",
"value": "true"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5,
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,531
|
music_2
|
spider:train_spider.json:5179
|
What are the different stage positions for all musicians whose first name is "Solveig"?
|
SELECT DISTINCT T1.stageposition FROM Performance AS T1 JOIN Band AS T2 ON T1.bandmate = T2.id WHERE Firstname = "Solveig"
|
[
"What",
"are",
"the",
"different",
"stage",
"positions",
"for",
"all",
"musicians",
"whose",
"first",
"name",
"is",
"\"",
"Solveig",
"\"",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "stageposition"
},
{
"id": 1,
"type": "table",
"value": "performance"
},
{
"id": 3,
"type": "column",
"value": "firstname"
},
{
"id": 5,
"type": "column",
"value": "bandmate"
},
{
"id": 4,
"type": "column",
"value": "Solveig"
},
{
"id": 2,
"type": "table",
"value": "band"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,533
|
advertising_agencies
|
bird:test.json:2083
|
How many invoices do we have?
|
SELECT count(*) FROM Invoices
|
[
"How",
"many",
"invoices",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "invoices"
}
] |
[
{
"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"
] |
2,535
|
language_corpus
|
bird:train.json:5706
|
What is the revision page ID of title "Aigua dolça"?
|
SELECT revision FROM pages WHERE title = 'Aigua dolça'
|
[
"What",
"is",
"the",
"revision",
"page",
"ID",
"of",
"title",
"\"",
"Aigua",
"dolça",
"\"",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Aigua dolça"
},
{
"id": 1,
"type": "column",
"value": "revision"
},
{
"id": 0,
"type": "table",
"value": "pages"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
2,537
|
cre_Doc_Workflow
|
bird:test.json:2036
|
What is the description for the process outcome code working?
|
SELECT process_outcome_description FROM Process_outcomes WHERE process_outcome_code = "working"
|
[
"What",
"is",
"the",
"description",
"for",
"the",
"process",
"outcome",
"code",
"working",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "process_outcome_description"
},
{
"id": 2,
"type": "column",
"value": "process_outcome_code"
},
{
"id": 0,
"type": "table",
"value": "process_outcomes"
},
{
"id": 3,
"type": "column",
"value": "working"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"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",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,538
|
thrombosis_prediction
|
bird:dev.json:1186
|
Lists all patients by ID who were diagnosed with Behcet's and had their exams between 01/01/197 and 12/31/1997.
|
SELECT ID FROM Examination WHERE `Examination Date` BETWEEN '1997-01-01' AND '1997-12-31' AND Diagnosis = 'Behcet'
|
[
"Lists",
"all",
"patients",
"by",
"ID",
"who",
"were",
"diagnosed",
"with",
"Behcet",
"'s",
"and",
"had",
"their",
"exams",
"between",
"01/01/197",
"and",
"12/31/1997",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "Examination Date"
},
{
"id": 0,
"type": "table",
"value": "examination"
},
{
"id": 3,
"type": "value",
"value": "1997-01-01"
},
{
"id": 4,
"type": "value",
"value": "1997-12-31"
},
{
"id": 5,
"type": "column",
"value": "diagnosis"
},
{
"id": 6,
"type": "value",
"value": "Behcet"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,539
|
thrombosis_prediction
|
bird:dev.json:1171
|
How many underage patients were examined during the course of the three-year period from 1990 to 1993?
|
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Examination AS T2 ON T1.ID = T2.ID WHERE STRFTIME('%Y', T2.`Examination Date`) BETWEEN '1990' AND '1993' AND STRFTIME('%Y', T2.`Examination Date`) - STRFTIME('%Y', T1.Birthday) < 18
|
[
"How",
"many",
"underage",
"patients",
"were",
"examined",
"during",
"the",
"course",
"of",
"the",
"three",
"-",
"year",
"period",
"from",
"1990",
"to",
"1993",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "Examination Date"
},
{
"id": 1,
"type": "table",
"value": "examination"
},
{
"id": 8,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "value",
"value": "1990"
},
{
"id": 4,
"type": "value",
"value": "1993"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "18"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6,
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,540
|
thrombosis_prediction
|
bird:dev.json:1284
|
For the patient with the highest lactate dehydrogenase in the normal range, when was his or her data first recorded?
|
SELECT T1.`First Date` FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.LDH < 500 ORDER BY T2.LDH ASC LIMIT 1
|
[
"For",
"the",
"patient",
"with",
"the",
"highest",
"lactate",
"dehydrogenase",
"in",
"the",
"normal",
"range",
",",
"when",
"was",
"his",
"or",
"her",
"data",
"first",
"recorded",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "First Date"
},
{
"id": 2,
"type": "table",
"value": "laboratory"
},
{
"id": 1,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "ldh"
},
{
"id": 4,
"type": "value",
"value": "500"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19,
20
]
},
{
"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-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,541
|
art_1
|
bird:test.json:1312
|
Find the locations that have paintings before 1885 and no work with medium on canvas?
|
SELECT DISTINCT LOCATION FROM paintings WHERE YEAR < 1885 AND mediumOn != "canvas"
|
[
"Find",
"the",
"locations",
"that",
"have",
"paintings",
"before",
"1885",
"and",
"no",
"work",
"with",
"medium",
"on",
"canvas",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 4,
"type": "column",
"value": "mediumon"
},
{
"id": 5,
"type": "column",
"value": "canvas"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "1885"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
12,
13
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
2,542
|
store_product
|
spider:train_spider.json:4926
|
What is the average pages per minute color?
|
SELECT avg(pages_per_minute_color) FROM product
|
[
"What",
"is",
"the",
"average",
"pages",
"per",
"minute",
"color",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "pages_per_minute_color"
},
{
"id": 0,
"type": "table",
"value": "product"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5,
6,
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
2,543
|
e_learning
|
spider:train_spider.json:3831
|
Return the completion date for all the tests that have "Fail" result.
|
SELECT T1.date_of_completion FROM Student_Course_Enrolment AS T1 JOIN Student_Tests_Taken AS T2 ON T1.registration_id = T2.registration_id WHERE T2.test_result = "Fail"
|
[
"Return",
"the",
"completion",
"date",
"for",
"all",
"the",
"tests",
"that",
"have",
"\"",
"Fail",
"\"",
"result",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "student_course_enrolment"
},
{
"id": 2,
"type": "table",
"value": "student_tests_taken"
},
{
"id": 0,
"type": "column",
"value": "date_of_completion"
},
{
"id": 5,
"type": "column",
"value": "registration_id"
},
{
"id": 3,
"type": "column",
"value": "test_result"
},
{
"id": 4,
"type": "column",
"value": "Fail"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,544
|
bbc_channels
|
bird:test.json:133
|
Find the name of the directors whose age is between 30 and 60.
|
SELECT name FROM director WHERE age BETWEEN 30 AND 60
|
[
"Find",
"the",
"name",
"of",
"the",
"directors",
"whose",
"age",
"is",
"between",
"30",
"and",
"60",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "director"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "30"
},
{
"id": 4,
"type": "value",
"value": "60"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,545
|
soccer_2016
|
bird:train.json:1841
|
List the first team's name in the match with the highest winning margin.
|
SELECT T2.Team_Name FROM Match AS T1 INNER JOIN Team AS T2 ON T2.Team_Id = T1.Team_1 ORDER BY T1.Win_Margin DESC LIMIT 1
|
[
"List",
"the",
"first",
"team",
"'s",
"name",
"in",
"the",
"match",
"with",
"the",
"highest",
"winning",
"margin",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "win_margin"
},
{
"id": 0,
"type": "column",
"value": "team_name"
},
{
"id": 4,
"type": "column",
"value": "team_id"
},
{
"id": 5,
"type": "column",
"value": "team_1"
},
{
"id": 1,
"type": "table",
"value": "match"
},
{
"id": 2,
"type": "table",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,548
|
retail_complains
|
bird:train.json:311
|
List all the complaints narratives made by the customer named Brenda and last name Mayer.
|
SELECT T2.`Consumer complaint narrative` FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Brenda' AND T1.last = 'Mayer'
|
[
"List",
"all",
"the",
"complaints",
"narratives",
"made",
"by",
"the",
"customer",
"named",
"Brenda",
"and",
"last",
"name",
"Mayer",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "Consumer complaint narrative"
},
{
"id": 3,
"type": "column",
"value": "client_id"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 2,
"type": "table",
"value": "events"
},
{
"id": 5,
"type": "value",
"value": "Brenda"
},
{
"id": 4,
"type": "column",
"value": "first"
},
{
"id": 7,
"type": "value",
"value": "Mayer"
},
{
"id": 6,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
4
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
0
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,549
|
headphone_store
|
bird:test.json:950
|
How many stores are there in each neighborhood?
|
SELECT count(*) , neighborhood FROM store GROUP BY neighborhood
|
[
"How",
"many",
"stores",
"are",
"there",
"in",
"each",
"neighborhood",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "neighborhood"
},
{
"id": 0,
"type": "table",
"value": "store"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,550
|
student_club
|
bird:dev.json:1367
|
Which college do most of the members go to?
|
SELECT T2.college FROM member AS T1 INNER JOIN major AS T2 ON T1.link_to_major = T2.major_id GROUP BY T2.major_id ORDER BY COUNT(T2.college) DESC LIMIT 1
|
[
"Which",
"college",
"do",
"most",
"of",
"the",
"members",
"go",
"to",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "link_to_major"
},
{
"id": 0,
"type": "column",
"value": "major_id"
},
{
"id": 1,
"type": "column",
"value": "college"
},
{
"id": 2,
"type": "table",
"value": "member"
},
{
"id": 3,
"type": "table",
"value": "major"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
2,551
|
movie_3
|
bird:train.json:9299
|
Who are the actors that act in the ACADEMY DINOSAUR film?
|
SELECT T1.first_name, T1.last_name FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T2.film_id = T3.film_id WHERE T3.title = 'ACADEMY DINOSAUR'
|
[
"Who",
"are",
"the",
"actors",
"that",
"act",
"in",
"the",
"ACADEMY",
"DINOSAUR",
"film",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "ACADEMY DINOSAUR"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "table",
"value": "film_actor"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 8,
"type": "column",
"value": "actor_id"
},
{
"id": 7,
"type": "column",
"value": "film_id"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "table",
"value": "actor"
},
{
"id": 2,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9
]
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
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"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"O"
] |
2,552
|
theme_gallery
|
spider:train_spider.json:1684
|
Which themes have had corresponding exhibitions that have had attendance both below 100 and above 500?
|
SELECT T2.theme FROM exhibition_record AS T1 JOIN exhibition AS T2 ON T1.exhibition_id = T2.exhibition_id WHERE T1.attendance < 100 INTERSECT SELECT T2.theme FROM exhibition_record AS T1 JOIN exhibition AS T2 ON T1.exhibition_id = T2.exhibition_id WHERE T1.attendance > 500
|
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"?"
] |
[
{
"id": 1,
"type": "table",
"value": "exhibition_record"
},
{
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"type": "column",
"value": "exhibition_id"
},
{
"id": 2,
"type": "table",
"value": "exhibition"
},
{
"id": 3,
"type": "column",
"value": "attendance"
},
{
"id": 0,
"type": "column",
"value": "theme"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "500"
}
] |
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] |
[
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"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
2,553
|
sales
|
bird:train.json:5399
|
Calculate the total number of sales closed by Michel E. DeFrance?
|
SELECT COUNT(T1.SalesID) FROM Sales AS T1 INNER JOIN Employees AS T2 ON T1.SalesPersonID = T2.EmployeeID WHERE T2.FirstName = 'Michel' AND T2.MiddleInitial = 'e' AND T2.LastName = 'DeFrance'
|
[
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"total",
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"sales",
"closed",
"by",
"Michel",
"E.",
"DeFrance",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "salespersonid"
},
{
"id": 7,
"type": "column",
"value": "middleinitial"
},
{
"id": 4,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 5,
"type": "column",
"value": "firstname"
},
{
"id": 9,
"type": "column",
"value": "lastname"
},
{
"id": 10,
"type": "value",
"value": "DeFrance"
},
{
"id": 2,
"type": "column",
"value": "salesid"
},
{
"id": 6,
"type": "value",
"value": "Michel"
},
{
"id": 0,
"type": "table",
"value": "sales"
},
{
"id": 8,
"type": "value",
"value": "e"
}
] |
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[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"B-VALUE",
"O"
] |
2,554
|
movie_3
|
bird:train.json:9210
|
List down the actors' full names who performed in "CHOCOLATE DUCK" film.
|
SELECT T3.first_name, T3.last_name FROM film_actor AS T1 INNER JOIN film AS T2 ON T1.film_id = T2.film_id INNER JOIN actor AS T3 ON T1.actor_id = T3.actor_id WHERE T2.title = 'CHOCOLATE DUCK'
|
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"CHOCOLATE",
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"\"",
"film",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "CHOCOLATE DUCK"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 5,
"type": "table",
"value": "film_actor"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 7,
"type": "column",
"value": "actor_id"
},
{
"id": 8,
"type": "column",
"value": "film_id"
},
{
"id": 2,
"type": "table",
"value": "actor"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "table",
"value": "film"
}
] |
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},
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}
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[
"O",
"O",
"O",
"B-TABLE",
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"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
2,555
|
store_1
|
spider:train_spider.json:590
|
What is the first and last name of the employee who reports to Nancy Edwards?
|
SELECT T2.first_name , T2.last_name FROM employees AS T1 JOIN employees AS T2 ON T1.id = T2.reports_to WHERE T1.first_name = "Nancy" AND T1.last_name = "Edwards";
|
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[
{
"id": 0,
"type": "column",
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{
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"type": "column",
"value": "reports_to"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "employees"
},
{
"id": 6,
"type": "column",
"value": "Edwards"
},
{
"id": 5,
"type": "column",
"value": "Nancy"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
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},
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] |
[
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"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,556
|
works_cycles
|
bird:train.json:7097
|
Calculate the total quantity of purchased product that has been prepared by employee number 257 and is in pending shipment status.
|
SELECT SUM(T2.OrderQty) FROM PurchaseOrderHeader AS T1 INNER JOIN PurchaseOrderDetail AS T2 ON T1.PurchaseOrderID = T2.PurchaseOrderID WHERE T1.Status = 1
|
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[
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{
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{
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"type": "column",
"value": "purchaseorderid"
},
{
"id": 4,
"type": "column",
"value": "orderqty"
},
{
"id": 2,
"type": "column",
"value": "status"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
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{
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},
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
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"O",
"O",
"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,557
|
company_office
|
spider:train_spider.json:4564
|
Which buildings have more than one company offices? Give me the building names.
|
SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id HAVING COUNT(*) > 1
|
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"."
] |
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{
"id": 4,
"type": "table",
"value": "office_locations"
},
{
"id": 0,
"type": "column",
"value": "building_id"
},
{
"id": 6,
"type": "column",
"value": "company_id"
},
{
"id": 2,
"type": "table",
"value": "companies"
},
{
"id": 5,
"type": "table",
"value": "buildings"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "id"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
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"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,558
|
country_language
|
bird:test.json:1368
|
What are the maximum and minimum health scores among countries that are not "Norway".
|
SELECT max(health_score) , min(health_score) FROM countries WHERE name != "Norway"
|
[
"What",
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"Norway",
"\"",
"."
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[
{
"id": 3,
"type": "column",
"value": "health_score"
},
{
"id": 0,
"type": "table",
"value": "countries"
},
{
"id": 2,
"type": "column",
"value": "Norway"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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{
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{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,559
|
book_publishing_company
|
bird:train.json:239
|
Name the top five titles that sold more than average and list them in descending order of the number of sales in California stores?
|
SELECT T1.title FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id INNER JOIN publishers AS T3 ON T1.pub_id = T3.pub_id WHERE T2.qty > ( SELECT CAST(SUM(qty) AS REAL) / COUNT(title_id) FROM sales ) AND T3.state = 'CA' ORDER BY T2.qty DESC LIMIT 5
|
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"stores",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "publishers"
},
{
"id": 8,
"type": "column",
"value": "title_id"
},
{
"id": 3,
"type": "table",
"value": "titles"
},
{
"id": 5,
"type": "column",
"value": "pub_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "table",
"value": "sales"
},
{
"id": 6,
"type": "column",
"value": "state"
},
{
"id": 2,
"type": "column",
"value": "qty"
},
{
"id": 7,
"type": "value",
"value": "CA"
}
] |
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] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
2,560
|
address
|
bird:train.json:5158
|
Among the cities with area code 608, how many cities implement daylight savings?
|
SELECT COUNT(T2.city) FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 608 AND T2.daylight_savings = 'Yes'
|
[
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"how",
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"savings",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "daylight_savings"
},
{
"id": 0,
"type": "table",
"value": "area_code"
},
{
"id": 4,
"type": "column",
"value": "area_code"
},
{
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"type": "table",
"value": "zip_data"
},
{
"id": 3,
"type": "column",
"value": "zip_code"
},
{
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"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "608"
},
{
"id": 7,
"type": "value",
"value": "Yes"
}
] |
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[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,561
|
department_store
|
spider:train_spider.json:4741
|
What are the ids of the two department store chains with the largest number of department stores?
|
SELECT dept_store_chain_id FROM department_stores GROUP BY dept_store_chain_id ORDER BY count(*) DESC LIMIT 2
|
[
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"the",
"ids",
"of",
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"department",
"store",
"chains",
"with",
"the",
"largest",
"number",
"of",
"department",
"stores",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "dept_store_chain_id"
},
{
"id": 0,
"type": "table",
"value": "department_stores"
}
] |
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{
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},
{
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
2,562
|
movies_4
|
bird:train.json:472
|
What is the percentage of romance films among films produced in India in 2015?
|
SELECT CAST(COUNT(CASE WHEN T4.genre_name = 'Romance' THEN T1.movie_id ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN production_COUNTry AS T3 ON T1.movie_id = T3.movie_id INNER JOIN genre AS T4 ON T2.genre_id = T4.genre_id INNER JOIN COUNTry AS T5 ON T3.COUNTry_id = T5.COUNTry_id WHERE T5.COUNTry_name = 'India' AND T1.release_date BETWEEN '2015-01-01' AND '2015-12-31'
|
[
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"?"
] |
[
{
"id": 10,
"type": "table",
"value": "production_country"
},
{
"id": 3,
"type": "column",
"value": "country_name"
},
{
"id": 5,
"type": "column",
"value": "release_date"
},
{
"id": 13,
"type": "table",
"value": "movie_genres"
},
{
"id": 2,
"type": "column",
"value": "country_id"
},
{
"id": 6,
"type": "value",
"value": "2015-01-01"
},
{
"id": 7,
"type": "value",
"value": "2015-12-31"
},
{
"id": 14,
"type": "column",
"value": "genre_name"
},
{
"id": 9,
"type": "column",
"value": "movie_id"
},
{
"id": 11,
"type": "column",
"value": "genre_id"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 15,
"type": "value",
"value": "Romance"
},
{
"id": 1,
"type": "table",
"value": "genre"
},
{
"id": 4,
"type": "value",
"value": "India"
},
{
"id": 12,
"type": "table",
"value": "movie"
},
{
"id": 8,
"type": "value",
"value": "100"
}
] |
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{
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
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"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
2,563
|
thrombosis_prediction
|
bird:dev.json:1175
|
How old was the patient who had the highest hemoglobin count at the time of the examination, and what is the doctor's diagnosis?
|
SELECT STRFTIME('%Y', T2.Date) - STRFTIME('%Y', T1.Birthday), T1.Diagnosis FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID ORDER BY T2.HGB DESC LIMIT 1
|
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",",
"and",
"what",
"is",
"the",
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"?"
] |
[
{
"id": 2,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "column",
"value": "diagnosis"
},
{
"id": 7,
"type": "column",
"value": "birthday"
},
{
"id": 1,
"type": "table",
"value": "patient"
},
{
"id": 6,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "hgb"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "%Y"
}
] |
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},
{
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},
{
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}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,564
|
roller_coaster
|
spider:train_spider.json:6218
|
How many countries do not have an roller coaster longer than 3000?
|
SELECT count(*) FROM country WHERE country_id NOT IN ( SELECT country_id FROM roller_coaster WHERE LENGTH > 3000 )
|
[
"How",
"many",
"countries",
"do",
"not",
"have",
"an",
"roller",
"coaster",
"longer",
"than",
"3000",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "roller_coaster"
},
{
"id": 1,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "length"
},
{
"id": 4,
"type": "value",
"value": "3000"
}
] |
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},
{
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},
{
"entity_id": 19,
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}
] |
[
"O",
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"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
2,565
|
airline
|
bird:train.json:5886
|
List the description of the airports that have code that ends with number 3?
|
SELECT Description FROM Airports WHERE Code LIKE '%3'
|
[
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"the",
"airports",
"that",
"have",
"code",
"that",
"ends",
"with",
"number",
"3",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "table",
"value": "airports"
},
{
"id": 2,
"type": "column",
"value": "code"
},
{
"id": 3,
"type": "value",
"value": "%3"
}
] |
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{
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},
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]
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},
{
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},
{
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},
{
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},
{
"entity_id": 16,
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,566
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5119
|
Find the payment method that is used the most often in all the invoices. Give me its code.
|
SELECT payment_method_code FROM INVOICES GROUP BY payment_method_code ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
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"payment",
"method",
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"in",
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"the",
"invoices",
".",
"Give",
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"its",
"code",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "payment_method_code"
},
{
"id": 0,
"type": "table",
"value": "invoices"
}
] |
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},
{
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},
{
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,567
|
beer_factory
|
bird:train.json:5270
|
How many customers are named Charles in Sacramento?
|
SELECT COUNT(CustomerID) FROM customers WHERE First = 'Charles' AND City = 'Sacramento'
|
[
"How",
"many",
"customers",
"are",
"named",
"Charles",
"in",
"Sacramento",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "customerid"
},
{
"id": 5,
"type": "value",
"value": "Sacramento"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "value",
"value": "Charles"
},
{
"id": 2,
"type": "column",
"value": "first"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"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",
"B-VALUE",
"O"
] |
2,568
|
restaurant
|
bird:train.json:1745
|
Please indicate which labels have the city located in Santa Cruz.
|
SELECT T1.label FROM generalinfo AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T2.county = 'Santa Cruz county'
|
[
"Please",
"indicate",
"which",
"labels",
"have",
"the",
"city",
"located",
"in",
"Santa",
"Cruz",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Santa Cruz county"
},
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 2,
"type": "table",
"value": "geographic"
},
{
"id": 3,
"type": "column",
"value": "county"
},
{
"id": 0,
"type": "column",
"value": "label"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9,
10
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,569
|
icfp_1
|
spider:train_spider.json:2861
|
Count the number of institutions.
|
SELECT count(*) FROM inst
|
[
"Count",
"the",
"number",
"of",
"institutions",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "inst"
}
] |
[
{
"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": []
},
{
"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"
] |
2,570
|
superhero
|
bird:dev.json:841
|
Provide the weight and race of the superhero with superhero ID 40.
|
SELECT T1.weight_kg, T2.race FROM superhero AS T1 INNER JOIN race AS T2 ON T1.race_id = T2.id WHERE T1.id = 40
|
[
"Provide",
"the",
"weight",
"and",
"race",
"of",
"the",
"superhero",
"with",
"superhero",
"ID",
"40",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "weight_kg"
},
{
"id": 2,
"type": "table",
"value": "superhero"
},
{
"id": 6,
"type": "column",
"value": "race_id"
},
{
"id": 1,
"type": "column",
"value": "race"
},
{
"id": 3,
"type": "table",
"value": "race"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "40"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
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