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12,949
|
thrombosis_prediction
|
bird:dev.json:1289
|
For the patients who are diagnosed with SJS, how many of them have a normal level of total protein?
|
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T1.Diagnosis = 'SJS' AND T2.TP > 6.0 AND T2.TP < 8.5
|
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{
"id": 1,
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{
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{
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"value": "patient"
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{
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"value": "6.0"
},
{
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},
{
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"type": "column",
"value": "id"
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{
"id": 5,
"type": "column",
"value": "tp"
}
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[
"O",
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"B-TABLE",
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"O",
"B-COLUMN",
"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,951
|
cre_Doc_and_collections
|
bird:test.json:698
|
What are the document object ids of the related to the document owned by Ransom ?
|
select t1.document_object_id from document_subset_members as t1 join document_objects as t2 on t1.document_object_id = t2.document_object_id where t2.owner = 'ransom'
|
[
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"Ransom",
"?"
] |
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{
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{
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{
"id": 4,
"type": "value",
"value": "ransom"
},
{
"id": 3,
"type": "column",
"value": "owner"
}
] |
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] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
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"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,952
|
sales
|
bird:train.json:5366
|
List down the product id for products with the highest quantity.
|
SELECT DISTINCT ProductID FROM Sales WHERE Quantity = ( SELECT MAX(Quantity) FROM Sales )
|
[
"List",
"down",
"the",
"product",
"i",
"d",
"for",
"products",
"with",
"the",
"highest",
"quantity",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "column",
"value": "quantity"
},
{
"id": 0,
"type": "table",
"value": "sales"
}
] |
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{
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"token_idxs": []
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{
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,953
|
professional_basketball
|
bird:train.json:2895
|
List the full name of players who are drafted from round 1 in 1973 but not born in USA.
|
SELECT T1.firstName, T1.middleName, T1.lastName FROM players AS T1 INNER JOIN draft AS T2 ON T1.playerID = T2.playerID WHERE T2.draftRound = 1 AND T1.birthCountry != 'USA' AND T2.draftYear = 1973
|
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"round",
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"in",
"1973",
"but",
"not",
"born",
"in",
"USA",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "birthcountry"
},
{
"id": 1,
"type": "column",
"value": "middlename"
},
{
"id": 6,
"type": "column",
"value": "draftround"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 10,
"type": "column",
"value": "draftyear"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "table",
"value": "players"
},
{
"id": 4,
"type": "table",
"value": "draft"
},
{
"id": 11,
"type": "value",
"value": "1973"
},
{
"id": 9,
"type": "value",
"value": "USA"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
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[
"O",
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"O",
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"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,954
|
station_weather
|
spider:train_spider.json:3160
|
How many trains have 'Express' in their names?
|
SELECT count(*) FROM train WHERE name LIKE "%Express%"
|
[
"How",
"many",
"trains",
"have",
"'",
"Express",
"'",
"in",
"their",
"names",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "%Express%"
},
{
"id": 0,
"type": "table",
"value": "train"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,955
|
law_episode
|
bird:train.json:1296
|
Who is the person who appeared the most in the series? Calculate in percentage how many times he or she appeared.
|
SELECT T2.person_id, CAST(COUNT(T2.person_id) AS REAL) * 100 / ( SELECT COUNT(T2.person_id) AS num FROM Credit AS T1 INNER JOIN Person AS T2 ON T2.person_id = T1.person_id ) AS per FROM Credit AS T1 INNER JOIN Person AS T2 ON T2.person_id = T1.person_id GROUP BY T2.person_id ORDER BY COUNT(T2.person_id) DESC LIMIT 1
|
[
"Who",
"is",
"the",
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"who",
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"the",
"most",
"in",
"the",
"series",
"?",
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"how",
"many",
"times",
"he",
"or",
"she",
"appeared",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "credit"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "value",
"value": "100"
}
] |
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{
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"token_idxs": []
},
{
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}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,956
|
authors
|
bird:train.json:3642
|
What is the title of the paper with the most authors?
|
SELECT T2.Title FROM PaperAuthor AS T1 INNER JOIN Paper AS T2 ON T1.PaperId = T2.Id GROUP BY T1.PaperId ORDER BY COUNT(T1.PaperId) DESC LIMIT 1
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"paper",
"with",
"the",
"most",
"authors",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "paperauthor"
},
{
"id": 0,
"type": "column",
"value": "paperid"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "paper"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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3
]
},
{
"entity_id": 2,
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7
]
},
{
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6
]
},
{
"entity_id": 4,
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},
{
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},
{
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},
{
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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},
{
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},
{
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},
{
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{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
12,957
|
e_government
|
spider:train_spider.json:6336
|
Find the name of organizations whose names contain "Party".
|
SELECT organization_name FROM organizations WHERE organization_name LIKE "%Party%"
|
[
"Find",
"the",
"name",
"of",
"organizations",
"whose",
"names",
"contain",
"\"",
"Party",
"\"",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "organization_name"
},
{
"id": 0,
"type": "table",
"value": "organizations"
},
{
"id": 2,
"type": "column",
"value": "%Party%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
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},
{
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9
]
},
{
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},
{
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{
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
12,958
|
cre_Students_Information_Systems
|
bird:test.json:505
|
How many students have gone through a detention?
|
SELECT count(DISTINCT student_id) FROM Detention
|
[
"How",
"many",
"students",
"have",
"gone",
"through",
"a",
"detention",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "student_id"
},
{
"id": 0,
"type": "table",
"value": "detention"
}
] |
[
{
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"token_idxs": [
7
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{
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"token_idxs": [
2
]
},
{
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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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,959
|
movie_2
|
bird:test.json:1847
|
Select the title of all movies.
|
SELECT title FROM movies
|
[
"Select",
"the",
"title",
"of",
"all",
"movies",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 1,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
12,960
|
institution_sports
|
bird:test.json:1662
|
What are the names of institutions, ordered descending by their number of championships?
|
SELECT T2.Name FROM championship AS T1 JOIN institution AS T2 ON T1.Institution_ID = T2.Institution_ID ORDER BY T1.Number_of_Championships DESC
|
[
"What",
"are",
"the",
"names",
"of",
"institutions",
",",
"ordered",
"descending",
"by",
"their",
"number",
"of",
"championships",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "number_of_championships"
},
{
"id": 4,
"type": "column",
"value": "institution_id"
},
{
"id": 1,
"type": "table",
"value": "championship"
},
{
"id": 2,
"type": "table",
"value": "institution"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O"
] |
12,961
|
software_company
|
bird:train.json:8548
|
List the income and number of inhabitants of customers with an age greater than the 80% of average age of all customers?
|
SELECT T2.INCOME_K, T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID GROUP BY T2.INCOME_K, T2.INHABITANTS_K HAVING T1.age > 0.8 * AVG(T1.age)
|
[
"List",
"the",
"income",
"and",
"number",
"of",
"inhabitants",
"of",
"customers",
"with",
"an",
"age",
"greater",
"than",
"the",
"80",
"%",
"of",
"average",
"age",
"of",
"all",
"customers",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "inhabitants_k"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "column",
"value": "income_k"
},
{
"id": 3,
"type": "table",
"value": "demog"
},
{
"id": 5,
"type": "column",
"value": "geoid"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 6,
"type": "value",
"value": "0.8"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
22
]
},
{
"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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,962
|
sales
|
bird:train.json:5451
|
How much is the total amount of sales handled by Heather McBadden?
|
SELECT SUM(T2.Quantity * T3.Price) FROM Employees AS T1 INNER JOIN Sales AS T2 ON T1.EmployeeID = T2.SalesPersonID INNER JOIN Products AS T3 ON T2.ProductID = T3.ProductID WHERE T1.FirstName = 'Heather' AND T1.LastName = 'McBadden'
|
[
"How",
"much",
"is",
"the",
"total",
"amount",
"of",
"sales",
"handled",
"by",
"Heather",
"McBadden",
"?"
] |
[
{
"id": 11,
"type": "column",
"value": "salespersonid"
},
{
"id": 10,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "productid"
},
{
"id": 4,
"type": "column",
"value": "firstname"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 6,
"type": "column",
"value": "lastname"
},
{
"id": 7,
"type": "value",
"value": "McBadden"
},
{
"id": 8,
"type": "column",
"value": "quantity"
},
{
"id": 5,
"type": "value",
"value": "Heather"
},
{
"id": 2,
"type": "table",
"value": "sales"
},
{
"id": 9,
"type": "column",
"value": "price"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
12,963
|
thrombosis_prediction
|
bird:dev.json:1257
|
Among the patients whose creatinine level is abnormal, how many of them aren't 70 yet?
|
SELECT COUNT(DISTINCT T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.CRE >= 1.5 AND STRFTIME('%Y', Date('now')) - STRFTIME('%Y', T1.Birthday) < 70
|
[
"Among",
"the",
"patients",
"whose",
"creatinine",
"level",
"is",
"abnormal",
",",
"how",
"many",
"of",
"them",
"are",
"n't",
"70",
"yet",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 7,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "cre"
},
{
"id": 4,
"type": "value",
"value": "1.5"
},
{
"id": 8,
"type": "value",
"value": "now"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "70"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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": [
15
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
12,964
|
decoration_competition
|
spider:train_spider.json:4487
|
Show the names of members whose country is "United States" or "Canada".
|
SELECT Name FROM member WHERE Country = "United States" OR Country = "Canada"
|
[
"Show",
"the",
"names",
"of",
"members",
"whose",
"country",
"is",
"\"",
"United",
"States",
"\"",
"or",
"\"",
"Canada",
"\"",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "United States"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 4,
"type": "column",
"value": "Canada"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
12,965
|
world
|
bird:train.json:7866
|
What city in Russia has the least population?
|
SELECT T2.Name FROM Country AS T1 INNER JOIN City AS T2 ON T1.Code = T2.CountryCode WHERE T1.Name = 'Russian Federation' ORDER BY T2.Population ASC LIMIT 1
|
[
"What",
"city",
"in",
"Russia",
"has",
"the",
"least",
"population",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Russian Federation"
},
{
"id": 6,
"type": "column",
"value": "countrycode"
},
{
"id": 4,
"type": "column",
"value": "population"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": [
3,
4,
5,
6
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
12,966
|
school_finance
|
spider:train_spider.json:1905
|
What is the total budget amount for school "Glenn" in all years?
|
SELECT sum(T1.budgeted) FROM budget AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = 'Glenn'
|
[
"What",
"is",
"the",
"total",
"budget",
"amount",
"for",
"school",
"\"",
"Glenn",
"\"",
"in",
"all",
"years",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "school_name"
},
{
"id": 5,
"type": "column",
"value": "school_id"
},
{
"id": 4,
"type": "column",
"value": "budgeted"
},
{
"id": 0,
"type": "table",
"value": "budget"
},
{
"id": 1,
"type": "table",
"value": "school"
},
{
"id": 3,
"type": "value",
"value": "Glenn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
12,967
|
baseball_1
|
spider:train_spider.json:3645
|
How many parks are there in the state of NY?
|
SELECT count(*) FROM park WHERE state = 'NY';
|
[
"How",
"many",
"parks",
"are",
"there",
"in",
"the",
"state",
"of",
"NY",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "table",
"value": "park"
},
{
"id": 2,
"type": "value",
"value": "NY"
}
] |
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9
]
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},
{
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{
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{
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},
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"entity_id": 14,
"token_idxs": []
},
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,968
|
card_games
|
bird:dev.json:369
|
How many cards that illusrtated in German have been reprinted?
|
SELECT COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'German' AND T1.isReprint = 1
|
[
"How",
"many",
"cards",
"that",
"illusrtated",
"in",
"German",
"have",
"been",
"reprinted",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "foreign_data"
},
{
"id": 6,
"type": "column",
"value": "isreprint"
},
{
"id": 4,
"type": "column",
"value": "language"
},
{
"id": 5,
"type": "value",
"value": "German"
},
{
"id": 0,
"type": "table",
"value": "cards"
},
{
"id": 3,
"type": "column",
"value": "uuid"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
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},
{
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},
{
"entity_id": 5,
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6
]
},
{
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9
]
},
{
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},
{
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},
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},
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},
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},
{
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
12,969
|
coffee_shop
|
spider:train_spider.json:793
|
Find the purchase time, age and address of each member, and show the results in the order of purchase time.
|
SELECT Time_of_purchase , age , address FROM member ORDER BY Time_of_purchase
|
[
"Find",
"the",
"purchase",
"time",
",",
"age",
"and",
"address",
"of",
"each",
"member",
",",
"and",
"show",
"the",
"results",
"in",
"the",
"order",
"of",
"purchase",
"time",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "time_of_purchase"
},
{
"id": 3,
"type": "column",
"value": "address"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
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10
]
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{
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19,
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]
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5
]
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7
]
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},
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},
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},
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"entity_id": 13,
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},
{
"entity_id": 14,
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},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
12,970
|
loan_1
|
spider:train_spider.json:3017
|
What city and state is the bank with the name morningside in?
|
SELECT city , state FROM bank WHERE bname = 'morningside'
|
[
"What",
"city",
"and",
"state",
"is",
"the",
"bank",
"with",
"the",
"name",
"morningside",
"in",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "morningside"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 3,
"type": "column",
"value": "bname"
},
{
"id": 0,
"type": "table",
"value": "bank"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
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1
]
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{
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3
]
},
{
"entity_id": 3,
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9
]
},
{
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10
]
},
{
"entity_id": 5,
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{
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{
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{
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},
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O"
] |
12,971
|
toxicology
|
bird:dev.json:310
|
How many molecules have a double bond type and among these molecule, how many are labeled as carcinogenic compound?
|
SELECT COUNT(DISTINCT T2.molecule_id), SUM(CASE WHEN T2.label = '+' THEN 1 ELSE 0 END) FROM bond AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.bond_type = '='
|
[
"How",
"many",
"molecules",
"have",
"a",
"double",
"bond",
"type",
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"among",
"these",
"molecule",
",",
"how",
"many",
"are",
"labeled",
"as",
"carcinogenic",
"compound",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "molecule_id"
},
{
"id": 2,
"type": "column",
"value": "bond_type"
},
{
"id": 1,
"type": "table",
"value": "molecule"
},
{
"id": 7,
"type": "column",
"value": "label"
},
{
"id": 0,
"type": "table",
"value": "bond"
},
{
"id": 3,
"type": "value",
"value": "="
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 8,
"type": "value",
"value": "+"
}
] |
[
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"entity_id": 0,
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6
]
},
{
"entity_id": 1,
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11
]
},
{
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7
]
},
{
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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16
]
},
{
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{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
12,972
|
hr_1
|
spider:train_spider.json:3423
|
display all the information of employees whose salary is in the range of 8000 and 12000 and commission is not null or department number does not equal to 40.
|
SELECT * FROM employees WHERE salary BETWEEN 8000 AND 12000 AND commission_pct != "null" OR department_id != 40
|
[
"display",
"all",
"the",
"information",
"of",
"employees",
"whose",
"salary",
"is",
"in",
"the",
"range",
"of",
"8000",
"and",
"12000",
"and",
"commission",
"is",
"not",
"null",
"or",
"department",
"number",
"does",
"not",
"equal",
"to",
"40",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "commission_pct"
},
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "salary"
},
{
"id": 5,
"type": "value",
"value": "12000"
},
{
"id": 4,
"type": "value",
"value": "8000"
},
{
"id": 7,
"type": "column",
"value": "null"
},
{
"id": 2,
"type": "value",
"value": "40"
}
] |
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{
"entity_id": 0,
"token_idxs": [
5
]
},
{
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22
]
},
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28
]
},
{
"entity_id": 3,
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7
]
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{
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]
},
{
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15
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17
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20
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,973
|
retail_world
|
bird:train.json:6474
|
Calculate the percentage of products supplied by Gai pturage over all products.
|
SELECT CAST(COUNT(CASE WHEN T2.CompanyName = 'Gai pturage' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.SupplierID) FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID
|
[
"Calculate",
"the",
"percentage",
"of",
"products",
"supplied",
"by",
"Gai",
"pturage",
"over",
"all",
"products",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "companyname"
},
{
"id": 6,
"type": "value",
"value": "Gai pturage"
},
{
"id": 2,
"type": "column",
"value": "supplierid"
},
{
"id": 1,
"type": "table",
"value": "suppliers"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
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4
]
},
{
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5
]
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},
{
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7,
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},
{
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{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
12,974
|
food_inspection
|
bird:train.json:8811
|
What is the name of the establishment with the lowest inspection score of all time?
|
SELECT T2.name FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.score = ( SELECT MIN(score) FROM inspections )
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"establishment",
"with",
"the",
"lowest",
"inspection",
"score",
"of",
"all",
"time",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "inspections"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 2,
"type": "table",
"value": "businesses"
},
{
"id": 3,
"type": "column",
"value": "score"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
12,975
|
movies_4
|
bird:train.json:492
|
Write down five rumoured movie titles within the genre of Drama.
|
SELECT T1.title FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T1.movie_status = 'Rumored' AND T3.genre_name = 'Drama' LIMIT 5
|
[
"Write",
"down",
"five",
"rumoured",
"movie",
"titles",
"within",
"the",
"genre",
"of",
"Drama",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "movie_genres"
},
{
"id": 5,
"type": "column",
"value": "movie_status"
},
{
"id": 7,
"type": "column",
"value": "genre_name"
},
{
"id": 4,
"type": "column",
"value": "genre_id"
},
{
"id": 9,
"type": "column",
"value": "movie_id"
},
{
"id": 6,
"type": "value",
"value": "Rumored"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "genre"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 8,
"type": "value",
"value": "Drama"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"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",
"O",
"O",
"B-VALUE",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
12,976
|
customers_card_transactions
|
spider:train_spider.json:729
|
Show all card type codes.
|
SELECT DISTINCT card_type_code FROM Customers_Cards
|
[
"Show",
"all",
"card",
"type",
"codes",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "customers_cards"
},
{
"id": 1,
"type": "column",
"value": "card_type_code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
12,978
|
talkingdata
|
bird:train.json:1116
|
List at least 5 device models that are commonly used by female users.
|
SELECT T.device_model FROM ( SELECT T2.device_model, COUNT(T2.device_model) AS num FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.gender = 'F' GROUP BY T2.device_model ) AS T ORDER BY T.num DESC LIMIT 5
|
[
"List",
"at",
"least",
"5",
"device",
"models",
"that",
"are",
"commonly",
"used",
"by",
"female",
"users",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 0,
"type": "column",
"value": "device_model"
},
{
"id": 2,
"type": "table",
"value": "gender_age"
},
{
"id": 6,
"type": "column",
"value": "device_id"
},
{
"id": 4,
"type": "column",
"value": "gender"
},
{
"id": 1,
"type": "column",
"value": "num"
},
{
"id": 5,
"type": "value",
"value": "F"
}
] |
[
{
"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": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,979
|
shipping
|
bird:train.json:5637
|
State the address of drivers who transported the shipment with weight greater than 50000 pounds.
|
SELECT T2.address FROM shipment AS T1 INNER JOIN driver AS T2 ON T1.driver_id = T2.driver_id GROUP BY T2.driver_id HAVING SUM(T1.weight) > 50000
|
[
"State",
"the",
"address",
"of",
"drivers",
"who",
"transported",
"the",
"shipment",
"with",
"weight",
"greater",
"than",
"50000",
"pounds",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "driver_id"
},
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 3,
"type": "table",
"value": "driver"
},
{
"id": 5,
"type": "column",
"value": "weight"
},
{
"id": 4,
"type": "value",
"value": "50000"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
12,980
|
address
|
bird:train.json:5085
|
Among all the residential areas in Delaware, how many of them implement daylight saving?
|
SELECT COUNT(T1.zip_code) FROM zip_data AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T2.county = 'DELAWARE' AND T1.daylight_savings = 'Yes'
|
[
"Among",
"all",
"the",
"residential",
"areas",
"in",
"Delaware",
",",
"how",
"many",
"of",
"them",
"implement",
"daylight",
"saving",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "daylight_savings"
},
{
"id": 0,
"type": "table",
"value": "zip_data"
},
{
"id": 2,
"type": "column",
"value": "zip_code"
},
{
"id": 4,
"type": "value",
"value": "DELAWARE"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "county"
},
{
"id": 6,
"type": "value",
"value": "Yes"
}
] |
[
{
"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": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
13,
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
12,981
|
restaurant
|
bird:train.json:1757
|
Give the street number of a bar in Oakland with a 2.7 review.
|
SELECT T2.street_num FROM generalinfo AS T1 INNER JOIN location AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T1.review = 2.7 AND T2.city = 'oakland' AND T1.food_type = 'bar'
|
[
"Give",
"the",
"street",
"number",
"of",
"a",
"bar",
"in",
"Oakland",
"with",
"a",
"2.7",
"review",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "id_restaurant"
},
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 0,
"type": "column",
"value": "street_num"
},
{
"id": 8,
"type": "column",
"value": "food_type"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 7,
"type": "value",
"value": "oakland"
},
{
"id": 4,
"type": "column",
"value": "review"
},
{
"id": 6,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "2.7"
},
{
"id": 9,
"type": "value",
"value": "bar"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
6
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,982
|
allergy_1
|
spider:train_spider.json:524
|
What are the first name and gender of the students who have allergy to milk but can put up with cats?
|
SELECT fname , sex FROM Student WHERE StuID IN (SELECT StuID FROM Has_allergy WHERE Allergy = "Milk" EXCEPT SELECT StuID FROM Has_allergy WHERE Allergy = "Cat")
|
[
"What",
"are",
"the",
"first",
"name",
"and",
"gender",
"of",
"the",
"students",
"who",
"have",
"allergy",
"to",
"milk",
"but",
"can",
"put",
"up",
"with",
"cats",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "has_allergy"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 5,
"type": "column",
"value": "allergy"
},
{
"id": 1,
"type": "column",
"value": "fname"
},
{
"id": 3,
"type": "column",
"value": "stuid"
},
{
"id": 6,
"type": "column",
"value": "Milk"
},
{
"id": 2,
"type": "column",
"value": "sex"
},
{
"id": 7,
"type": "column",
"value": "Cat"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
20
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,983
|
flight_company
|
spider:train_spider.json:6383
|
which countries have more than 2 airports?
|
SELECT country FROM airport GROUP BY country HAVING count(*) > 2
|
[
"which",
"countries",
"have",
"more",
"than",
"2",
"airports",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "airport"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
12,984
|
art_1
|
bird:test.json:1200
|
What is the title of the sculpture that was created in the most recent year ?
|
select title from sculptures order by year desc limit 1
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"sculpture",
"that",
"was",
"created",
"in",
"the",
"most",
"recent",
"year",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "sculptures"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,985
|
retail_world
|
bird:train.json:6353
|
How many percent more orders were fulfilled with shipper company "United Package" than with "Speedy Express"?
|
SELECT CAST((COUNT(CASE WHEN T2.CompanyName = 'United Package' THEN 1 ELSE NULL END) - COUNT(CASE WHEN T2.CompanyName = 'Speedy Express' THEN 1 ELSE NULL END)) AS REAL) * 100 / COUNT(CASE WHEN T2.CompanyName = 'Speedy Express' THEN 1 ELSE NULL END) FROM Orders AS T1 INNER JOIN Shippers AS T2 ON T1.ShipVia = T2.ShipperID
|
[
"How",
"many",
"percent",
"more",
"orders",
"were",
"fulfilled",
"with",
"shipper",
"company",
"\"",
"United",
"Package",
"\"",
"than",
"with",
"\"",
"Speedy",
"Express",
"\"",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Speedy Express"
},
{
"id": 8,
"type": "value",
"value": "United Package"
},
{
"id": 6,
"type": "column",
"value": "companyname"
},
{
"id": 3,
"type": "column",
"value": "shipperid"
},
{
"id": 1,
"type": "table",
"value": "shippers"
},
{
"id": 2,
"type": "column",
"value": "shipvia"
},
{
"id": 0,
"type": "table",
"value": "orders"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"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": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
17,
18
]
},
{
"entity_id": 8,
"token_idxs": [
11,
12
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
12,986
|
cre_Doc_Workflow
|
bird:test.json:2048
|
Show all document ids without a process.
|
SELECT document_id FROM Documents EXCEPT SELECT document_id FROM Documents_processes
|
[
"Show",
"all",
"document",
"ids",
"without",
"a",
"process",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "documents_processes"
},
{
"id": 2,
"type": "column",
"value": "document_id"
},
{
"id": 0,
"type": "table",
"value": "documents"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O"
] |
12,987
|
advertising_agencies
|
bird:test.json:2129
|
Show all meeting ids, meeting outcomes, meeting types and the details of the client atttending it.
|
SELECT T1.meeting_id , T1.meeting_outcome , T1.meeting_type , T2.client_details FROM meetings AS T1 JOIN clients AS T2 ON T1.client_id = T2.client_id
|
[
"Show",
"all",
"meeting",
"ids",
",",
"meeting",
"outcomes",
",",
"meeting",
"types",
"and",
"the",
"details",
"of",
"the",
"client",
"atttending",
"it",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "meeting_outcome"
},
{
"id": 3,
"type": "column",
"value": "client_details"
},
{
"id": 2,
"type": "column",
"value": "meeting_type"
},
{
"id": 0,
"type": "column",
"value": "meeting_id"
},
{
"id": 6,
"type": "column",
"value": "client_id"
},
{
"id": 4,
"type": "table",
"value": "meetings"
},
{
"id": 5,
"type": "table",
"value": "clients"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
12,988
|
authors
|
bird:train.json:3644
|
List all of the papers written by the author "Karin Rengefors."
|
SELECT T2.Title FROM PaperAuthor AS T1 INNER JOIN Paper AS T2 ON T1.PaperId = T2.Id WHERE T1.Name = 'Karin Rengefors'
|
[
"List",
"all",
"of",
"the",
"papers",
"written",
"by",
"the",
"author",
"\"",
"Karin",
"Rengefors",
".",
"\""
] |
[
{
"id": 4,
"type": "value",
"value": "Karin Rengefors"
},
{
"id": 1,
"type": "table",
"value": "paperauthor"
},
{
"id": 5,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10,
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
12,989
|
sports_competition
|
spider:train_spider.json:3388
|
What are the countries that have never participated in any friendly-type competitions?
|
SELECT country FROM competition EXCEPT SELECT country FROM competition WHERE competition_type = 'Friendly'
|
[
"What",
"are",
"the",
"countries",
"that",
"have",
"never",
"participated",
"in",
"any",
"friendly",
"-",
"type",
"competitions",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "competition_type"
},
{
"id": 0,
"type": "table",
"value": "competition"
},
{
"id": 3,
"type": "value",
"value": "Friendly"
},
{
"id": 1,
"type": "column",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
12,990
|
phone_1
|
spider:train_spider.json:1039
|
List the hardware model name for the phones that were produced by "Nokia Corporation" or whose screen mode type is "Graphics."
|
SELECT DISTINCT T2.Hardware_Model_name FROM screen_mode AS T1 JOIN phone AS T2 ON T1.Graphics_mode = T2.screen_mode WHERE T1.Type = "Graphics" OR t2.Company_name = "Nokia Corporation"
|
[
"List",
"the",
"hardware",
"model",
"name",
"for",
"the",
"phones",
"that",
"were",
"produced",
"by",
"\"",
"Nokia",
"Corporation",
"\"",
"or",
"whose",
"screen",
"mode",
"type",
"is",
"\"",
"Graphics",
".",
"\""
] |
[
{
"id": 0,
"type": "column",
"value": "hardware_model_name"
},
{
"id": 8,
"type": "column",
"value": "Nokia Corporation"
},
{
"id": 3,
"type": "column",
"value": "graphics_mode"
},
{
"id": 7,
"type": "column",
"value": "company_name"
},
{
"id": 1,
"type": "table",
"value": "screen_mode"
},
{
"id": 4,
"type": "column",
"value": "screen_mode"
},
{
"id": 6,
"type": "column",
"value": "Graphics"
},
{
"id": 2,
"type": "table",
"value": "phone"
},
{
"id": 5,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
18,
19
]
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"entity_id": 6,
"token_idxs": [
23
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
13,
14
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
12,991
|
book_2
|
spider:train_spider.json:223
|
Show writers who have published a book with price more than 4000000.
|
SELECT T1.Writer FROM book AS T1 JOIN publication AS T2 ON T1.Book_ID = T2.Book_ID WHERE T2.Price > 4000000
|
[
"Show",
"writers",
"who",
"have",
"published",
"a",
"book",
"with",
"price",
"more",
"than",
"4000000",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "publication"
},
{
"id": 4,
"type": "value",
"value": "4000000"
},
{
"id": 5,
"type": "column",
"value": "book_id"
},
{
"id": 0,
"type": "column",
"value": "writer"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
12,992
|
restaurant
|
bird:train.json:1696
|
In which regions are there no pizza restaurants?
|
SELECT DISTINCT T2.region FROM generalinfo AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T1.food_type = 'pizza' AND T2.region != 'unknown'
|
[
"In",
"which",
"regions",
"are",
"there",
"no",
"pizza",
"restaurants",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 2,
"type": "table",
"value": "geographic"
},
{
"id": 4,
"type": "column",
"value": "food_type"
},
{
"id": 6,
"type": "value",
"value": "unknown"
},
{
"id": 0,
"type": "column",
"value": "region"
},
{
"id": 5,
"type": "value",
"value": "pizza"
},
{
"id": 3,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
12,993
|
movielens
|
bird:train.json:2295
|
How many drama movie with the rating of 3?
|
SELECT COUNT(DISTINCT T2.movieid) FROM u2base AS T1 INNER JOIN movies2directors AS T2 ON T1.movieid = T2.movieid WHERE T2.genre = 'drama' AND T1.rating = 3
|
[
"How",
"many",
"drama",
"movie",
"with",
"the",
"rating",
"of",
"3",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "movies2directors"
},
{
"id": 2,
"type": "column",
"value": "movieid"
},
{
"id": 0,
"type": "table",
"value": "u2base"
},
{
"id": 5,
"type": "column",
"value": "rating"
},
{
"id": 3,
"type": "column",
"value": "genre"
},
{
"id": 4,
"type": "value",
"value": "drama"
},
{
"id": 6,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"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-VALUE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,994
|
e_learning
|
spider:train_spider.json:3832
|
List the dates of enrollment and completion of the student with personal name "Karson".
|
SELECT T1.date_of_enrolment , T1.date_of_completion FROM Student_Course_Enrolment AS T1 JOIN Students AS T2 ON T1.student_id = T2.student_id WHERE T2.personal_name = "Karson"
|
[
"List",
"the",
"dates",
"of",
"enrollment",
"and",
"completion",
"of",
"the",
"student",
"with",
"personal",
"name",
"\"",
"Karson",
"\"",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "student_course_enrolment"
},
{
"id": 1,
"type": "column",
"value": "date_of_completion"
},
{
"id": 0,
"type": "column",
"value": "date_of_enrolment"
},
{
"id": 4,
"type": "column",
"value": "personal_name"
},
{
"id": 6,
"type": "column",
"value": "student_id"
},
{
"id": 3,
"type": "table",
"value": "students"
},
{
"id": 5,
"type": "column",
"value": "Karson"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
12,995
|
program_share
|
spider:train_spider.json:3734
|
how many programs are there?
|
SELECT count(*) FROM program
|
[
"how",
"many",
"programs",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "program"
}
] |
[
{
"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"
] |
12,996
|
books
|
bird:train.json:5939
|
Give the number of Ukrainian addresses in the database.
|
SELECT COUNT(*) FROM country AS T1 INNER JOIN address AS T2 ON T1.country_id = T2.country_id WHERE T1.country_name = 'Ukraine'
|
[
"Give",
"the",
"number",
"of",
"Ukrainian",
"addresses",
"in",
"the",
"database",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "country_name"
},
{
"id": 4,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "address"
},
{
"id": 3,
"type": "value",
"value": "Ukraine"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
12,997
|
pilot_1
|
bird:test.json:1136
|
What are the locations of the different planes, ordered by plane name?
|
SELECT LOCATION FROM hangar ORDER BY plane_name
|
[
"What",
"are",
"the",
"locations",
"of",
"the",
"different",
"planes",
",",
"ordered",
"by",
"plane",
"name",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "plane_name"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "hangar"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11,
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",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
12,998
|
codebase_community
|
bird:dev.json:540
|
What is the title of the post that is owned by csgillespie and has the highest popularity?
|
SELECT T1.Title FROM posts AS T1 INNER JOIN users AS T2 ON T1.OwnerUserId = T2.Id WHERE T2.DisplayName = 'csgillespie' ORDER BY T1.ViewCount DESC LIMIT 1
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"post",
"that",
"is",
"owned",
"by",
"csgillespie",
"and",
"has",
"the",
"highest",
"popularity",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "displayname"
},
{
"id": 4,
"type": "value",
"value": "csgillespie"
},
{
"id": 6,
"type": "column",
"value": "owneruserid"
},
{
"id": 5,
"type": "column",
"value": "viewcount"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "posts"
},
{
"id": 2,
"type": "table",
"value": "users"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,999
|
student_assessment
|
spider:train_spider.json:71
|
How many courses do the student whose id is 171 attend?
|
SELECT count(*) FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T2.student_id = 171
|
[
"How",
"many",
"courses",
"do",
"the",
"student",
"whose",
"i",
"d",
"is",
"171",
"attend",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "student_course_attendance"
},
{
"id": 2,
"type": "column",
"value": "student_id"
},
{
"id": 4,
"type": "column",
"value": "course_id"
},
{
"id": 0,
"type": "table",
"value": "courses"
},
{
"id": 3,
"type": "value",
"value": "171"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
13,000
|
video_games
|
bird:train.json:3313
|
Among the games published by 10TACLE Studios, how many of them are puzzles?
|
SELECT COUNT(T1.id) FROM game AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.game_id INNER JOIN publisher AS T3 ON T2.publisher_id = T3.id INNER JOIN genre AS T4 ON T1.genre_id = T4.id WHERE T4.genre_name = 'Puzzle' AND T3.publisher_name = '10TACLE Studios'
|
[
"Among",
"the",
"games",
"published",
"by",
"10TACLE",
"Studios",
",",
"how",
"many",
"of",
"them",
"are",
"puzzles",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "10TACLE Studios"
},
{
"id": 6,
"type": "column",
"value": "publisher_name"
},
{
"id": 9,
"type": "table",
"value": "game_publisher"
},
{
"id": 10,
"type": "column",
"value": "publisher_id"
},
{
"id": 4,
"type": "column",
"value": "genre_name"
},
{
"id": 2,
"type": "table",
"value": "publisher"
},
{
"id": 3,
"type": "column",
"value": "genre_id"
},
{
"id": 11,
"type": "column",
"value": "game_id"
},
{
"id": 5,
"type": "value",
"value": "Puzzle"
},
{
"id": 0,
"type": "table",
"value": "genre"
},
{
"id": 8,
"type": "table",
"value": "game"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5,
6
]
},
{
"entity_id": 8,
"token_idxs": [
2
]
},
{
"entity_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-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,001
|
insurance_policies
|
spider:train_spider.json:3862
|
Among all the claims, which settlements have a claimed amount that is no more than the average? List the claim start date.
|
SELECT Date_Claim_Made FROM Claims WHERE Amount_Settled <= ( SELECT avg(Amount_Settled) FROM Claims )
|
[
"Among",
"all",
"the",
"claims",
",",
"which",
"settlements",
"have",
"a",
"claimed",
"amount",
"that",
"is",
"no",
"more",
"than",
"the",
"average",
"?",
"List",
"the",
"claim",
"start",
"date",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "date_claim_made"
},
{
"id": 2,
"type": "column",
"value": "amount_settled"
},
{
"id": 0,
"type": "table",
"value": "claims"
}
] |
[
{
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"token_idxs": [
3
]
},
{
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20,
21
]
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10,
11
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{
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},
{
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{
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},
{
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},
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"token_idxs": []
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"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O"
] |
13,002
|
card_games
|
bird:dev.json:356
|
How many cards have infinite power?
|
SELECT COUNT(*) FROM cards WHERE power = '*'
|
[
"How",
"many",
"cards",
"have",
"infinite",
"power",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "cards"
},
{
"id": 1,
"type": "column",
"value": "power"
},
{
"id": 2,
"type": "value",
"value": "*"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
13,003
|
card_games
|
bird:dev.json:487
|
What is the percentage of incredibly powerful cards in the set Coldsnap?
|
SELECT CAST(SUM(CASE WHEN T1.cardKingdomFoilId IS NOT NULL AND T1.cardKingdomId IS NOT NULL THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE T2.name = 'Coldsnap'
|
[
"What",
"is",
"the",
"percentage",
"of",
"incredibly",
"powerful",
"cards",
"in",
"the",
"set",
"Coldsnap",
"?"
] |
[
{
"id": 10,
"type": "column",
"value": "cardkingdomfoilid"
},
{
"id": 11,
"type": "column",
"value": "cardkingdomid"
},
{
"id": 3,
"type": "value",
"value": "Coldsnap"
},
{
"id": 5,
"type": "column",
"value": "setcode"
},
{
"id": 0,
"type": "table",
"value": "cards"
},
{
"id": 1,
"type": "table",
"value": "sets"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
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7
]
},
{
"entity_id": 1,
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10
]
},
{
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"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,
"token_idxs": []
},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
13,005
|
talkingdata
|
bird:train.json:1072
|
What are the ages and genders of the LG L70 users?
|
SELECT T2.age, T2.gender FROM phone_brand_device_model2 AS T1 INNER JOIN gender_age AS T2 ON T2.device_id = T1.device_id WHERE T1.phone_brand = 'LG' AND T1.device_model = 'L70'
|
[
"What",
"are",
"the",
"ages",
"and",
"genders",
"of",
"the",
"LG",
"L70",
"users",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 7,
"type": "column",
"value": "device_model"
},
{
"id": 5,
"type": "column",
"value": "phone_brand"
},
{
"id": 3,
"type": "table",
"value": "gender_age"
},
{
"id": 4,
"type": "column",
"value": "device_id"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 0,
"type": "column",
"value": "age"
},
{
"id": 8,
"type": "value",
"value": "L70"
},
{
"id": 6,
"type": "value",
"value": "LG"
}
] |
[
{
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3
]
},
{
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5
]
},
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},
{
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},
{
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{
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},
{
"entity_id": 6,
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8
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},
{
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},
{
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9
]
},
{
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"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
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},
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"token_idxs": []
},
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"token_idxs": []
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{
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"token_idxs": []
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{
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"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
13,006
|
chicago_crime
|
bird:train.json:8682
|
Which community area has the highest number of crimes reported on the street?
|
SELECT T1.community_area_no FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T2.community_area_no = T1.community_area_no WHERE T2.location_description = 'STREET' GROUP BY T1.community_area_no ORDER BY COUNT(T2.location_description) DESC LIMIT 1
|
[
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"area",
"has",
"the",
"highest",
"number",
"of",
"crimes",
"reported",
"on",
"the",
"street",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "location_description"
},
{
"id": 0,
"type": "column",
"value": "community_area_no"
},
{
"id": 1,
"type": "table",
"value": "community_area"
},
{
"id": 4,
"type": "value",
"value": "STREET"
},
{
"id": 2,
"type": "table",
"value": "crime"
}
] |
[
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"token_idxs": []
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1,
2
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8
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{
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{
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"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
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{
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"token_idxs": []
},
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,007
|
works_cycles
|
bird:train.json:7006
|
Which is a high quality product but with the lowest transacted quantity?
|
SELECT T1.Name FROM Product AS T1 INNER JOIN TransactionHistory AS T2 ON T1.ProductID = T2.ProductID WHERE T1.Class = 'H' ORDER BY T2.Quantity ASC LIMIT 1
|
[
"Which",
"is",
"a",
"high",
"quality",
"product",
"but",
"with",
"the",
"lowest",
"transacted",
"quantity",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "transactionhistory"
},
{
"id": 6,
"type": "column",
"value": "productid"
},
{
"id": 5,
"type": "column",
"value": "quantity"
},
{
"id": 1,
"type": "table",
"value": "product"
},
{
"id": 3,
"type": "column",
"value": "class"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "H"
}
] |
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{
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"token_idxs": []
},
{
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5
]
},
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10
]
},
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},
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},
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
13,008
|
candidate_poll
|
spider:train_spider.json:2417
|
For each sex, what is the name and sex of the candidate with the oppose rate for their sex?
|
SELECT t1.name , t1.sex , min(oppose_rate) FROM people AS t1 JOIN candidate AS t2 ON t1.people_id = t2.people_id GROUP BY t1.sex
|
[
"For",
"each",
"sex",
",",
"what",
"is",
"the",
"name",
"and",
"sex",
"of",
"the",
"candidate",
"with",
"the",
"oppose",
"rate",
"for",
"their",
"sex",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "oppose_rate"
},
{
"id": 3,
"type": "table",
"value": "candidate"
},
{
"id": 5,
"type": "column",
"value": "people_id"
},
{
"id": 2,
"type": "table",
"value": "people"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "sex"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
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},
{
"entity_id": 3,
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12
]
},
{
"entity_id": 4,
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15,
16
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},
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{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
13,009
|
chicago_crime
|
bird:train.json:8652
|
Among the crimes in the Central, calculate the percentage of larceny incidents.
|
SELECT CAST(COUNT(CASE WHEN T3.title = 'Larceny' THEN T2.report_no END) AS REAL) * 100 / COUNT(T2.report_no) FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T2.community_area_no = T1.community_area_no INNER JOIN FBI_Code AS T3 ON T3.fbi_code_no = T2.fbi_code_no WHERE T1.side = 'Central'
|
[
"Among",
"the",
"crimes",
"in",
"the",
"Central",
",",
"calculate",
"the",
"percentage",
"of",
"larceny",
"incidents",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "community_area_no"
},
{
"id": 3,
"type": "table",
"value": "community_area"
},
{
"id": 5,
"type": "column",
"value": "fbi_code_no"
},
{
"id": 7,
"type": "column",
"value": "report_no"
},
{
"id": 0,
"type": "table",
"value": "fbi_code"
},
{
"id": 2,
"type": "value",
"value": "Central"
},
{
"id": 10,
"type": "value",
"value": "Larceny"
},
{
"id": 4,
"type": "table",
"value": "crime"
},
{
"id": 9,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "column",
"value": "side"
},
{
"id": 6,
"type": "value",
"value": "100"
}
] |
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"token_idxs": []
},
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"token_idxs": [
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},
{
"entity_id": 18,
"token_idxs": []
},
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"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
13,010
|
election
|
spider:train_spider.json:2743
|
What are the distinct districts for elections?
|
SELECT DISTINCT District FROM election
|
[
"What",
"are",
"the",
"distinct",
"districts",
"for",
"elections",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "election"
},
{
"id": 1,
"type": "column",
"value": "district"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
13,011
|
network_2
|
spider:train_spider.json:4422
|
What is average age for different job title?
|
SELECT avg(age) , job FROM Person GROUP BY job
|
[
"What",
"is",
"average",
"age",
"for",
"different",
"job",
"title",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "job"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,012
|
movie_platform
|
bird:train.json:25
|
Which year was the third movie directed by Quentin Tarantino released? Indicate the user ids of the user who gave it a rating score of 4.
|
SELECT T2.movie_release_year, T1.user_id FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T1.movie_id = ( SELECT movie_id FROM movies WHERE director_name = 'Quentin Tarantino' ORDER BY movie_release_year ASC LIMIT 2, 1 ) AND T1.rating_score = 4
|
[
"Which",
"year",
"was",
"the",
"third",
"movie",
"directed",
"by",
"Quentin",
"Tarantino",
"released",
"?",
"Indicate",
"the",
"user",
"ids",
"of",
"the",
"user",
"who",
"gave",
"it",
"a",
"rating",
"score",
"of",
"4",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "movie_release_year"
},
{
"id": 8,
"type": "value",
"value": "Quentin Tarantino"
},
{
"id": 7,
"type": "column",
"value": "director_name"
},
{
"id": 5,
"type": "column",
"value": "rating_score"
},
{
"id": 4,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "column",
"value": "user_id"
},
{
"id": 2,
"type": "table",
"value": "ratings"
},
{
"id": 3,
"type": "table",
"value": "movies"
},
{
"id": 6,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14,
15
]
},
{
"entity_id": 2,
"token_idxs": [
23
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
24
]
},
{
"entity_id": 6,
"token_idxs": [
26
]
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": [
8,
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",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,013
|
bakery_1
|
bird:test.json:1584
|
Give the three most purchased items at this bakery.
|
SELECT item FROM items GROUP BY item ORDER BY COUNT (*) DESC LIMIT 3
|
[
"Give",
"the",
"three",
"most",
"purchased",
"items",
"at",
"this",
"bakery",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "items"
},
{
"id": 1,
"type": "column",
"value": "item"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,014
|
thrombosis_prediction
|
bird:dev.json:1173
|
What is the most common illness that doctors identified among the patients whose lab work was done between 1/1/1985, and 12/31/1995?
|
SELECT T2.Diagnosis FROM Examination AS T1 INNER JOIN Patient AS T2 ON T1.ID = T2.ID WHERE T1.`Examination Date` BETWEEN '1985-01-01' AND '1995-12-31' GROUP BY T2.Diagnosis ORDER BY COUNT(T2.Diagnosis) DESC LIMIT 1
|
[
"What",
"is",
"the",
"most",
"common",
"illness",
"that",
"doctors",
"identified",
"among",
"the",
"patients",
"whose",
"lab",
"work",
"was",
"done",
"between",
"1/1/1985",
",",
"and",
"12/31/1995",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Examination Date"
},
{
"id": 1,
"type": "table",
"value": "examination"
},
{
"id": 4,
"type": "value",
"value": "1985-01-01"
},
{
"id": 5,
"type": "value",
"value": "1995-12-31"
},
{
"id": 0,
"type": "column",
"value": "diagnosis"
},
{
"id": 2,
"type": "table",
"value": "patient"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,015
|
hockey
|
bird:train.json:7659
|
Among the coaches whose team has over 30 wins in a year, how many of them are born in the USA?
|
SELECT COUNT(T2.coachID) FROM Master AS T1 INNER JOIN Coaches AS T2 ON T1.coachID = T2.coachID WHERE T2.W > 30 AND T1.birthCountry = 'USA'
|
[
"Among",
"the",
"coaches",
"whose",
"team",
"has",
"over",
"30",
"wins",
"in",
"a",
"year",
",",
"how",
"many",
"of",
"them",
"are",
"born",
"in",
"the",
"USA",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "birthcountry"
},
{
"id": 1,
"type": "table",
"value": "coaches"
},
{
"id": 2,
"type": "column",
"value": "coachid"
},
{
"id": 0,
"type": "table",
"value": "master"
},
{
"id": 6,
"type": "value",
"value": "USA"
},
{
"id": 4,
"type": "value",
"value": "30"
},
{
"id": 3,
"type": "column",
"value": "w"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
21
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,016
|
movie_1
|
spider:train_spider.json:2439
|
How many movies were made before 2000?
|
SELECT count(*) FROM Movie WHERE YEAR < 2000
|
[
"How",
"many",
"movies",
"were",
"made",
"before",
"2000",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "movie"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "2000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,017
|
language_corpus
|
bird:train.json:5690
|
List the page id of wikipedia about Catalan language which have the appearance of the word 'decimal'?
|
SELECT T2.pid FROM words AS T1 INNER JOIN pages_words AS T2 ON T1.wid = T2.wid WHERE T1.word = 'decimal'
|
[
"List",
"the",
"page",
"i",
"d",
"of",
"wikipedia",
"about",
"Catalan",
"language",
"which",
"have",
"the",
"appearance",
"of",
"the",
"word",
"'",
"decimal",
"'",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "pages_words"
},
{
"id": 4,
"type": "value",
"value": "decimal"
},
{
"id": 1,
"type": "table",
"value": "words"
},
{
"id": 3,
"type": "column",
"value": "word"
},
{
"id": 0,
"type": "column",
"value": "pid"
},
{
"id": 5,
"type": "column",
"value": "wid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": [
3,
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
13,018
|
toxicology
|
bird:dev.json:316
|
Among the molecules which contain "c" element, which of them are not carcinogenic?
|
SELECT DISTINCT T1.molecule_id FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.element = 'c' AND T2.label = '-'
|
[
"Among",
"the",
"molecules",
"which",
"contain",
"\"",
"c",
"\"",
"element",
",",
"which",
"of",
"them",
"are",
"not",
"carcinogenic",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "molecule_id"
},
{
"id": 2,
"type": "table",
"value": "molecule"
},
{
"id": 3,
"type": "column",
"value": "element"
},
{
"id": 5,
"type": "column",
"value": "label"
},
{
"id": 1,
"type": "table",
"value": "atom"
},
{
"id": 4,
"type": "value",
"value": "c"
},
{
"id": 6,
"type": "value",
"value": "-"
}
] |
[
{
"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": [
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",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,019
|
country_language
|
bird:test.json:1373
|
What are the names of the countries, ordered descending by education score?
|
SELECT name FROM countries ORDER BY education_score DESC
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"countries",
",",
"ordered",
"descending",
"by",
"education",
"score",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "education_score"
},
{
"id": 0,
"type": "table",
"value": "countries"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11,
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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,020
|
address_1
|
bird:test.json:763
|
List all different states .
|
select distinct state from city
|
[
"List",
"all",
"different",
"states",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,021
|
gymnast
|
spider:train_spider.json:1759
|
Give the different hometowns of gymnasts that have a total point score of above 57.5.
|
SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T1.Total_Points > 57.5
|
[
"Give",
"the",
"different",
"hometowns",
"of",
"gymnasts",
"that",
"have",
"a",
"total",
"point",
"score",
"of",
"above",
"57.5",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "total_points"
},
{
"id": 5,
"type": "column",
"value": "gymnast_id"
},
{
"id": 6,
"type": "column",
"value": "people_id"
},
{
"id": 0,
"type": "column",
"value": "hometown"
},
{
"id": 1,
"type": "table",
"value": "gymnast"
},
{
"id": 2,
"type": "table",
"value": "people"
},
{
"id": 4,
"type": "value",
"value": "57.5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,022
|
movie_3
|
bird:train.json:9171
|
How many times is the number of films Gina DeGeneres acted in than Penelope Guinness?
|
SELECT CAST(SUM(IIF(T2.first_name = 'GINA' AND T2.last_name = 'DEGENERES', 1, 0)) AS REAL) * 100 / SUM(IIF(T2.first_name = 'PENELOPE' AND T2.last_name = 'GUINESS', 1, 0)) FROM film_actor AS T1 INNER JOIN actor AS T2 ON T1.actor_id = T2.actor_id
|
[
"How",
"many",
"times",
"is",
"the",
"number",
"of",
"films",
"Gina",
"DeGeneres",
"acted",
"in",
"than",
"Penelope",
"Guinness",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "film_actor"
},
{
"id": 6,
"type": "column",
"value": "first_name"
},
{
"id": 8,
"type": "column",
"value": "last_name"
},
{
"id": 11,
"type": "value",
"value": "DEGENERES"
},
{
"id": 2,
"type": "column",
"value": "actor_id"
},
{
"id": 7,
"type": "value",
"value": "PENELOPE"
},
{
"id": 9,
"type": "value",
"value": "GUINESS"
},
{
"id": 1,
"type": "table",
"value": "actor"
},
{
"id": 10,
"type": "value",
"value": "GINA"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
14
]
},
{
"entity_id": 10,
"token_idxs": [
8
]
},
{
"entity_id": 11,
"token_idxs": [
9
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
13,023
|
student_club
|
bird:dev.json:1419
|
What is the category of event which was taken place in 2020-03-24T12:00:00?
|
SELECT T2.category FROM event AS T1 INNER JOIN budget AS T2 ON T1.event_id = T2.link_to_event WHERE T1.event_date = '2020-03-24T12:00:00'
|
[
"What",
"is",
"the",
"category",
"of",
"event",
"which",
"was",
"taken",
"place",
"in",
"2020",
"-",
"03",
"-",
"24T12:00:00",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "2020-03-24T12:00:00"
},
{
"id": 6,
"type": "column",
"value": "link_to_event"
},
{
"id": 3,
"type": "column",
"value": "event_date"
},
{
"id": 0,
"type": "column",
"value": "category"
},
{
"id": 5,
"type": "column",
"value": "event_id"
},
{
"id": 2,
"type": "table",
"value": "budget"
},
{
"id": 1,
"type": "table",
"value": "event"
}
] |
[
{
"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": [
11,
12,
13,
14,
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,024
|
medicine_enzyme_interaction
|
spider:train_spider.json:946
|
What are the names and trade names of the medcines that are FDA approved?
|
SELECT name , trade_name FROM medicine WHERE FDA_approved = 'Yes'
|
[
"What",
"are",
"the",
"names",
"and",
"trade",
"names",
"of",
"the",
"medcines",
"that",
"are",
"FDA",
"approved",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "fda_approved"
},
{
"id": 2,
"type": "column",
"value": "trade_name"
},
{
"id": 0,
"type": "table",
"value": "medicine"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "Yes"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"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",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,025
|
codebase_comments
|
bird:train.json:630
|
What is the total processed time of all solutions from the repository with the most forks?
|
SELECT SUM(T2.ProcessedTime) FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T1.Forks = ( SELECT MAX(Forks) FROM Repo )
|
[
"What",
"is",
"the",
"total",
"processed",
"time",
"of",
"all",
"solutions",
"from",
"the",
"repository",
"with",
"the",
"most",
"forks",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "processedtime"
},
{
"id": 1,
"type": "table",
"value": "solution"
},
{
"id": 5,
"type": "column",
"value": "repoid"
},
{
"id": 2,
"type": "column",
"value": "forks"
},
{
"id": 0,
"type": "table",
"value": "repo"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,026
|
address_1
|
bird:test.json:823
|
What is the total distance between city BAL and all other cities.
|
SELECT sum(distance) FROM Direct_distance WHERE city1_code = "BAL"
|
[
"What",
"is",
"the",
"total",
"distance",
"between",
"city",
"BAL",
"and",
"all",
"other",
"cities",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "direct_distance"
},
{
"id": 1,
"type": "column",
"value": "city1_code"
},
{
"id": 3,
"type": "column",
"value": "distance"
},
{
"id": 2,
"type": "column",
"value": "BAL"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
13,027
|
chicago_crime
|
bird:train.json:8707
|
Which commander has had to deal with more cases of criminal sexual abuse?
|
SELECT T3.commander FROM IUCR AS T1 INNER JOIN Crime AS T2 ON T2.iucr_no = T1.iucr_no INNER JOIN District AS T3 ON T3.district_no = T2.district_no WHERE T1.secondary_description = 'CRIMINAL SEXUAL ABUSE' GROUP BY T3.commander ORDER BY COUNT(T1.secondary_description) DESC LIMIT 1
|
[
"Which",
"commander",
"has",
"had",
"to",
"deal",
"with",
"more",
"cases",
"of",
"criminal",
"sexual",
"abuse",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "secondary_description"
},
{
"id": 3,
"type": "value",
"value": "CRIMINAL SEXUAL ABUSE"
},
{
"id": 6,
"type": "column",
"value": "district_no"
},
{
"id": 0,
"type": "column",
"value": "commander"
},
{
"id": 1,
"type": "table",
"value": "district"
},
{
"id": 7,
"type": "column",
"value": "iucr_no"
},
{
"id": 5,
"type": "table",
"value": "crime"
},
{
"id": 4,
"type": "table",
"value": "iucr"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O"
] |
13,028
|
activity_1
|
spider:train_spider.json:6716
|
What is the total number of faculty members?
|
SELECT count(*) FROM Faculty
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"faculty",
"members",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "faculty"
}
] |
[
{
"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": []
},
{
"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"
] |
13,029
|
retail_world
|
bird:train.json:6614
|
The product 'Mozzarella di Giovanni' belongs in which category? Include the category's description as well.
|
SELECT T2.CategoryName, T2.Description FROM Products AS T1 INNER JOIN Categories AS T2 ON T1.CategoryID = T2.CategoryID WHERE T1.ProductName = 'Mozzarella di Giovanni'
|
[
"The",
"product",
"'",
"Mozzarella",
"di",
"Giovanni",
"'",
"belongs",
"in",
"which",
"category",
"?",
"Include",
"the",
"category",
"'s",
"description",
"as",
"well",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Mozzarella di Giovanni"
},
{
"id": 0,
"type": "column",
"value": "categoryname"
},
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 4,
"type": "column",
"value": "productname"
},
{
"id": 3,
"type": "table",
"value": "categories"
},
{
"id": 6,
"type": "column",
"value": "categoryid"
},
{
"id": 2,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": [
14,
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O"
] |
13,031
|
talkingdata
|
bird:train.json:1102
|
What is the age of the oldest male user of the app?
|
SELECT MAX(age) FROM gender_age WHERE gender = 'M'
|
[
"What",
"is",
"the",
"age",
"of",
"the",
"oldest",
"male",
"user",
"of",
"the",
"app",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "gender_age"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 3,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,032
|
world_development_indicators
|
bird:train.json:2204
|
Which form of government has more countries that have completed the actual external debt reporting between the two types of government accounting concepts, budgetary central government vs. consolidated central government?
|
SELECT SUM(CASE WHEN GovernmentAccountingConcept = 'Budgetary central government' THEN 1 ELSE 0 END), SUM(CASE WHEN GovernmentAccountingConcept = 'Consolidated central government' THEN 1 ELSE 0 END) central_nums FROM country WHERE ExternalDebtReportingStatus = 'Actual'
|
[
"Which",
"form",
"of",
"government",
"has",
"more",
"countries",
"that",
"have",
"completed",
"the",
"actual",
"external",
"debt",
"reporting",
"between",
"the",
"two",
"types",
"of",
"government",
"accounting",
"concepts",
",",
"budgetary",
"central",
"government",
"vs.",
"consolidated",
"central",
"government",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Consolidated central government"
},
{
"id": 6,
"type": "value",
"value": "Budgetary central government"
},
{
"id": 1,
"type": "column",
"value": "externaldebtreportingstatus"
},
{
"id": 5,
"type": "column",
"value": "governmentaccountingconcept"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "value",
"value": "Actual"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
20,
21,
22
]
},
{
"entity_id": 6,
"token_idxs": [
24,
25,
26
]
},
{
"entity_id": 7,
"token_idxs": [
28,
29,
30
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,033
|
video_game
|
bird:test.json:1948
|
What are the names and colleges of all players, ordered by rank of year descending?
|
SELECT Player_name , College FROM player ORDER BY Rank_of_the_year DESC
|
[
"What",
"are",
"the",
"names",
"and",
"colleges",
"of",
"all",
"players",
",",
"ordered",
"by",
"rank",
"of",
"year",
"descending",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "rank_of_the_year"
},
{
"id": 1,
"type": "column",
"value": "player_name"
},
{
"id": 2,
"type": "column",
"value": "college"
},
{
"id": 0,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
13,034
|
cinema
|
spider:train_spider.json:1941
|
Show each location and the number of cinemas there.
|
SELECT LOCATION , count(*) FROM cinema GROUP BY LOCATION
|
[
"Show",
"each",
"location",
"and",
"the",
"number",
"of",
"cinemas",
"there",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "cinema"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
13,035
|
allergy_1
|
spider:train_spider.json:515
|
Show all allergies with number of students affected.
|
SELECT Allergy , count(*) FROM Has_allergy GROUP BY Allergy
|
[
"Show",
"all",
"allergies",
"with",
"number",
"of",
"students",
"affected",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "has_allergy"
},
{
"id": 1,
"type": "column",
"value": "allergy"
}
] |
[
{
"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": []
},
{
"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"
] |
13,036
|
flight_1
|
spider:train_spider.json:346
|
What are the names and distances for all airplanes?
|
SELECT name , distance FROM Aircraft
|
[
"What",
"are",
"the",
"names",
"and",
"distances",
"for",
"all",
"airplanes",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "aircraft"
},
{
"id": 2,
"type": "column",
"value": "distance"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,037
|
news_report
|
spider:train_spider.json:2805
|
Show the names of journalists from "England" or "Wales".
|
SELECT Name FROM journalist WHERE Nationality = "England" OR Nationality = "Wales"
|
[
"Show",
"the",
"names",
"of",
"journalists",
"from",
"\"",
"England",
"\"",
"or",
"\"",
"Wales",
"\"",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "table",
"value": "journalist"
},
{
"id": 3,
"type": "column",
"value": "England"
},
{
"id": 4,
"type": "column",
"value": "Wales"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"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",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,038
|
company_employee
|
spider:train_spider.json:4102
|
Show the different headquarters and number of companies at each headquarter.
|
SELECT Headquarters , COUNT(*) FROM company GROUP BY Headquarters
|
[
"Show",
"the",
"different",
"headquarters",
"and",
"number",
"of",
"companies",
"at",
"each",
"headquarter",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "headquarters"
},
{
"id": 0,
"type": "table",
"value": "company"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
13,039
|
customers_and_invoices
|
spider:train_spider.json:1550
|
Count the number of customers who have an account.
|
SELECT count(DISTINCT customer_id) FROM Accounts
|
[
"Count",
"the",
"number",
"of",
"customers",
"who",
"have",
"an",
"account",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "accounts"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,040
|
advertising_agencies
|
bird:test.json:2139
|
What are the ids and details of the clients who have attended any meeting or have any invoice?
|
SELECT T1.client_id , T1.client_details FROM Clients AS T1 JOIN meetings AS T2 ON T1.client_id = T2.client_id UNION SELECT T1.client_id , T1.client_details FROM Clients AS T1 JOIN invoices AS T2 ON T1.client_id = T2.client_id
|
[
"What",
"are",
"the",
"ids",
"and",
"details",
"of",
"the",
"clients",
"who",
"have",
"attended",
"any",
"meeting",
"or",
"have",
"any",
"invoice",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "client_details"
},
{
"id": 0,
"type": "column",
"value": "client_id"
},
{
"id": 3,
"type": "table",
"value": "meetings"
},
{
"id": 4,
"type": "table",
"value": "invoices"
},
{
"id": 2,
"type": "table",
"value": "clients"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"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": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,041
|
hospital_1
|
spider:train_spider.json:3928
|
How many patients do each physician take care of? List their names and number of patients they take care of.
|
SELECT T1.name , count(*) FROM physician AS T1 JOIN patient AS T2 ON T1.employeeid = T2.PCP GROUP BY T1.employeeid
|
[
"How",
"many",
"patients",
"do",
"each",
"physician",
"take",
"care",
"of",
"?",
"List",
"their",
"names",
"and",
"number",
"of",
"patients",
"they",
"take",
"care",
"of",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "employeeid"
},
{
"id": 2,
"type": "table",
"value": "physician"
},
{
"id": 3,
"type": "table",
"value": "patient"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "pcp"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
13,044
|
food_inspection_2
|
bird:train.json:6155
|
List the full names of the employees who were responsible for inspecting Taqueria La Paz.
|
SELECT DISTINCT T3.first_name, T3.last_name FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN employee AS T3 ON T2.employee_id = T3.employee_id WHERE T1.dba_name = 'TAQUERIA LA PAZ'
|
[
"List",
"the",
"full",
"names",
"of",
"the",
"employees",
"who",
"were",
"responsible",
"for",
"inspecting",
"Taqueria",
"La",
"Paz",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "TAQUERIA LA PAZ"
},
{
"id": 5,
"type": "table",
"value": "establishment"
},
{
"id": 7,
"type": "column",
"value": "employee_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "table",
"value": "inspection"
},
{
"id": 8,
"type": "column",
"value": "license_no"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "employee"
},
{
"id": 3,
"type": "column",
"value": "dba_name"
}
] |
[
{
"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": [
12,
13,
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,045
|
public_review_platform
|
bird:train.json:4025
|
Among the businesses with average rating, how many business has attribute of full_bar.
|
SELECT COUNT(T1.business_id) FROM Business_Attributes AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T1.attribute_value = 'full_bar'
|
[
"Among",
"the",
"businesses",
"with",
"average",
"rating",
",",
"how",
"many",
"business",
"has",
"attribute",
"of",
"full_bar",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "business_attributes"
},
{
"id": 2,
"type": "column",
"value": "attribute_value"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "business"
},
{
"id": 3,
"type": "value",
"value": "full_bar"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,046
|
mondial_geo
|
bird:train.json:8224
|
Provide the country with its full name which has the most ethnic group? List them all ethnic group together with its percentage.
|
SELECT T1.Name, T2.Name, T2.Percentage FROM country AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Code = T2.Country WHERE T1.Name = ( SELECT T1.Name FROM country AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Code = T2.Country GROUP BY T1.Name ORDER BY COUNT(T2.Name) DESC LIMIT 1 ) GROUP BY T1.Name, T2.Name, T2.Percentage
|
[
"Provide",
"the",
"country",
"with",
"its",
"full",
"name",
"which",
"has",
"the",
"most",
"ethnic",
"group",
"?",
"List",
"them",
"all",
"ethnic",
"group",
"together",
"with",
"its",
"percentage",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "ethnicgroup"
},
{
"id": 1,
"type": "column",
"value": "percentage"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
22
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
17,
18
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,047
|
document_management
|
spider:train_spider.json:4531
|
How many users are logged in?
|
SELECT count(*) FROM users WHERE user_login = 1
|
[
"How",
"many",
"users",
"are",
"logged",
"in",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "user_login"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
13,048
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5131
|
Find the description and code of the service type that is performed the most times.
|
SELECT T1.Service_Type_Description , T1.Service_Type_Code FROM Ref_Service_Types AS T1 JOIN Services AS T2 ON T1.Service_Type_Code = T2.Service_Type_Code GROUP BY T1.Service_Type_Code ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Find",
"the",
"description",
"and",
"code",
"of",
"the",
"service",
"type",
"that",
"is",
"performed",
"the",
"most",
"times",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "service_type_description"
},
{
"id": 0,
"type": "column",
"value": "service_type_code"
},
{
"id": 2,
"type": "table",
"value": "ref_service_types"
},
{
"id": 3,
"type": "table",
"value": "services"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1,
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,049
|
language_corpus
|
bird:train.json:5818
|
Among the biwords pairs with "àbac" as its first word, how many of them have an occurrence of over 10?
|
SELECT COUNT(T2.w2nd) FROM words AS T1 INNER JOIN biwords AS T2 ON T1.wid = T2.w1st WHERE T1.word = 'àbac' AND T2.occurrences > 10
|
[
"Among",
"the",
"biwords",
"pairs",
"with",
"\"",
"àbac",
"\"",
"as",
"its",
"first",
"word",
",",
"how",
"many",
"of",
"them",
"have",
"an",
"occurrence",
"of",
"over",
"10",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "occurrences"
},
{
"id": 1,
"type": "table",
"value": "biwords"
},
{
"id": 0,
"type": "table",
"value": "words"
},
{
"id": 2,
"type": "column",
"value": "w2nd"
},
{
"id": 4,
"type": "column",
"value": "w1st"
},
{
"id": 5,
"type": "column",
"value": "word"
},
{
"id": 6,
"type": "value",
"value": "àbac"
},
{
"id": 3,
"type": "column",
"value": "wid"
},
{
"id": 8,
"type": "value",
"value": "10"
}
] |
[
{
"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": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": [
19
]
},
{
"entity_id": 8,
"token_idxs": [
22
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,050
|
university_basketball
|
spider:train_spider.json:994
|
What are the all games score and location of the school called Clemson?
|
SELECT t2.All_Games , t1.location FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id WHERE team_name = 'Clemson'
|
[
"What",
"are",
"the",
"all",
"games",
"score",
"and",
"location",
"of",
"the",
"school",
"called",
"Clemson",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "basketball_match"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 0,
"type": "column",
"value": "all_games"
},
{
"id": 4,
"type": "column",
"value": "team_name"
},
{
"id": 6,
"type": "column",
"value": "school_id"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 5,
"type": "value",
"value": "Clemson"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,051
|
public_review_platform
|
bird:train.json:3866
|
Among the Yelp_Business in Arizona, how many of them closes at 12PM on Sundays?
|
SELECT COUNT(T1.business_id) FROM Business_Hours AS T1 INNER JOIN Days AS T2 ON T1.day_id = T2.day_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id WHERE T2.day_of_week LIKE 'Sunday' AND T1.closing_time LIKE '12PM' AND T3.state LIKE 'AZ'
|
[
"Among",
"the",
"Yelp_Business",
"in",
"Arizona",
",",
"how",
"many",
"of",
"them",
"closes",
"at",
"12PM",
"on",
"Sundays",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "business_hours"
},
{
"id": 6,
"type": "column",
"value": "closing_time"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 4,
"type": "column",
"value": "day_of_week"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 5,
"type": "value",
"value": "Sunday"
},
{
"id": 10,
"type": "column",
"value": "day_id"
},
{
"id": 8,
"type": "column",
"value": "state"
},
{
"id": 3,
"type": "table",
"value": "days"
},
{
"id": 7,
"type": "value",
"value": "12PM"
},
{
"id": 9,
"type": "value",
"value": "AZ"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O"
] |
13,052
|
european_football_1
|
bird:train.json:2745
|
What is the percentage whereby the away team scored 2 goals during the 2017 seasons?
|
SELECT CAST(SUM(CASE WHEN FTAG = 2 THEN 1 ELSE 0 END) / COUNT(FTAG) AS REAL) * 100 FROM matchs WHERE season = 2017
|
[
"What",
"is",
"the",
"percentage",
"whereby",
"the",
"away",
"team",
"scored",
"2",
"goals",
"during",
"the",
"2017",
"seasons",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "matchs"
},
{
"id": 1,
"type": "column",
"value": "season"
},
{
"id": 2,
"type": "value",
"value": "2017"
},
{
"id": 4,
"type": "column",
"value": "ftag"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"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": [
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": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
13,053
|
insurance_fnol
|
spider:train_spider.json:905
|
What is the effective date of the claim that has the largest amount of total settlement?
|
SELECT t1.Effective_Date FROM claims AS t1 JOIN settlements AS t2 ON t1.claim_id = t2.claim_id GROUP BY t1.claim_id ORDER BY sum(t2.settlement_amount) DESC LIMIT 1
|
[
"What",
"is",
"the",
"effective",
"date",
"of",
"the",
"claim",
"that",
"has",
"the",
"largest",
"amount",
"of",
"total",
"settlement",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "settlement_amount"
},
{
"id": 1,
"type": "column",
"value": "effective_date"
},
{
"id": 3,
"type": "table",
"value": "settlements"
},
{
"id": 0,
"type": "column",
"value": "claim_id"
},
{
"id": 2,
"type": "table",
"value": "claims"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,054
|
formula_1
|
bird:dev.json:915
|
Which country is the oldest driver from?
|
SELECT nationality FROM drivers WHERE dob IS NOT NULL ORDER BY dob ASC LIMIT 1
|
[
"Which",
"country",
"is",
"the",
"oldest",
"driver",
"from",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "table",
"value": "drivers"
},
{
"id": 2,
"type": "column",
"value": "dob"
}
] |
[
{
"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": []
},
{
"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"
] |
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