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16.1k
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14,775
|
driving_school
|
spider:train_spider.json:6640
|
How many staff in total?
|
SELECT count(*) FROM Staff;
|
[
"How",
"many",
"staff",
"in",
"total",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "staff"
}
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{
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}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
14,776
|
student_club
|
bird:dev.json:1446
|
Calculate the percentage of zip codes that are PO boxes.
|
SELECT CAST(SUM(CASE WHEN type = 'PO Box' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(zip_code) FROM zip_code
|
[
"Calculate",
"the",
"percentage",
"of",
"zip",
"codes",
"that",
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"PO",
"boxes",
"."
] |
[
{
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"type": "table",
"value": "zip_code"
},
{
"id": 2,
"type": "column",
"value": "zip_code"
},
{
"id": 6,
"type": "value",
"value": "PO Box"
},
{
"id": 5,
"type": "column",
"value": "type"
},
{
"id": 1,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
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[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
14,777
|
entrepreneur
|
spider:train_spider.json:2277
|
What is the weight of the shortest person?
|
SELECT Weight FROM people ORDER BY Height ASC LIMIT 1
|
[
"What",
"is",
"the",
"weight",
"of",
"the",
"shortest",
"person",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "people"
},
{
"id": 1,
"type": "column",
"value": "weight"
},
{
"id": 2,
"type": "column",
"value": "height"
}
] |
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{
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}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
14,778
|
e_commerce
|
bird:test.json:62
|
List the customers' first name, middle initial, last name and payment methods.
|
SELECT T1.customer_first_name , T1.customer_middle_initial , T1.customer_last_name , T2.Payment_method_code FROM Customers AS T1 JOIN Customer_Payment_Methods AS T2 ON T1.customer_id = T2.customer_id
|
[
"List",
"the",
"customers",
"'",
"first",
"name",
",",
"middle",
"initial",
",",
"last",
"name",
"and",
"payment",
"methods",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "customer_payment_methods"
},
{
"id": 1,
"type": "column",
"value": "customer_middle_initial"
},
{
"id": 0,
"type": "column",
"value": "customer_first_name"
},
{
"id": 3,
"type": "column",
"value": "payment_method_code"
},
{
"id": 2,
"type": "column",
"value": "customer_last_name"
},
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "table",
"value": "customers"
}
] |
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"entity_id": 0,
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{
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"token_idxs": []
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{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
14,779
|
driving_school
|
spider:train_spider.json:6712
|
What is the first name of the staff who did not give any lesson?
|
SELECT first_name FROM Staff EXCEPT SELECT T2.first_name FROM Lessons AS T1 JOIN Staff AS T2 ON T1.staff_id = T2.staff_id
|
[
"What",
"is",
"the",
"first",
"name",
"of",
"the",
"staff",
"who",
"did",
"not",
"give",
"any",
"lesson",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "column",
"value": "staff_id"
},
{
"id": 2,
"type": "table",
"value": "lessons"
},
{
"id": 0,
"type": "table",
"value": "staff"
}
] |
[
{
"entity_id": 0,
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},
{
"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",
"O"
] |
14,780
|
insurance_fnol
|
spider:train_spider.json:911
|
What are all the policy types of the customer named "Dayana Robel"?
|
SELECT DISTINCT t3.policy_type_code FROM customers AS t1 JOIN customers_policies AS t2 ON t1.customer_id = t2.customer_id JOIN available_policies AS t3 ON t2.policy_id = t3.policy_id WHERE t1.customer_name = "Dayana Robel"
|
[
"What",
"are",
"all",
"the",
"policy",
"types",
"of",
"the",
"customer",
"named",
"\"",
"Dayana",
"Robel",
"\"",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "available_policies"
},
{
"id": 5,
"type": "table",
"value": "customers_policies"
},
{
"id": 0,
"type": "column",
"value": "policy_type_code"
},
{
"id": 2,
"type": "column",
"value": "customer_name"
},
{
"id": 3,
"type": "column",
"value": "Dayana Robel"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "policy_id"
}
] |
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{
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5,
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},
{
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3
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9
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},
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"token_idxs": []
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
14,781
|
activity_1
|
spider:train_spider.json:6802
|
Which students participate in both Canoeing and Kayaking as their activities? Tell me their student ids.
|
SELECT T1.stuid FROM participates_in AS T1 JOIN activity AS T2 ON T2.actid = T2.actid WHERE T2.activity_name = 'Canoeing' INTERSECT SELECT T1.stuid FROM participates_in AS T1 JOIN activity AS T2 ON T2.actid = T2.actid WHERE T2.activity_name = 'Kayaking'
|
[
"Which",
"students",
"participate",
"in",
"both",
"Canoeing",
"and",
"Kayaking",
"as",
"their",
"activities",
"?",
"Tell",
"me",
"their",
"student",
"ids",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "participates_in"
},
{
"id": 3,
"type": "column",
"value": "activity_name"
},
{
"id": 2,
"type": "table",
"value": "activity"
},
{
"id": 4,
"type": "value",
"value": "Canoeing"
},
{
"id": 5,
"type": "value",
"value": "Kayaking"
},
{
"id": 0,
"type": "column",
"value": "stuid"
},
{
"id": 6,
"type": "column",
"value": "actid"
}
] |
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{
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
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}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
14,783
|
disney
|
bird:train.json:4675
|
List the directors of movies that feature a song.
|
SELECT T2.director FROM characters AS T1 INNER JOIN director AS T2 ON T1.movie_title = T2.name WHERE T1.song IS NOT NULL GROUP BY T2.director
|
[
"List",
"the",
"directors",
"of",
"movies",
"that",
"feature",
"a",
"song",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "movie_title"
},
{
"id": 1,
"type": "table",
"value": "characters"
},
{
"id": 0,
"type": "column",
"value": "director"
},
{
"id": 2,
"type": "table",
"value": "director"
},
{
"id": 3,
"type": "column",
"value": "song"
},
{
"id": 5,
"type": "column",
"value": "name"
}
] |
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{
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"token_idxs": []
},
{
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{
"entity_id": 2,
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2
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},
{
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{
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"token_idxs": []
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{
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"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
14,784
|
superhero
|
bird:dev.json:794
|
Which hero was the fastest?
|
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN hero_attribute AS T2 ON T1.id = T2.hero_id INNER JOIN attribute AS T3 ON T2.attribute_id = T3.id WHERE T3.attribute_name = 'Speed' ORDER BY T2.attribute_value DESC LIMIT 1
|
[
"Which",
"hero",
"was",
"the",
"fastest",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "attribute_value"
},
{
"id": 0,
"type": "column",
"value": "superhero_name"
},
{
"id": 2,
"type": "column",
"value": "attribute_name"
},
{
"id": 6,
"type": "table",
"value": "hero_attribute"
},
{
"id": 7,
"type": "column",
"value": "attribute_id"
},
{
"id": 1,
"type": "table",
"value": "attribute"
},
{
"id": 5,
"type": "table",
"value": "superhero"
},
{
"id": 9,
"type": "column",
"value": "hero_id"
},
{
"id": 3,
"type": "value",
"value": "Speed"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
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{
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},
{
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{
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"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": [
1
]
},
{
"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"
] |
14,786
|
works_cycles
|
bird:train.json:7287
|
Please list the reviewers who have given the highest rating for a medium class, women's product.
|
SELECT T1.ReviewerName FROM ProductReview AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Class = 'M' AND T2.Style = 'W' AND T1.Rating = 5
|
[
"Please",
"list",
"the",
"reviewers",
"who",
"have",
"given",
"the",
"highest",
"rating",
"for",
"a",
"medium",
"class",
",",
"women",
"'s",
"product",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "productreview"
},
{
"id": 0,
"type": "column",
"value": "reviewername"
},
{
"id": 3,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "table",
"value": "product"
},
{
"id": 8,
"type": "column",
"value": "rating"
},
{
"id": 4,
"type": "column",
"value": "class"
},
{
"id": 6,
"type": "column",
"value": "style"
},
{
"id": 5,
"type": "value",
"value": "M"
},
{
"id": 7,
"type": "value",
"value": "W"
},
{
"id": 9,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
17
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
9
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,787
|
world
|
bird:train.json:7906
|
List down the country names of countries that have a GNP lower than 1000 and have Dutch as their language.
|
SELECT T2.Name FROM CountryLanguage AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T2.GNP < 1000 AND T1.IsOfficial = 'T' AND T1.Language = 'Dutch'
|
[
"List",
"down",
"the",
"country",
"names",
"of",
"countries",
"that",
"have",
"a",
"GNP",
"lower",
"than",
"1000",
"and",
"have",
"Dutch",
"as",
"their",
"language",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "countrylanguage"
},
{
"id": 3,
"type": "column",
"value": "countrycode"
},
{
"id": 7,
"type": "column",
"value": "isofficial"
},
{
"id": 9,
"type": "column",
"value": "language"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 10,
"type": "value",
"value": "Dutch"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "value",
"value": "1000"
},
{
"id": 5,
"type": "column",
"value": "gnp"
},
{
"id": 8,
"type": "value",
"value": "T"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
19
]
},
{
"entity_id": 10,
"token_idxs": [
16
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
14,788
|
music_1
|
spider:train_spider.json:3589
|
What are the names of artists who are Male and are from UK?
|
SELECT artist_name FROM artist WHERE country = "UK" AND gender = "Male"
|
[
"What",
"are",
"the",
"names",
"of",
"artists",
"who",
"are",
"Male",
"and",
"are",
"from",
"UK",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "artist_name"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "artist"
},
{
"id": 4,
"type": "column",
"value": "gender"
},
{
"id": 5,
"type": "column",
"value": "Male"
},
{
"id": 3,
"type": "column",
"value": "UK"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,789
|
hockey
|
bird:train.json:7657
|
Did the tallest player got in the Hall of Fame? If yes, please list the year when he got in the Hall of Fame.
|
SELECT CASE WHEN T1.hofID IS NULL THEN 'NO' ELSE T2.year END FROM Master AS T1 LEFT JOIN HOF AS T2 ON T1.hofID = T2.hofID WHERE T1.height = ( SELECT MAX(height) FROM Master )
|
[
"Did",
"the",
"tallest",
"player",
"got",
"in",
"the",
"Hall",
"of",
"Fame",
"?",
"If",
"yes",
",",
"please",
"list",
"the",
"year",
"when",
"he",
"got",
"in",
"the",
"Hall",
"of",
"Fame",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "master"
},
{
"id": 2,
"type": "column",
"value": "height"
},
{
"id": 4,
"type": "column",
"value": "hofid"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 1,
"type": "table",
"value": "hof"
},
{
"id": 5,
"type": "value",
"value": "NO"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
24
]
},
{
"entity_id": 2,
"token_idxs": [
19,
20
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
14,790
|
codebase_community
|
bird:dev.json:678
|
Which post by Harvey Motulsky has the most views? Please give the id and title of this post.
|
SELECT T2.Id, T2.Title FROM users AS T1 INNER JOIN posts AS T2 ON T1.Id = T2.OwnerUserId WHERE T1.DisplayName = 'Harvey Motulsky' ORDER BY T2.ViewCount DESC LIMIT 1
|
[
"Which",
"post",
"by",
"Harvey",
"Motulsky",
"has",
"the",
"most",
"views",
"?",
"Please",
"give",
"the",
"i",
"d",
"and",
"title",
"of",
"this",
"post",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Harvey Motulsky"
},
{
"id": 4,
"type": "column",
"value": "displayname"
},
{
"id": 7,
"type": "column",
"value": "owneruserid"
},
{
"id": 6,
"type": "column",
"value": "viewcount"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "users"
},
{
"id": 3,
"type": "table",
"value": "posts"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13,
14
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
3,
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
14,792
|
flight_1
|
spider:train_spider.json:400
|
What are the numbers of the shortest flights?
|
SELECT flno FROM Flight ORDER BY distance ASC LIMIT 3
|
[
"What",
"are",
"the",
"numbers",
"of",
"the",
"shortest",
"flights",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "distance"
},
{
"id": 0,
"type": "table",
"value": "flight"
},
{
"id": 1,
"type": "column",
"value": "flno"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,793
|
icfp_1
|
spider:train_spider.json:2870
|
What is the name of the institution that "Matthias Blume" belongs to?
|
SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Matthias" AND t1.lname = "Blume"
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"institution",
"that",
"\"",
"Matthias",
"Blume",
"\"",
"belongs",
"to",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "authorship"
},
{
"id": 6,
"type": "column",
"value": "Matthias"
},
{
"id": 2,
"type": "table",
"value": "authors"
},
{
"id": 4,
"type": "column",
"value": "instid"
},
{
"id": 9,
"type": "column",
"value": "authid"
},
{
"id": 5,
"type": "column",
"value": "fname"
},
{
"id": 7,
"type": "column",
"value": "lname"
},
{
"id": 8,
"type": "column",
"value": "Blume"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "inst"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
14,794
|
trains
|
bird:train.json:726
|
Among the trains running west, how many trains have three-wheeled, jagged roof cars?
|
SELECT SUM(CASE WHEN T2.direction = 'west' THEN 1 ELSE 0 END)as count FROM cars AS T1 INNER JOIN trains AS T2 ON T1.train_id = T2.id WHERE T1.wheels = 3 AND T1.roof = 'jagged'
|
[
"Among",
"the",
"trains",
"running",
"west",
",",
"how",
"many",
"trains",
"have",
"three",
"-",
"wheeled",
",",
"jagged",
"roof",
"cars",
"?"
] |
[
{
"id": 10,
"type": "column",
"value": "direction"
},
{
"id": 2,
"type": "column",
"value": "train_id"
},
{
"id": 1,
"type": "table",
"value": "trains"
},
{
"id": 4,
"type": "column",
"value": "wheels"
},
{
"id": 7,
"type": "value",
"value": "jagged"
},
{
"id": 0,
"type": "table",
"value": "cars"
},
{
"id": 6,
"type": "column",
"value": "roof"
},
{
"id": 11,
"type": "value",
"value": "west"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "3"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"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": [
4
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"B-TABLE",
"O"
] |
14,795
|
works_cycles
|
bird:train.json:7214
|
What is the name of the territory assigned to the sales person with business id "277"?
|
SELECT T2.Name FROM SalesPerson AS T1 INNER JOIN SalesTerritory AS T2 ON T1.TerritoryID = T2.TerritoryID WHERE T1.BusinessEntityID = 277
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"territory",
"assigned",
"to",
"the",
"sales",
"person",
"with",
"business",
"i",
"d",
"\"",
"277",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "businessentityid"
},
{
"id": 2,
"type": "table",
"value": "salesterritory"
},
{
"id": 1,
"type": "table",
"value": "salesperson"
},
{
"id": 5,
"type": "column",
"value": "territoryid"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "277"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
10,
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"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",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
14,796
|
mondial_geo
|
bird:train.json:8245
|
Which country has the highest GDP?
|
SELECT T1.Name FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country ORDER BY T2.GDP DESC LIMIT 1
|
[
"Which",
"country",
"has",
"the",
"highest",
"GDP",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "economy"
},
{
"id": 5,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 3,
"type": "column",
"value": "gdp"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"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": [
1
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,797
|
online_exams
|
bird:test.json:218
|
Find the valid answer text that appeared most frequently.
|
SELECT Valid_Answer_Text FROM Valid_Answers GROUP BY Valid_Answer_Text ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Find",
"the",
"valid",
"answer",
"text",
"that",
"appeared",
"most",
"frequently",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "valid_answer_text"
},
{
"id": 0,
"type": "table",
"value": "valid_answers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
14,798
|
store_product
|
spider:train_spider.json:4914
|
Find all types of store and number of them.
|
SELECT TYPE , count(*) FROM store GROUP BY TYPE
|
[
"Find",
"all",
"types",
"of",
"store",
"and",
"number",
"of",
"them",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "store"
},
{
"id": 1,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
14,799
|
college_1
|
spider:train_spider.json:3237
|
Find the total credits of all classes offered by each department.
|
SELECT sum(T1.crs_credit) , T1.dept_code FROM course AS T1 JOIN CLASS AS T2 ON T1.crs_code = T2.crs_code GROUP BY T1.dept_code
|
[
"Find",
"the",
"total",
"credits",
"of",
"all",
"classes",
"offered",
"by",
"each",
"department",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "crs_credit"
},
{
"id": 0,
"type": "column",
"value": "dept_code"
},
{
"id": 4,
"type": "column",
"value": "crs_code"
},
{
"id": 1,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "table",
"value": "class"
}
] |
[
{
"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-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
14,800
|
student_club
|
bird:dev.json:1317
|
Among the students from the Student_Club who attended the event "Women's Soccer", how many of them want a T-shirt that's in medium size?
|
SELECT COUNT(T1.event_id) FROM event AS T1 INNER JOIN attendance AS T2 ON T1.event_id = T2.link_to_event INNER JOIN member AS T3 ON T2.link_to_member = T3.member_id WHERE T1.event_name = 'Women''s Soccer' AND T3.t_shirt_size = 'Medium'
|
[
"Among",
"the",
"students",
"from",
"the",
"Student_Club",
"who",
"attended",
"the",
"event",
"\"",
"Women",
"'s",
"Soccer",
"\"",
",",
"how",
"many",
"of",
"them",
"want",
"a",
"T",
"-",
"shirt",
"that",
"'s",
"in",
"medium",
"size",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "link_to_member"
},
{
"id": 7,
"type": "value",
"value": "Women's Soccer"
},
{
"id": 10,
"type": "column",
"value": "link_to_event"
},
{
"id": 8,
"type": "column",
"value": "t_shirt_size"
},
{
"id": 3,
"type": "table",
"value": "attendance"
},
{
"id": 6,
"type": "column",
"value": "event_name"
},
{
"id": 5,
"type": "column",
"value": "member_id"
},
{
"id": 1,
"type": "column",
"value": "event_id"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 9,
"type": "value",
"value": "Medium"
},
{
"id": 2,
"type": "table",
"value": "event"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"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": [
11,
12,
13
]
},
{
"entity_id": 8,
"token_idxs": [
22,
23,
24
]
},
{
"entity_id": 9,
"token_idxs": [
28
]
},
{
"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",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
14,801
|
school_bus
|
spider:train_spider.json:6358
|
Show the types of schools that have two schools.
|
SELECT TYPE FROM school GROUP BY TYPE HAVING count(*) = 2
|
[
"Show",
"the",
"types",
"of",
"schools",
"that",
"have",
"two",
"schools",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "school"
},
{
"id": 1,
"type": "column",
"value": "type"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,802
|
cre_Doc_and_collections
|
bird:test.json:687
|
What is the description of collection named Best?
|
SELECT Collection_Description FROM Collections WHERE Collection_Name = "Best";
|
[
"What",
"is",
"the",
"description",
"of",
"collection",
"named",
"Best",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "collection_description"
},
{
"id": 2,
"type": "column",
"value": "collection_name"
},
{
"id": 0,
"type": "table",
"value": "collections"
},
{
"id": 3,
"type": "column",
"value": "Best"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O"
] |
14,803
|
ship_1
|
spider:train_spider.json:6246
|
Find the name, type, and flag of the ship that is built in the most recent year.
|
SELECT name , TYPE , flag FROM ship ORDER BY built_year DESC LIMIT 1
|
[
"Find",
"the",
"name",
",",
"type",
",",
"and",
"flag",
"of",
"the",
"ship",
"that",
"is",
"built",
"in",
"the",
"most",
"recent",
"year",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "built_year"
},
{
"id": 0,
"type": "table",
"value": "ship"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "type"
},
{
"id": 3,
"type": "column",
"value": "flag"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,804
|
works_cycles
|
bird:train.json:7274
|
What is the average lead time of product ID 843? Calculate for its profit on net and indicate the full location to which the vendor is located.
|
SELECT T1.AverageLeadTime, T1.LastReceiptCost - T1.StandardPrice, T4.AddressLine1, T4.AddressLine2 , T4.City, T4.PostalCode FROM ProductVendor AS T1 INNER JOIN Vendor AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN BusinessEntityAddress AS T3 ON T1.BusinessEntityID = T3.BusinessEntityID INNER JOIN Address AS T4 ON T3.AddressID = T4.AddressID WHERE T1.ProductID = 843
|
[
"What",
"is",
"the",
"average",
"lead",
"time",
"of",
"product",
"ID",
"843",
"?",
"Calculate",
"for",
"its",
"profit",
"on",
"net",
"and",
"indicate",
"the",
"full",
"location",
"to",
"which",
"the",
"vendor",
"is",
"located",
"."
] |
[
{
"id": 10,
"type": "table",
"value": "businessentityaddress"
},
{
"id": 14,
"type": "column",
"value": "businessentityid"
},
{
"id": 0,
"type": "column",
"value": "averageleadtime"
},
{
"id": 8,
"type": "column",
"value": "lastreceiptcost"
},
{
"id": 9,
"type": "column",
"value": "standardprice"
},
{
"id": 12,
"type": "table",
"value": "productvendor"
},
{
"id": 1,
"type": "column",
"value": "addressline1"
},
{
"id": 2,
"type": "column",
"value": "addressline2"
},
{
"id": 4,
"type": "column",
"value": "postalcode"
},
{
"id": 6,
"type": "column",
"value": "productid"
},
{
"id": 11,
"type": "column",
"value": "addressid"
},
{
"id": 5,
"type": "table",
"value": "address"
},
{
"id": 13,
"type": "table",
"value": "vendor"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 7,
"type": "value",
"value": "843"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4,
5
]
},
{
"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": [
7,
8
]
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"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": [
25
]
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
14,805
|
store_1
|
spider:train_spider.json:631
|
List the name of tracks belongs to genre Rock or media type is MPEG audio file.
|
SELECT T2.name FROM genres AS T1 JOIN tracks AS T2 ON T1.id = T2.genre_id JOIN media_types AS T3 ON T3.id = T2.media_type_id WHERE T1.name = "Rock" OR T3.name = "MPEG audio file";
|
[
"List",
"the",
"name",
"of",
"tracks",
"belongs",
"to",
"genre",
"Rock",
"or",
"media",
"type",
"is",
"MPEG",
"audio",
"file",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "MPEG audio file"
},
{
"id": 5,
"type": "column",
"value": "media_type_id"
},
{
"id": 1,
"type": "table",
"value": "media_types"
},
{
"id": 8,
"type": "column",
"value": "genre_id"
},
{
"id": 2,
"type": "table",
"value": "genres"
},
{
"id": 3,
"type": "table",
"value": "tracks"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "Rock"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
10,
11
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
14,806
|
synthea
|
bird:train.json:1389
|
How many patients are allergic to eggs?
|
SELECT COUNT(PATIENT) FROM allergies WHERE DESCRIPTION = 'Allergy to eggs'
|
[
"How",
"many",
"patients",
"are",
"allergic",
"to",
"eggs",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "Allergy to eggs"
},
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "table",
"value": "allergies"
},
{
"id": 3,
"type": "column",
"value": "patient"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O"
] |
14,807
|
authors
|
bird:train.json:3564
|
How many authors have written paper "145 GROWTH HORMONE RECEPTORS AND THE ONSET OF HYPERINSULINEMIA IN THE OBESE ZUCKER RAT: "?
|
SELECT COUNT(DISTINCT T2.Name) FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Title = '145 GROWTH HORMONE RECEPTORS AND THE ONSET OF HYPERINSULINEMIA IN THE OBESE ZUCKER RAT: '
|
[
"How",
"many",
"authors",
"have",
"written",
"paper",
"\"",
"145",
"GROWTH",
"HORMONE",
"RECEPTORS",
"AND",
"THE",
"ONSET",
"OF",
"HYPERINSULINEMIA",
"IN",
"THE",
"OBESE",
"ZUCKER",
"RAT",
":",
"\"",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "145 GROWTH HORMONE RECEPTORS AND THE ONSET OF HYPERINSULINEMIA IN THE OBESE ZUCKER RAT: "
},
{
"id": 1,
"type": "table",
"value": "paperauthor"
},
{
"id": 6,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "table",
"value": "paper"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"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",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
14,808
|
bike_share_1
|
bird:train.json:9076
|
What is the total number of bikes that can be hold in Redwood City before 2014.
|
SELECT SUM(CASE WHEN city = 'Redwood City' AND SUBSTR(installation_date, -4) < '2014' THEN dock_count ELSE 0 END) NUM FROM station
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"bikes",
"that",
"can",
"be",
"hold",
"in",
"Redwood",
"City",
"before",
"2014",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "installation_date"
},
{
"id": 4,
"type": "value",
"value": "Redwood City"
},
{
"id": 2,
"type": "column",
"value": "dock_count"
},
{
"id": 0,
"type": "table",
"value": "station"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "2014"
},
{
"id": 7,
"type": "value",
"value": "-4"
},
{
"id": 1,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
14,810
|
cre_Doc_Workflow
|
bird:test.json:2033
|
What is the process name for the next process of the process with id 9?
|
SELECT process_name FROM Business_processes WHERE process_id = (SELECT next_process_id FROM Business_processes WHERE process_id = 9)
|
[
"What",
"is",
"the",
"process",
"name",
"for",
"the",
"next",
"process",
"of",
"the",
"process",
"with",
"i",
"d",
"9",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "business_processes"
},
{
"id": 3,
"type": "column",
"value": "next_process_id"
},
{
"id": 1,
"type": "column",
"value": "process_name"
},
{
"id": 2,
"type": "column",
"value": "process_id"
},
{
"id": 4,
"type": "value",
"value": "9"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
14,811
|
music_2
|
spider:train_spider.json:5258
|
Find the first name of the band mate that has performed in most songs.
|
SELECT t2.firstname FROM Performance AS t1 JOIN Band AS t2 ON t1.bandmate = t2.id JOIN Songs AS T3 ON T3.SongId = T1.SongId GROUP BY firstname ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"first",
"name",
"of",
"the",
"band",
"mate",
"that",
"has",
"performed",
"in",
"most",
"songs",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "performance"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 5,
"type": "column",
"value": "bandmate"
},
{
"id": 4,
"type": "column",
"value": "songid"
},
{
"id": 1,
"type": "table",
"value": "songs"
},
{
"id": 3,
"type": "table",
"value": "band"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
0
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O"
] |
14,812
|
hospital_1
|
spider:train_spider.json:3937
|
Tell me the distinct block codes where some rooms are available.
|
SELECT DISTINCT blockcode FROM room WHERE unavailable = 0
|
[
"Tell",
"me",
"the",
"distinct",
"block",
"codes",
"where",
"some",
"rooms",
"are",
"available",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "unavailable"
},
{
"id": 1,
"type": "column",
"value": "blockcode"
},
{
"id": 0,
"type": "table",
"value": "room"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O"
] |
14,813
|
company_office
|
spider:train_spider.json:4550
|
List the name and assets of each company in ascending order of company name.
|
SELECT name , Assets_billion FROM Companies ORDER BY name ASC
|
[
"List",
"the",
"name",
"and",
"assets",
"of",
"each",
"company",
"in",
"ascending",
"order",
"of",
"company",
"name",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "assets_billion"
},
{
"id": 0,
"type": "table",
"value": "companies"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
14,814
|
music_1
|
spider:train_spider.json:3599
|
What are the maximum and minimum resolution of songs whose duration is 3 minutes?
|
SELECT max(T2.resolution) , min(T2.resolution) FROM files AS T1 JOIN song AS T2 ON T1.f_id = T2.f_id WHERE T1.duration LIKE "3:%"
|
[
"What",
"are",
"the",
"maximum",
"and",
"minimum",
"resolution",
"of",
"songs",
"whose",
"duration",
"is",
"3",
"minutes",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "resolution"
},
{
"id": 2,
"type": "column",
"value": "duration"
},
{
"id": 0,
"type": "table",
"value": "files"
},
{
"id": 1,
"type": "table",
"value": "song"
},
{
"id": 5,
"type": "column",
"value": "f_id"
},
{
"id": 3,
"type": "column",
"value": "3:%"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
14,815
|
soccer_2016
|
bird:train.json:1868
|
Provide the names and birthdates of players who have left-arm fast skills.
|
SELECT T1.Player_Name, T1.DOB FROM Player AS T1 INNER JOIN Bowling_Style AS T2 ON T2.Bowling_Id = T1.Bowling_skill WHERE T2.Bowling_skill = 'Left-arm fast'
|
[
"Provide",
"the",
"names",
"and",
"birthdates",
"of",
"players",
"who",
"have",
"left",
"-",
"arm",
"fast",
"skills",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "bowling_style"
},
{
"id": 4,
"type": "column",
"value": "bowling_skill"
},
{
"id": 5,
"type": "value",
"value": "Left-arm fast"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 6,
"type": "column",
"value": "bowling_id"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 1,
"type": "column",
"value": "dob"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9,
10,
11,
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
14,816
|
sales_in_weather
|
bird:train.json:8202
|
How many stations were able to sell item 5 on January 2014?
|
SELECT COUNT(DISTINCT T2.station_nbr) AS number FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr WHERE SUBSTR(`date`, 1, 7) = '2014-01' AND item_nbr = 5
|
[
"How",
"many",
"stations",
"were",
"able",
"to",
"sell",
"item",
"5",
"on",
"January",
"2014",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "sales_in_weather"
},
{
"id": 2,
"type": "column",
"value": "station_nbr"
},
{
"id": 3,
"type": "column",
"value": "store_nbr"
},
{
"id": 1,
"type": "table",
"value": "relation"
},
{
"id": 5,
"type": "column",
"value": "item_nbr"
},
{
"id": 4,
"type": "value",
"value": "2014-01"
},
{
"id": 7,
"type": "column",
"value": "date"
},
{
"id": 6,
"type": "value",
"value": "5"
},
{
"id": 8,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "7"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"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",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
14,817
|
social_media
|
bird:train.json:806
|
Give the name of the city of the user who tweeted `One of our favorite stories is @FINRA_News's move to the cloud with AWS Enterprise Support! https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a`.
|
SELECT T2.City FROM twitter AS T1 INNER JOIN location AS T2 ON T2.LocationID = T1.LocationID WHERE T1.text = 'One of our favorite stories is @FINRA_News''s move to the cloud with AWS Enterprise Support! https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a'
|
[
"Give",
"the",
"name",
"of",
"the",
"city",
"of",
"the",
"user",
"who",
"tweeted",
"`",
"One",
"of",
"our",
"favorite",
"stories",
"is",
"@FINRA_News",
"'s",
"move",
"to",
"the",
"cloud",
"with",
"AWS",
"Enterprise",
"Support",
"!",
"https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a",
"`",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "One of our favorite stories is @FINRA_News's move to the cloud with AWS Enterprise Support! https://amp.twimg.com/v/991837f1-4815-4edc-a88f-e68ded09a02a"
},
{
"id": 5,
"type": "column",
"value": "locationid"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 1,
"type": "table",
"value": "twitter"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 3,
"type": "column",
"value": "text"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"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",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
14,818
|
legislator
|
bird:train.json:4805
|
What is the birthday of Amy Klobuchar?
|
SELECT birthday_bio FROM current WHERE first_name = 'Amy' AND last_name = 'Klobuchar'
|
[
"What",
"is",
"the",
"birthday",
"of",
"Amy",
"Klobuchar",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "birthday_bio"
},
{
"id": 2,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "value",
"value": "Klobuchar"
},
{
"id": 0,
"type": "table",
"value": "current"
},
{
"id": 3,
"type": "value",
"value": "Amy"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
14,819
|
aan_1
|
bird:test.json:984
|
What are the titles and paper ids co-authored by Mckeown, Kathleen and Rambow, Owen?
|
SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T2.author_id = T3.author_id WHERE T3.name LIKE "%Mckeown , Kathleen%" INTERSECT SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T2.author_id = T3.author_id WHERE T3.name LIKE "%Rambow , Owen%"
|
[
"What",
"are",
"the",
"titles",
"and",
"paper",
"ids",
"co",
"-",
"authored",
"by",
"Mckeown",
",",
"Kathleen",
"and",
"Rambow",
",",
"Owen",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "%Mckeown , Kathleen%"
},
{
"id": 5,
"type": "column",
"value": "%Rambow , Owen%"
},
{
"id": 7,
"type": "table",
"value": "author_list"
},
{
"id": 8,
"type": "column",
"value": "author_id"
},
{
"id": 1,
"type": "column",
"value": "paper_id"
},
{
"id": 2,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12,
13
]
},
{
"entity_id": 5,
"token_idxs": [
15,
16,
17
]
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
14,820
|
soccer_1
|
spider:train_spider.json:1298
|
What are the names of players who have the best dribbling?
|
SELECT DISTINCT T1.player_name FROM Player AS T1 JOIN Player_Attributes AS T2 ON T1.player_api_id = T2.player_api_id WHERE T2.dribbling = ( SELECT max(overall_rating) FROM Player_Attributes)
|
[
"What",
"are",
"the",
"names",
"of",
"players",
"who",
"have",
"the",
"best",
"dribbling",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "player_attributes"
},
{
"id": 5,
"type": "column",
"value": "overall_rating"
},
{
"id": 4,
"type": "column",
"value": "player_api_id"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 3,
"type": "column",
"value": "dribbling"
},
{
"id": 1,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,821
|
car_road_race
|
bird:test.json:1314
|
How many races are there?
|
SELECT count(*) FROM race
|
[
"How",
"many",
"races",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "race"
}
] |
[
{
"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"
] |
14,822
|
advertising_agencies
|
bird:test.json:2105
|
Show all invoice ids and statuses without a payment.
|
SELECT invoice_id , invoice_status FROM Invoices EXCEPT SELECT T1.invoice_id , T1.invoice_status FROM Invoices AS T1 JOIN Payments AS T2 ON T1.invoice_id = T2.invoice_id
|
[
"Show",
"all",
"invoice",
"ids",
"and",
"statuses",
"without",
"a",
"payment",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "invoice_status"
},
{
"id": 1,
"type": "column",
"value": "invoice_id"
},
{
"id": 0,
"type": "table",
"value": "invoices"
},
{
"id": 3,
"type": "table",
"value": "payments"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
14,823
|
formula_1
|
bird:dev.json:998
|
In terms of number of points acquired, how many victories did the driver who ranked 91st acquired?
|
SELECT SUM(CASE WHEN points = 91 THEN wins ELSE 0 END) FROM driverStandings
|
[
"In",
"terms",
"of",
"number",
"of",
"points",
"acquired",
",",
"how",
"many",
"victories",
"did",
"the",
"driver",
"who",
"ranked",
"91st",
"acquired",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "driverstandings"
},
{
"id": 3,
"type": "column",
"value": "points"
},
{
"id": 2,
"type": "column",
"value": "wins"
},
{
"id": 4,
"type": "value",
"value": "91"
},
{
"id": 1,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
0
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"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": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
14,825
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4190
|
List all role codes, role names, and role descriptions.
|
SELECT role_code , role_name , role_description FROM ROLES
|
[
"List",
"all",
"role",
"codes",
",",
"role",
"names",
",",
"and",
"role",
"descriptions",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "role_description"
},
{
"id": 1,
"type": "column",
"value": "role_code"
},
{
"id": 2,
"type": "column",
"value": "role_name"
},
{
"id": 0,
"type": "table",
"value": "roles"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
14,826
|
student_loan
|
bird:train.json:4494
|
Among the students who have been absent for four months, provide any five students' names and enlisted organizations.
|
SELECT T2.name, T2.organ FROM longest_absense_from_school AS T1 INNER JOIN enlist AS T2 ON T2.name = T1.name WHERE T1.month = 4 LIMIT 5
|
[
"Among",
"the",
"students",
"who",
"have",
"been",
"absent",
"for",
"four",
"months",
",",
"provide",
"any",
"five",
"students",
"'",
"names",
"and",
"enlisted",
"organizations",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 3,
"type": "table",
"value": "enlist"
},
{
"id": 1,
"type": "column",
"value": "organ"
},
{
"id": 4,
"type": "column",
"value": "month"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O"
] |
14,827
|
regional_sales
|
bird:train.json:2632
|
From 2018 to 2020, which year did the George Lewis group have the highest number of orders?
|
SELECT SUBSTR(T1.OrderDate, -2, 2) FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.`Sales Team` = 'George Lewis' GROUP BY SUBSTR(T1.OrderDate, -2, 2) ORDER BY COUNT(T1.OrderNumber) DESC LIMIT 1
|
[
"From",
"2018",
"to",
"2020",
",",
"which",
"year",
"did",
"the",
"George",
"Lewis",
"group",
"have",
"the",
"highest",
"number",
"of",
"orders",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 3,
"type": "value",
"value": "George Lewis"
},
{
"id": 8,
"type": "column",
"value": "_salesteamid"
},
{
"id": 7,
"type": "column",
"value": "salesteamid"
},
{
"id": 9,
"type": "column",
"value": "ordernumber"
},
{
"id": 1,
"type": "table",
"value": "Sales Team"
},
{
"id": 2,
"type": "column",
"value": "Sales Team"
},
{
"id": 4,
"type": "column",
"value": "orderdate"
},
{
"id": 5,
"type": "value",
"value": "-2"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
15
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
14,828
|
college_1
|
spider:train_spider.json:3324
|
What are the different first names and highest degree attained for professors teaching in the Computer Information Systems department?
|
SELECT DISTINCT T2.emp_fname , T3.prof_high_degree FROM CLASS AS T1 JOIN employee AS T2 ON T1.prof_num = T2.emp_num JOIN professor AS T3 ON T2.emp_num = T3.emp_num JOIN department AS T4 ON T4.dept_code = T3.dept_code WHERE T4.dept_name = 'Computer Info. Systems'
|
[
"What",
"are",
"the",
"different",
"first",
"names",
"and",
"highest",
"degree",
"attained",
"for",
"professors",
"teaching",
"in",
"the",
"Computer",
"Information",
"Systems",
"department",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Computer Info. Systems"
},
{
"id": 1,
"type": "column",
"value": "prof_high_degree"
},
{
"id": 2,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "emp_fname"
},
{
"id": 3,
"type": "column",
"value": "dept_name"
},
{
"id": 5,
"type": "table",
"value": "professor"
},
{
"id": 6,
"type": "column",
"value": "dept_code"
},
{
"id": 8,
"type": "table",
"value": "employee"
},
{
"id": 10,
"type": "column",
"value": "prof_num"
},
{
"id": 9,
"type": "column",
"value": "emp_num"
},
{
"id": 7,
"type": "table",
"value": "class"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7,
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": [
15,
16,
17
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
14,829
|
world
|
bird:train.json:7832
|
Among the languages used in Baltic Countries, provide the languages which are used by over 80%.
|
SELECT T2.Language FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Region = 'Baltic Countries' AND T2.Percentage > 80
|
[
"Among",
"the",
"languages",
"used",
"in",
"Baltic",
"Countries",
",",
"provide",
"the",
"languages",
"which",
"are",
"used",
"by",
"over",
"80",
"%",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "Baltic Countries"
},
{
"id": 2,
"type": "table",
"value": "countrylanguage"
},
{
"id": 4,
"type": "column",
"value": "countrycode"
},
{
"id": 7,
"type": "column",
"value": "percentage"
},
{
"id": 0,
"type": "column",
"value": "language"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "region"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 8,
"type": "value",
"value": "80"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
16
]
},
{
"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-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
14,830
|
college_1
|
spider:train_spider.json:3307
|
Find the first name and office of the professor who is in the history department and has a Ph.D. degree.
|
SELECT T1.emp_fname , T2.prof_office FROM employee AS T1 JOIN professor AS T2 ON T1.emp_num = T2.emp_num JOIN department AS T3 ON T3.dept_code = T2.dept_code WHERE T3.dept_name = 'History' AND T2.prof_high_degree = 'Ph.D.'
|
[
"Find",
"the",
"first",
"name",
"and",
"office",
"of",
"the",
"professor",
"who",
"is",
"in",
"the",
"history",
"department",
"and",
"has",
"a",
"Ph.D.",
"degree",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "prof_high_degree"
},
{
"id": 1,
"type": "column",
"value": "prof_office"
},
{
"id": 2,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "emp_fname"
},
{
"id": 4,
"type": "table",
"value": "professor"
},
{
"id": 5,
"type": "column",
"value": "dept_code"
},
{
"id": 6,
"type": "column",
"value": "dept_name"
},
{
"id": 3,
"type": "table",
"value": "employee"
},
{
"id": 7,
"type": "value",
"value": "History"
},
{
"id": 10,
"type": "column",
"value": "emp_num"
},
{
"id": 9,
"type": "value",
"value": "Ph.D."
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
18
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
14,831
|
movie_platform
|
bird:train.json:145
|
List all the titles created by user who was a subsriber when he created the list and have less than 50 movies in the list.
|
SELECT DISTINCT T2.list_title FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_movie_number < 50 AND T1.user_subscriber = 1
|
[
"List",
"all",
"the",
"titles",
"created",
"by",
"user",
"who",
"was",
"a",
"subsriber",
"when",
"he",
"created",
"the",
"list",
"and",
"have",
"less",
"than",
"50",
"movies",
"in",
"the",
"list",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "list_movie_number"
},
{
"id": 6,
"type": "column",
"value": "user_subscriber"
},
{
"id": 1,
"type": "table",
"value": "lists_users"
},
{
"id": 0,
"type": "column",
"value": "list_title"
},
{
"id": 3,
"type": "column",
"value": "list_id"
},
{
"id": 2,
"type": "table",
"value": "lists"
},
{
"id": 5,
"type": "value",
"value": "50"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0,
1,
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
14,832
|
soccer_2016
|
bird:train.json:2033
|
What is the average of Indian players that were born between 1975 and 1985 among all players?
|
SELECT CAST(SUM(CASE WHEN T2.Country_Name = 'India' THEN 1 ELSE 0 END) AS REAL) / COUNT(T1.Player_Id) FROM Player AS T1 INNER JOIN Country AS T2 ON T1.Country_Name = T2.Country_ID WHERE strftime('%Y', T1.DOB) BETWEEN '1975' AND '1985'
|
[
"What",
"is",
"the",
"average",
"of",
"Indian",
"players",
"that",
"were",
"born",
"between",
"1975",
"and",
"1985",
"among",
"all",
"players",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "country_name"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 8,
"type": "column",
"value": "player_id"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 11,
"type": "value",
"value": "India"
},
{
"id": 2,
"type": "value",
"value": "1975"
},
{
"id": 3,
"type": "value",
"value": "1985"
},
{
"id": 7,
"type": "column",
"value": "dob"
},
{
"id": 6,
"type": "value",
"value": "%Y"
},
{
"id": 9,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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": [
5
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
14,835
|
music_tracker
|
bird:train.json:2050
|
Name all the release titles of the "ep's" under the alternative tag.
|
SELECT T1.groupName FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T2.tag LIKE 'alternative' AND T1.releaseType = 'ep'
|
[
"Name",
"all",
"the",
"release",
"titles",
"of",
"the",
"\"",
"ep",
"'s",
"\"",
"under",
"the",
"alternative",
"tag",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "alternative"
},
{
"id": 6,
"type": "column",
"value": "releasetype"
},
{
"id": 0,
"type": "column",
"value": "groupname"
},
{
"id": 1,
"type": "table",
"value": "torrents"
},
{
"id": 2,
"type": "table",
"value": "tags"
},
{
"id": 4,
"type": "column",
"value": "tag"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "ep"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
14,836
|
student_club
|
bird:dev.json:1388
|
Which students manage to generate the highest income. State his/her full name along with the income source.
|
SELECT T1.first_name, T1.last_name, T2.source FROM member AS T1 INNER JOIN income AS T2 ON T1.member_id = T2.link_to_member GROUP BY T1.first_name, T1.last_name, T2.source ORDER BY SUM(T2.amount) DESC LIMIT 1
|
[
"Which",
"students",
"manage",
"to",
"generate",
"the",
"highest",
"income",
".",
"State",
"his",
"/",
"her",
"full",
"name",
"along",
"with",
"the",
"income",
"source",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "link_to_member"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "member_id"
},
{
"id": 2,
"type": "column",
"value": "source"
},
{
"id": 3,
"type": "table",
"value": "member"
},
{
"id": 4,
"type": "table",
"value": "income"
},
{
"id": 7,
"type": "column",
"value": "amount"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
14,837
|
epinions_1
|
spider:train_spider.json:1714
|
Find the name of the target user with the lowest trust score.
|
SELECT T1.name FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.target_u_id ORDER BY trust LIMIT 1
|
[
"Find",
"the",
"name",
"of",
"the",
"target",
"user",
"with",
"the",
"lowest",
"trust",
"score",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "target_u_id"
},
{
"id": 1,
"type": "table",
"value": "useracct"
},
{
"id": 2,
"type": "table",
"value": "trust"
},
{
"id": 3,
"type": "column",
"value": "trust"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "u_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
14,838
|
video_games
|
bird:train.json:3430
|
What are the three largest numbers of games sold?
|
SELECT T.game_platform_id, SUM(T.num_sales) * 100000 FROM region_sales AS T GROUP BY game_platform_id ORDER BY SUM(T.num_sales) * 100000 DESC LIMIT 3
|
[
"What",
"are",
"the",
"three",
"largest",
"numbers",
"of",
"games",
"sold",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "game_platform_id"
},
{
"id": 0,
"type": "table",
"value": "region_sales"
},
{
"id": 3,
"type": "column",
"value": "num_sales"
},
{
"id": 2,
"type": "value",
"value": "100000"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"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": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
14,839
|
headphone_store
|
bird:test.json:925
|
Which headphone class does have more than two headphones?
|
SELECT CLASS FROM headphone GROUP BY CLASS HAVING count(*) > 2
|
[
"Which",
"headphone",
"class",
"does",
"have",
"more",
"than",
"two",
"headphones",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "headphone"
},
{
"id": 1,
"type": "column",
"value": "class"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,840
|
works_cycles
|
bird:train.json:7069
|
What is the first name of the male employee who has a western name style?
|
SELECT T2.FirstName FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T2.NameStyle = 0 AND T1.Gender = 'M'
|
[
"What",
"is",
"the",
"first",
"name",
"of",
"the",
"male",
"employee",
"who",
"has",
"a",
"western",
"name",
"style",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "businessentityid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 4,
"type": "column",
"value": "namestyle"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 6,
"type": "column",
"value": "gender"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
14,841
|
simpson_episodes
|
bird:train.json:4361
|
Among the people in Animation Department, who are credited for additional time in the episode titled by "How the Test Was Won"?
|
SELECT T2.person FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'How the Test Was Won' AND T2.role = 'additional timer' AND T2.credited = 'true' AND T2.category = 'Animation Department';
|
[
"Among",
"the",
"people",
"in",
"Animation",
"Department",
",",
"who",
"are",
"credited",
"for",
"additional",
"time",
"in",
"the",
"episode",
"titled",
"by",
"\"",
"How",
"the",
"Test",
"Was",
"Won",
"\"",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "How the Test Was Won"
},
{
"id": 11,
"type": "value",
"value": "Animation Department"
},
{
"id": 7,
"type": "value",
"value": "additional timer"
},
{
"id": 3,
"type": "column",
"value": "episode_id"
},
{
"id": 8,
"type": "column",
"value": "credited"
},
{
"id": 10,
"type": "column",
"value": "category"
},
{
"id": 1,
"type": "table",
"value": "episode"
},
{
"id": 0,
"type": "column",
"value": "person"
},
{
"id": 2,
"type": "table",
"value": "credit"
},
{
"id": 4,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "column",
"value": "role"
},
{
"id": 9,
"type": "value",
"value": "true"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
19,
20,
21,
22,
23
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
11,
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
4,
5
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
14,842
|
thrombosis_prediction
|
bird:dev.json:1188
|
How many female patients born in 1964 were admitted to the hospital? List them by ID.
|
SELECT ID FROM Patient WHERE STRFTIME('%Y', Birthday) = '1964' AND SEX = 'F' AND Admission = '+'
|
[
"How",
"many",
"female",
"patients",
"born",
"in",
"1964",
"were",
"admitted",
"to",
"the",
"hospital",
"?",
"List",
"them",
"by",
"ID",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "admission"
},
{
"id": 8,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 2,
"type": "value",
"value": "1964"
},
{
"id": 3,
"type": "column",
"value": "sex"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "%Y"
},
{
"id": 4,
"type": "value",
"value": "F"
},
{
"id": 6,
"type": "value",
"value": "+"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,843
|
online_exams
|
bird:test.json:193
|
How many exams are there?
|
SELECT count(*) FROM Exams
|
[
"How",
"many",
"exams",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "exams"
}
] |
[
{
"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"
] |
14,844
|
retail_complains
|
bird:train.json:271
|
What is the percentage of the complaint calls from Mr Mason Javen Lopez has got the consent provided by the customer?
|
SELECT CAST(SUM(CASE WHEN T2.`Consumer consent provided?` = 'Consent provided' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.`Consumer consent provided?`) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.sex = 'Male' AND T1.first = 'Mason' AND T1.middle = 'Javen' AND T1.last = 'Lopez'
|
[
"What",
"is",
"the",
"percentage",
"of",
"the",
"complaint",
"calls",
"from",
"Mr",
"Mason",
"Javen",
"Lopez",
"has",
"got",
"the",
"consent",
"provided",
"by",
"the",
"customer",
"?"
] |
[
{
"id": 12,
"type": "column",
"value": "Consumer consent provided?"
},
{
"id": 15,
"type": "value",
"value": "Consent provided"
},
{
"id": 2,
"type": "column",
"value": "client_id"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "table",
"value": "events"
},
{
"id": 7,
"type": "column",
"value": "middle"
},
{
"id": 5,
"type": "column",
"value": "first"
},
{
"id": 6,
"type": "value",
"value": "Mason"
},
{
"id": 8,
"type": "value",
"value": "Javen"
},
{
"id": 10,
"type": "value",
"value": "Lopez"
},
{
"id": 4,
"type": "value",
"value": "Male"
},
{
"id": 9,
"type": "column",
"value": "last"
},
{
"id": 3,
"type": "column",
"value": "sex"
},
{
"id": 11,
"type": "value",
"value": "100"
},
{
"id": 13,
"type": "value",
"value": "0"
},
{
"id": 14,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
12
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
15
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": [
16,
17
]
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
14,845
|
gas_company
|
spider:train_spider.json:2022
|
What are the headquarters without companies that are in the banking industry?
|
SELECT headquarters FROM company EXCEPT SELECT headquarters FROM company WHERE main_industry = 'Banking'
|
[
"What",
"are",
"the",
"headquarters",
"without",
"companies",
"that",
"are",
"in",
"the",
"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": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
14,846
|
mondial_geo
|
bird:train.json:8436
|
Which two nations are separated from one another by the longest border? Please include the entire names of the nations in your answer.
|
SELECT Country1, Country2 FROM borders ORDER BY Length DESC LIMIT 1
|
[
"Which",
"two",
"nations",
"are",
"separated",
"from",
"one",
"another",
"by",
"the",
"longest",
"border",
"?",
"Please",
"include",
"the",
"entire",
"names",
"of",
"the",
"nations",
"in",
"your",
"answer",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "country1"
},
{
"id": 2,
"type": "column",
"value": "country2"
},
{
"id": 0,
"type": "table",
"value": "borders"
},
{
"id": 3,
"type": "column",
"value": "length"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,847
|
cre_Students_Information_Systems
|
bird:test.json:454
|
What are the personal details and the address type descriptions of each student?
|
SELECT DISTINCT T1.student_details , T3.address_type_description FROM Students AS T1 JOIN Students_Addresses AS T2 ON T1.student_id = T2.student_id JOIN Ref_Address_Types AS T3 ON T2.address_type_code = T3.address_type_code
|
[
"What",
"are",
"the",
"personal",
"details",
"and",
"the",
"address",
"type",
"descriptions",
"of",
"each",
"student",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "address_type_description"
},
{
"id": 4,
"type": "table",
"value": "students_addresses"
},
{
"id": 2,
"type": "table",
"value": "ref_address_types"
},
{
"id": 5,
"type": "column",
"value": "address_type_code"
},
{
"id": 0,
"type": "column",
"value": "student_details"
},
{
"id": 6,
"type": "column",
"value": "student_id"
},
{
"id": 3,
"type": "table",
"value": "students"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
7,
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
14,848
|
college_2
|
spider:train_spider.json:1354
|
Find the department name of the instructor whose name contains 'Soisalon'.
|
SELECT dept_name FROM instructor WHERE name LIKE '%Soisalon%'
|
[
"Find",
"the",
"department",
"name",
"of",
"the",
"instructor",
"whose",
"name",
"contains",
"'",
"Soisalon",
"'",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "instructor"
},
{
"id": 3,
"type": "value",
"value": "%Soisalon%"
},
{
"id": 1,
"type": "column",
"value": "dept_name"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
14,849
|
book_press
|
bird:test.json:1975
|
What are the names of the publishers that made more than 15 billion profits each year or 1 billion each month?
|
SELECT name FROM press WHERE Year_Profits_billion > 15 OR Month_Profits_billion > 1
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"publishers",
"that",
"made",
"more",
"than",
"15",
"billion",
"profits",
"each",
"year",
"or",
"1",
"billion",
"each",
"month",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "month_profits_billion"
},
{
"id": 2,
"type": "column",
"value": "year_profits_billion"
},
{
"id": 0,
"type": "table",
"value": "press"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "15"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
15,
16,
18
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
14,850
|
bike_share_1
|
bird:train.json:9005
|
What is the longest trip duration that started and ended August 29, 2013?
|
SELECT MAX(duration) FROM trip WHERE start_date LIKE '8/29/2013%' AND end_date LIKE '8/29/2013%'
|
[
"What",
"is",
"the",
"longest",
"trip",
"duration",
"that",
"started",
"and",
"ended",
"August",
"29",
",",
"2013",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "start_date"
},
{
"id": 3,
"type": "value",
"value": "8/29/2013%"
},
{
"id": 1,
"type": "column",
"value": "duration"
},
{
"id": 4,
"type": "column",
"value": "end_date"
},
{
"id": 0,
"type": "table",
"value": "trip"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12,
13
]
},
{
"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-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
14,851
|
movie_2
|
bird:test.json:1822
|
What are the names of the movie theaters that are playing 'G' or 'PG' rated movies?
|
SELECT title FROM movies WHERE rating = 'G' OR rating = 'PG'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"movie",
"theaters",
"that",
"are",
"playing",
"'",
"G",
"'",
"or",
"'",
"PG",
"'",
"rated",
"movies",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "value",
"value": "PG"
},
{
"id": 3,
"type": "value",
"value": "G"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
14,852
|
public_review_platform
|
bird:train.json:3810
|
How many businesses are there in Phoenix city? Find the percentage of businesses in Phoenix city in the total city.
|
SELECT SUM(CASE WHEN T3.city LIKE 'Phoenix' THEN 1 ELSE 0 END) AS "num" , CAST(SUM(CASE WHEN T3.city LIKE 'Phoenix' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T3.city) FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id
|
[
"How",
"many",
"businesses",
"are",
"there",
"in",
"Phoenix",
"city",
"?",
"Find",
"the",
"percentage",
"of",
"businesses",
"in",
"Phoenix",
"city",
"in",
"the",
"total",
"city",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "business_categories"
},
{
"id": 3,
"type": "column",
"value": "business_id"
},
{
"id": 7,
"type": "column",
"value": "category_id"
},
{
"id": 2,
"type": "table",
"value": "categories"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 9,
"type": "value",
"value": "Phoenix"
},
{
"id": 6,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
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"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": [
6
]
},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,853
|
sakila_1
|
spider:train_spider.json:2957
|
What is the id of the store that has the most items in inventory?
|
SELECT store_id FROM inventory GROUP BY store_id ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"the",
"store",
"that",
"has",
"the",
"most",
"items",
"in",
"inventory",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "inventory"
},
{
"id": 1,
"type": "column",
"value": "store_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
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"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,854
|
aircraft
|
spider:train_spider.json:4813
|
List names of all pilot aged 30 or younger in descending alphabetical order.
|
SELECT Name FROM pilot WHERE Age <= 30 ORDER BY Name DESC
|
[
"List",
"names",
"of",
"all",
"pilot",
"aged",
"30",
"or",
"younger",
"in",
"descending",
"alphabetical",
"order",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "pilot"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,855
|
codebase_community
|
bird:dev.json:568
|
Provide the display name of the user who made the vote No.6347.
|
SELECT T1.DisplayName FROM users AS T1 INNER JOIN votes AS T2 ON T1.Id = T2.UserId WHERE T2.Id = 6347
|
[
"Provide",
"the",
"display",
"name",
"of",
"the",
"user",
"who",
"made",
"the",
"vote",
"No.6347",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "displayname"
},
{
"id": 5,
"type": "column",
"value": "userid"
},
{
"id": 1,
"type": "table",
"value": "users"
},
{
"id": 2,
"type": "table",
"value": "votes"
},
{
"id": 4,
"type": "value",
"value": "6347"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
14,856
|
simpson_episodes
|
bird:train.json:4346
|
What are the keywords of the episodes which have the air date in 2008?
|
SELECT T2.keyword FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE SUBSTR(T1.air_date, 1, 4) = '2008';
|
[
"What",
"are",
"the",
"keywords",
"of",
"the",
"episodes",
"which",
"have",
"the",
"air",
"date",
"in",
"2008",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "episode_id"
},
{
"id": 5,
"type": "column",
"value": "air_date"
},
{
"id": 0,
"type": "column",
"value": "keyword"
},
{
"id": 1,
"type": "table",
"value": "episode"
},
{
"id": 2,
"type": "table",
"value": "keyword"
},
{
"id": 3,
"type": "value",
"value": "2008"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10,
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
14,858
|
mondial_geo
|
bird:train.json:8502
|
What year saw the greatest number of organizations created on the European continent?
|
SELECT STRFTIME('%Y', T4.Established) FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T2.Country = T3.Code INNER JOIN organization AS T4 ON T4.Country = T3.Code WHERE T1.Name = 'Europe' GROUP BY STRFTIME('%Y', T4.Established) ORDER BY COUNT(T4.Name) DESC LIMIT 1
|
[
"What",
"year",
"saw",
"the",
"greatest",
"number",
"of",
"organizations",
"created",
"on",
"the",
"European",
"continent",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "organization"
},
{
"id": 4,
"type": "column",
"value": "established"
},
{
"id": 9,
"type": "table",
"value": "encompasses"
},
{
"id": 8,
"type": "table",
"value": "continent"
},
{
"id": 10,
"type": "column",
"value": "continent"
},
{
"id": 5,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "value",
"value": "Europe"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "code"
},
{
"id": 3,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"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": [
12
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
14,860
|
club_1
|
spider:train_spider.json:4267
|
How many clubs does "Linda Smith" have membership for?
|
SELECT count(*) FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t3.fname = "Linda" AND t3.lname = "Smith"
|
[
"How",
"many",
"clubs",
"does",
"\"",
"Linda",
"Smith",
"\"",
"have",
"membership",
"for",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "member_of_club"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 8,
"type": "column",
"value": "clubid"
},
{
"id": 3,
"type": "column",
"value": "stuid"
},
{
"id": 4,
"type": "column",
"value": "fname"
},
{
"id": 5,
"type": "column",
"value": "Linda"
},
{
"id": 6,
"type": "column",
"value": "lname"
},
{
"id": 7,
"type": "column",
"value": "Smith"
},
{
"id": 1,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
14,861
|
movie_3
|
bird:train.json:9323
|
How many id movies have category id 11?
|
SELECT COUNT(film_id) FROM film_category WHERE category_id = 11
|
[
"How",
"many",
"i",
"d",
"movies",
"have",
"category",
"i",
"d",
"11",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "film_category"
},
{
"id": 1,
"type": "column",
"value": "category_id"
},
{
"id": 3,
"type": "column",
"value": "film_id"
},
{
"id": 2,
"type": "value",
"value": "11"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
14,862
|
election
|
spider:train_spider.json:2775
|
For each county, find the name of the county and the number of delegates from that county.
|
SELECT T1.County_name , COUNT(*) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id
|
[
"For",
"each",
"county",
",",
"find",
"the",
"name",
"of",
"the",
"county",
"and",
"the",
"number",
"of",
"delegates",
"from",
"that",
"county",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "county_name"
},
{
"id": 0,
"type": "column",
"value": "county_id"
},
{
"id": 3,
"type": "table",
"value": "election"
},
{
"id": 4,
"type": "column",
"value": "district"
},
{
"id": 2,
"type": "table",
"value": "county"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,863
|
company_office
|
spider:train_spider.json:4558
|
What are the names of buildings sorted in descending order of building height?
|
SELECT name FROM buildings ORDER BY Height DESC
|
[
"What",
"are",
"the",
"names",
"of",
"buildings",
"sorted",
"in",
"descending",
"order",
"of",
"building",
"height",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "buildings"
},
{
"id": 2,
"type": "column",
"value": "height"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,864
|
image_and_language
|
bird:train.json:7564
|
Which object has the highest attribute classes?
|
SELECT OBJ_SAMPLE_ID FROM IMG_OBJ_ATT GROUP BY OBJ_SAMPLE_ID ORDER BY COUNT(OBJ_SAMPLE_ID) DESC LIMIT 1
|
[
"Which",
"object",
"has",
"the",
"highest",
"attribute",
"classes",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "obj_sample_id"
},
{
"id": 0,
"type": "table",
"value": "img_obj_att"
}
] |
[
{
"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",
"O",
"O"
] |
14,865
|
e_government
|
spider:train_spider.json:6342
|
Which state can address "6862 Kaitlyn Knolls" possibly be in?
|
SELECT state_province_county FROM addresses WHERE line_1_number_building LIKE "%6862 Kaitlyn Knolls%"
|
[
"Which",
"state",
"can",
"address",
"\"",
"6862",
"Kaitlyn",
"Knolls",
"\"",
"possibly",
"be",
"in",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "line_1_number_building"
},
{
"id": 1,
"type": "column",
"value": "state_province_county"
},
{
"id": 3,
"type": "column",
"value": "%6862 Kaitlyn Knolls%"
},
{
"id": 0,
"type": "table",
"value": "addresses"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
14,866
|
tracking_grants_for_research
|
spider:train_spider.json:4355
|
When did the first staff member start working?
|
SELECT date_from FROM Project_Staff ORDER BY date_from ASC LIMIT 1
|
[
"When",
"did",
"the",
"first",
"staff",
"member",
"start",
"working",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "project_staff"
},
{
"id": 1,
"type": "column",
"value": "date_from"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O"
] |
14,867
|
chinook_1
|
spider:train_spider.json:817
|
Find the names of all artists that have "a" in their names.
|
SELECT Name FROM ARTIST WHERE Name LIKE "%a%"
|
[
"Find",
"the",
"names",
"of",
"all",
"artists",
"that",
"have",
"\"",
"a",
"\"",
"in",
"their",
"names",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "artist"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "%a%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,868
|
retail_world
|
bird:train.json:6640
|
State the name of employee that manages the order from Victuailles en stock?
|
SELECT DISTINCT T1.FirstName, T1.LastName FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Customers AS T3 ON T2.CustomerID = T3.CustomerID WHERE T3.CompanyName = 'Victuailles en stock'
|
[
"State",
"the",
"name",
"of",
"employee",
"that",
"manages",
"the",
"order",
"from",
"Victuailles",
"en",
"stock",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Victuailles en stock"
},
{
"id": 3,
"type": "column",
"value": "companyname"
},
{
"id": 7,
"type": "column",
"value": "customerid"
},
{
"id": 8,
"type": "column",
"value": "employeeid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 6,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
14,869
|
mondial_geo
|
bird:train.json:8230
|
Calculate the population of Arab in each country?
|
SELECT T2.Percentage * T1.Population FROM country AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Code = T2.Country WHERE T2.Name = 'Arab'
|
[
"Calculate",
"the",
"population",
"of",
"Arab",
"in",
"each",
"country",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "ethnicgroup"
},
{
"id": 4,
"type": "column",
"value": "percentage"
},
{
"id": 5,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 7,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "Arab"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
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",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
14,870
|
epinions_1
|
spider:train_spider.json:1689
|
Find the id of the item whose title is "orange".
|
SELECT i_id FROM item WHERE title = "orange"
|
[
"Find",
"the",
"i",
"d",
"of",
"the",
"item",
"whose",
"title",
"is",
"\"",
"orange",
"\"",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "orange"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "item"
},
{
"id": 1,
"type": "column",
"value": "i_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
14,871
|
shakespeare
|
bird:train.json:2983
|
What percentage of all scenes are tragic scenes in Shakespeare's work in 1594?
|
SELECT CAST(SUM(IIF(T2.GenreType = 'Tragedy', 1, 0)) AS REAL) * 100 / COUNT(T1.Scene) FROM chapters AS T1 INNER JOIN works AS T2 ON T1.work_id = T2.id WHERE T2.Date = '1594'
|
[
"What",
"percentage",
"of",
"all",
"scenes",
"are",
"tragic",
"scenes",
"in",
"Shakespeare",
"'s",
"work",
"in",
"1594",
"?"
] |
[
{
"id": 10,
"type": "column",
"value": "genretype"
},
{
"id": 0,
"type": "table",
"value": "chapters"
},
{
"id": 4,
"type": "column",
"value": "work_id"
},
{
"id": 11,
"type": "value",
"value": "Tragedy"
},
{
"id": 1,
"type": "table",
"value": "works"
},
{
"id": 7,
"type": "column",
"value": "scene"
},
{
"id": 2,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "value",
"value": "1594"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"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": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
6
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
14,872
|
products_gen_characteristics
|
spider:train_spider.json:5552
|
What are the name and typical buying and selling prices of the products that have color described as "yellow"?
|
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"
|
[
"What",
"are",
"the",
"name",
"and",
"typical",
"buying",
"and",
"selling",
"prices",
"of",
"the",
"products",
"that",
"have",
"color",
"described",
"as",
"\"",
"yellow",
"\"",
"?"
] |
[
{
"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": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
19
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
14,873
|
movie_1
|
spider:train_spider.json:2447
|
What is the id of the reviewer named Daniel Lewis?
|
SELECT rID FROM Reviewer WHERE name = "Daniel Lewis"
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"the",
"reviewer",
"named",
"Daniel",
"Lewis",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Daniel Lewis"
},
{
"id": 0,
"type": "table",
"value": "reviewer"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "rid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O"
] |
14,874
|
regional_sales
|
bird:train.json:2667
|
Mention the customer names and IDs which ordered total net profit of above 5000 USD through online channel.
|
SELECT DISTINCT `Customer Names`, CustomerID FROM ( SELECT T2.`Customer Names`, T2.CustomerID , SUM(REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '')) AS T FROM `Sales Orders` T1 INNER JOIN Customers T2 ON T2.CustomerID = T1._CustomerID WHERE T1.`Sales Channel` = 'Online' GROUP BY T2.CustomerID ) WHERE T > 5000
|
[
"Mention",
"the",
"customer",
"names",
"and",
"IDs",
"which",
"ordered",
"total",
"net",
"profit",
"of",
"above",
"5000",
"USD",
"through",
"online",
"channel",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "Customer Names"
},
{
"id": 6,
"type": "column",
"value": "Sales Channel"
},
{
"id": 4,
"type": "table",
"value": "Sales Orders"
},
{
"id": 8,
"type": "column",
"value": "_customerid"
},
{
"id": 1,
"type": "column",
"value": "customerid"
},
{
"id": 9,
"type": "column",
"value": "Unit Price"
},
{
"id": 5,
"type": "table",
"value": "customers"
},
{
"id": 11,
"type": "column",
"value": "Unit Cost"
},
{
"id": 7,
"type": "value",
"value": "Online"
},
{
"id": 3,
"type": "value",
"value": "5000"
},
{
"id": 2,
"type": "column",
"value": "t"
},
{
"id": 10,
"type": "value",
"value": ","
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
9,
10
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
14,875
|
movie_3
|
bird:train.json:9374
|
Where can you rent the movie 'Wyoming Storm'? Identify the address of the rental store and the rental rate.
|
SELECT T2.store_id, T1.address, T4.rental_rate FROM address AS T1 INNER JOIN store AS T2 ON T1.address_id = T2.address_id INNER JOIN inventory AS T3 ON T2.store_id = T3.store_id INNER JOIN film AS T4 ON T3.film_id = T4.film_id WHERE T4.title = 'WYOMING STORM'
|
[
"Where",
"can",
"you",
"rent",
"the",
"movie",
"'",
"Wyoming",
"Storm",
"'",
"?",
"Identify",
"the",
"address",
"of",
"the",
"rental",
"store",
"and",
"the",
"rental",
"rate",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "WYOMING STORM"
},
{
"id": 2,
"type": "column",
"value": "rental_rate"
},
{
"id": 10,
"type": "column",
"value": "address_id"
},
{
"id": 6,
"type": "table",
"value": "inventory"
},
{
"id": 0,
"type": "column",
"value": "store_id"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 7,
"type": "column",
"value": "film_id"
},
{
"id": 8,
"type": "table",
"value": "address"
},
{
"id": 4,
"type": "column",
"value": "title"
},
{
"id": 9,
"type": "table",
"value": "store"
},
{
"id": 3,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
20,
21
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7,
8
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": [
17
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
14,876
|
codebase_comments
|
bird:train.json:614
|
Give the repository Url of the one with most solutions.
|
SELECT T1.Url FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId GROUP BY T2.RepoId ORDER BY COUNT(T2.RepoId) DESC LIMIT 1
|
[
"Give",
"the",
"repository",
"Url",
"of",
"the",
"one",
"with",
"most",
"solutions",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "solution"
},
{
"id": 0,
"type": "column",
"value": "repoid"
},
{
"id": 2,
"type": "table",
"value": "repo"
},
{
"id": 1,
"type": "column",
"value": "url"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,877
|
tracking_orders
|
spider:train_spider.json:6888
|
Find the order id and customer id associated with the oldest order.
|
SELECT order_id , customer_id FROM orders ORDER BY date_order_placed LIMIT 1
|
[
"Find",
"the",
"order",
"i",
"d",
"and",
"customer",
"i",
"d",
"associated",
"with",
"the",
"oldest",
"order",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "date_order_placed"
},
{
"id": 2,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "column",
"value": "order_id"
},
{
"id": 0,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,878
|
student_loan
|
bird:train.json:4497
|
List any ten male students who enlisted for foreign legion.
|
SELECT T1.name FROM enlist AS T1 INNER JOIN male AS T2 ON T2.name = T1.name WHERE T1.organ = 'foreign_legion' LIMIT 10
|
[
"List",
"any",
"ten",
"male",
"students",
"who",
"enlisted",
"for",
"foreign",
"legion",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "foreign_legion"
},
{
"id": 1,
"type": "table",
"value": "enlist"
},
{
"id": 3,
"type": "column",
"value": "organ"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "male"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
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",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
14,880
|
donor
|
bird:train.json:3294
|
Which item provided for projects with Mathematics as a primary subject is the most expensive?
|
SELECT T1.item_name FROM resources AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T2.primary_focus_subject = 'Mathematics' ORDER BY T1.item_unit_price DESC LIMIT 1
|
[
"Which",
"item",
"provided",
"for",
"projects",
"with",
"Mathematics",
"as",
"a",
"primary",
"subject",
"is",
"the",
"most",
"expensive",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "primary_focus_subject"
},
{
"id": 5,
"type": "column",
"value": "item_unit_price"
},
{
"id": 4,
"type": "value",
"value": "Mathematics"
},
{
"id": 0,
"type": "column",
"value": "item_name"
},
{
"id": 1,
"type": "table",
"value": "resources"
},
{
"id": 6,
"type": "column",
"value": "projectid"
},
{
"id": 2,
"type": "table",
"value": "projects"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
14,881
|
retails
|
bird:train.json:6737
|
Calculate the percentage of suppliers in Germany.
|
SELECT CAST(SUM(IIF(T2.n_name = 'GERMANY', 1, 0)) AS REAL) * 100 / COUNT(T1.s_suppkey) FROM supplier AS T1 INNER JOIN nation AS T2 ON T1.s_nationkey = T2.n_nationkey WHERE T1.s_acctbal < 0
|
[
"Calculate",
"the",
"percentage",
"of",
"suppliers",
"in",
"Germany",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "s_nationkey"
},
{
"id": 5,
"type": "column",
"value": "n_nationkey"
},
{
"id": 2,
"type": "column",
"value": "s_acctbal"
},
{
"id": 7,
"type": "column",
"value": "s_suppkey"
},
{
"id": 0,
"type": "table",
"value": "supplier"
},
{
"id": 10,
"type": "value",
"value": "GERMANY"
},
{
"id": 1,
"type": "table",
"value": "nation"
},
{
"id": 9,
"type": "column",
"value": "n_name"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
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",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
14,882
|
synthea
|
bird:train.json:1500
|
Among all patients who sought medical attention in 2010 due to contact dermatitis, identify the percentage of females.
|
SELECT CAST(SUM(CASE WHEN T2.gender = 'F' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.PATIENT) FROM encounters AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE strftime('%Y', T1.DATE) = '2010' AND T1.REASONDESCRIPTION = 'Contact dermatitis'
|
[
"Among",
"all",
"patients",
"who",
"sought",
"medical",
"attention",
"in",
"2010",
"due",
"to",
"contact",
"dermatitis",
",",
"identify",
"the",
"percentage",
"of",
"females",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Contact dermatitis"
},
{
"id": 4,
"type": "column",
"value": "reasondescription"
},
{
"id": 0,
"type": "table",
"value": "encounters"
},
{
"id": 1,
"type": "table",
"value": "patients"
},
{
"id": 2,
"type": "column",
"value": "patient"
},
{
"id": 11,
"type": "column",
"value": "gender"
},
{
"id": 3,
"type": "value",
"value": "2010"
},
{
"id": 8,
"type": "column",
"value": "date"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "%Y"
},
{
"id": 9,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "1"
},
{
"id": 12,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11,
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
17
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
14,883
|
bike_share_1
|
bird:train.json:9018
|
What is the average duration of bike trips in the city of Palo Alto?
|
SELECT AVG(T1.duration) FROM trip AS T1 LEFT JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.city = 'Palo Alto'
|
[
"What",
"is",
"the",
"average",
"duration",
"of",
"bike",
"trips",
"in",
"the",
"city",
"of",
"Palo",
"Alto",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "start_station_name"
},
{
"id": 3,
"type": "value",
"value": "Palo Alto"
},
{
"id": 4,
"type": "column",
"value": "duration"
},
{
"id": 1,
"type": "table",
"value": "station"
},
{
"id": 0,
"type": "table",
"value": "trip"
},
{
"id": 2,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
14,885
|
art_1
|
bird:test.json:1275
|
What are the titles of paintings that have a width less than 600 or a height taller taller than 800?
|
SELECT title FROM paintings WHERE width_mm < 600 OR height_mm > 800
|
[
"What",
"are",
"the",
"titles",
"of",
"paintings",
"that",
"have",
"a",
"width",
"less",
"than",
"600",
"or",
"a",
"height",
"taller",
"taller",
"than",
"800",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 4,
"type": "column",
"value": "height_mm"
},
{
"id": 2,
"type": "column",
"value": "width_mm"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "value",
"value": "600"
},
{
"id": 5,
"type": "value",
"value": "800"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
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