question_id
int64 0
16.1k
| db_id
stringclasses 259
values | dber_id
stringlengths 15
29
| question
stringlengths 16
325
| SQL
stringlengths 18
1.25k
| tokens
listlengths 4
62
| entities
listlengths 0
21
| entity_to_token
listlengths 20
20
| dber_tags
listlengths 4
62
|
|---|---|---|---|---|---|---|---|---|
425
|
planet_1
|
bird:test.json:1881
|
Who sent most number of packages? List client name and number of packages sent by that client.
|
SELECT T2.Name , count(*) FROM PACKAGE AS T1 JOIN Client AS T2 ON T1.Sender = T2.AccountNumber GROUP BY T1.Sender ORDER BY count(*) DESC LIMIT 1;
|
[
"Who",
"sent",
"most",
"number",
"of",
"packages",
"?",
"List",
"client",
"name",
"and",
"number",
"of",
"packages",
"sent",
"by",
"that",
"client",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "accountnumber"
},
{
"id": 2,
"type": "table",
"value": "package"
},
{
"id": 0,
"type": "column",
"value": "sender"
},
{
"id": 3,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
426
|
solvency_ii
|
spider:train_spider.json:4588
|
What is the name of the product with the highest price?
|
SELECT Product_Name FROM Products ORDER BY Product_Price DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"product",
"with",
"the",
"highest",
"price",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "product_price"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"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",
"O",
"O",
"O"
] |
427
|
thrombosis_prediction
|
bird:dev.json:1157
|
For patients with severe degree of thrombosis, list their ID, sex and disease the patient is diagnosed with.
|
SELECT DISTINCT T1.ID, T1.SEX, T1.Diagnosis FROM Patient AS T1 INNER JOIN Examination AS T2 ON T1.ID = T2.ID WHERE T2.Thrombosis = 2
|
[
"For",
"patients",
"with",
"severe",
"degree",
"of",
"thrombosis",
",",
"list",
"their",
"ID",
",",
"sex",
"and",
"disease",
"the",
"patient",
"is",
"diagnosed",
"with",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "examination"
},
{
"id": 5,
"type": "column",
"value": "thrombosis"
},
{
"id": 2,
"type": "column",
"value": "diagnosis"
},
{
"id": 3,
"type": "table",
"value": "patient"
},
{
"id": 1,
"type": "column",
"value": "sex"
},
{
"id": 0,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O"
] |
428
|
cre_Doc_and_collections
|
bird:test.json:673
|
What is the owner of document with the Description 'Braeden Collection'?
|
SELECT OWNER FROM Document_Objects WHERE Description = 'Braeden Collection'
|
[
"What",
"is",
"the",
"owner",
"of",
"document",
"with",
"the",
"Description",
"'",
"Braeden",
"Collection",
"'",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Braeden Collection"
},
{
"id": 0,
"type": "table",
"value": "document_objects"
},
{
"id": 2,
"type": "column",
"value": "description"
},
{
"id": 1,
"type": "column",
"value": "owner"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
429
|
government_shift
|
bird:test.json:377
|
Find the name of all the services which either have been used by customer "Hardy Kutch" or have been rated as "good" in one of the customer interactions.
|
SELECT DISTINCT t3.service_details FROM customers AS t1 JOIN customers_and_services AS t2 ON t1.customer_id = t2.customer_id JOIN services AS t3 ON t2.service_id = t3.service_id JOIN customer_interactions AS t4 ON t3.service_id = t4.service_id WHERE t1.customer_details = "Hardy Kutch" OR t4.services_and_channels_details = "good"
|
[
"Find",
"the",
"name",
"of",
"all",
"the",
"services",
"which",
"either",
"have",
"been",
"used",
"by",
"customer",
"\"",
"Hardy",
"Kutch",
"\"",
"or",
"have",
"been",
"rated",
"as",
"\"",
"good",
"\"",
"in",
"one",
"of",
"the",
"customer",
"interactions",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "services_and_channels_details"
},
{
"id": 9,
"type": "table",
"value": "customers_and_services"
},
{
"id": 1,
"type": "table",
"value": "customer_interactions"
},
{
"id": 4,
"type": "column",
"value": "customer_details"
},
{
"id": 0,
"type": "column",
"value": "service_details"
},
{
"id": 5,
"type": "column",
"value": "Hardy Kutch"
},
{
"id": 10,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "column",
"value": "service_id"
},
{
"id": 8,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "services"
},
{
"id": 7,
"type": "column",
"value": "good"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
31
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
15,
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
24
]
},
{
"entity_id": 8,
"token_idxs": [
30
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O"
] |
430
|
codebase_comments
|
bird:train.json:638
|
List all the solutions ids of the repository with "636430969128176000" processed time
|
SELECT T2.Id FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T1.ProcessedTime = 636430969128176000
|
[
"List",
"all",
"the",
"solutions",
"ids",
"of",
"the",
"repository",
"with",
"\"",
"636430969128176000",
"\"",
"processed",
"time"
] |
[
{
"id": 4,
"type": "value",
"value": "636430969128176000"
},
{
"id": 3,
"type": "column",
"value": "processedtime"
},
{
"id": 2,
"type": "table",
"value": "solution"
},
{
"id": 5,
"type": "column",
"value": "repoid"
},
{
"id": 1,
"type": "table",
"value": "repo"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN"
] |
431
|
sing_contest
|
bird:test.json:759
|
Which song names have the substring "Is"?
|
SELECT name FROM songs WHERE name LIKE "%Is%"
|
[
"Which",
"song",
"names",
"have",
"the",
"substring",
"\"",
"Is",
"\"",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "songs"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "%Is%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
432
|
public_review_platform
|
bird:train.json:4132
|
Among the active businesses located at Goodyear, AZ, list the category and atrributes of business with a high review count.
|
SELECT T3.category_name, T5.attribute_name FROM Business AS T1 INNER JOIN Business_Categories AS T2 ON T1.business_id = T2.business_id INNER JOIN Categories AS T3 ON T2.category_id = T3.category_id INNER JOIN Business_Attributes AS T4 ON T1.business_id = T4.business_id INNER JOIN Attributes AS T5 ON T4.attribute_id = T5.attribute_id WHERE T1.review_count = 'High' AND T1.city = 'Goodyear' AND T1.state = 'AZ' AND T1.active = 'true'
|
[
"Among",
"the",
"active",
"businesses",
"located",
"at",
"Goodyear",
",",
"AZ",
",",
"list",
"the",
"category",
"and",
"atrributes",
"of",
"business",
"with",
"a",
"high",
"review",
"count",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "business_attributes"
},
{
"id": 16,
"type": "table",
"value": "business_categories"
},
{
"id": 1,
"type": "column",
"value": "attribute_name"
},
{
"id": 0,
"type": "column",
"value": "category_name"
},
{
"id": 4,
"type": "column",
"value": "attribute_id"
},
{
"id": 5,
"type": "column",
"value": "review_count"
},
{
"id": 14,
"type": "column",
"value": "business_id"
},
{
"id": 17,
"type": "column",
"value": "category_id"
},
{
"id": 2,
"type": "table",
"value": "attributes"
},
{
"id": 13,
"type": "table",
"value": "categories"
},
{
"id": 8,
"type": "value",
"value": "Goodyear"
},
{
"id": 15,
"type": "table",
"value": "business"
},
{
"id": 11,
"type": "column",
"value": "active"
},
{
"id": 9,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "value",
"value": "High"
},
{
"id": 7,
"type": "column",
"value": "city"
},
{
"id": 12,
"type": "value",
"value": "true"
},
{
"id": 10,
"type": "value",
"value": "AZ"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
20,
21
]
},
{
"entity_id": 6,
"token_idxs": [
19
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
6
]
},
{
"entity_id": 9,
"token_idxs": [
10,
11
]
},
{
"entity_id": 10,
"token_idxs": [
8
]
},
{
"entity_id": 11,
"token_idxs": [
2
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": [
12
]
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": [
16
]
},
{
"entity_id": 16,
"token_idxs": [
3
]
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
433
|
codebase_comments
|
bird:train.json:566
|
How many English language codes whose comments for the method are in the XML format?
|
SELECT COUNT(Lang) FROM Method WHERE Lang = 'en' AND CommentIsXml = 1
|
[
"How",
"many",
"English",
"language",
"codes",
"whose",
"comments",
"for",
"the",
"method",
"are",
"in",
"the",
"XML",
"format",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "commentisxml"
},
{
"id": 0,
"type": "table",
"value": "method"
},
{
"id": 1,
"type": "column",
"value": "lang"
},
{
"id": 2,
"type": "value",
"value": "en"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
435
|
manufactory_1
|
spider:train_spider.json:5277
|
What are the names and headquarters of all manufacturers, ordered by revenue descending?
|
SELECT name , headquarter FROM manufacturers ORDER BY revenue DESC
|
[
"What",
"are",
"the",
"names",
"and",
"headquarters",
"of",
"all",
"manufacturers",
",",
"ordered",
"by",
"revenue",
"descending",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "manufacturers"
},
{
"id": 2,
"type": "column",
"value": "headquarter"
},
{
"id": 3,
"type": "column",
"value": "revenue"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
436
|
manufactory_1
|
spider:train_spider.json:5327
|
What are the names of products with price at most 200?
|
SELECT name FROM products WHERE price <= 200
|
[
"What",
"are",
"the",
"names",
"of",
"products",
"with",
"price",
"at",
"most",
"200",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "200"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
437
|
law_episode
|
bird:train.json:1305
|
How many votes did the episode titled Juvenile get?
|
SELECT SUM(T2.votes) FROM Episode AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Juvenile'
|
[
"How",
"many",
"votes",
"did",
"the",
"episode",
"titled",
"Juvenile",
"get",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "episode_id"
},
{
"id": 3,
"type": "value",
"value": "Juvenile"
},
{
"id": 0,
"type": "table",
"value": "episode"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "column",
"value": "votes"
},
{
"id": 1,
"type": "table",
"value": "vote"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"O"
] |
438
|
works_cycles
|
bird:train.json:7222
|
How many customers are there in Canada?
|
SELECT COUNT(T2.CustomerID) FROM SalesTerritory AS T1 INNER JOIN Customer AS T2 ON T1.TerritoryID = T2.TerritoryID WHERE T1.Name = 'Canada'
|
[
"How",
"many",
"customers",
"are",
"there",
"in",
"Canada",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "salesterritory"
},
{
"id": 5,
"type": "column",
"value": "territoryid"
},
{
"id": 4,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 3,
"type": "value",
"value": "Canada"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
439
|
simpson_episodes
|
bird:train.json:4303
|
Which country has the tallest person in the crew?
|
SELECT birth_country FROM Person ORDER BY height_meters DESC LIMIT 1;
|
[
"Which",
"country",
"has",
"the",
"tallest",
"person",
"in",
"the",
"crew",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "birth_country"
},
{
"id": 2,
"type": "column",
"value": "height_meters"
},
{
"id": 0,
"type": "table",
"value": "person"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
440
|
food_inspection
|
bird:train.json:8850
|
List the violation type ID of business with business ID from 30 to 50 and located at 747 IRVING St, San Francisco.
|
SELECT DISTINCT T1.violation_type_id FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.business_id BETWEEN 30 AND 50 AND T2.address = '747 IRVING St' AND T2.city = 'San Francisco'
|
[
"List",
"the",
"violation",
"type",
"ID",
"of",
"business",
"with",
"business",
"ID",
"from",
"30",
"to",
"50",
"and",
"located",
"at",
"747",
"IRVING",
"St",
",",
"San",
"Francisco",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "violation_type_id"
},
{
"id": 7,
"type": "value",
"value": "747 IRVING St"
},
{
"id": 9,
"type": "value",
"value": "San Francisco"
},
{
"id": 3,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "violations"
},
{
"id": 2,
"type": "table",
"value": "businesses"
},
{
"id": 6,
"type": "column",
"value": "address"
},
{
"id": 8,
"type": "column",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "30"
},
{
"id": 5,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
17,
18,
19
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
21,
22
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
442
|
allergy_1
|
spider:train_spider.json:474
|
How many students are 18 years old?
|
SELECT count(*) FROM Student WHERE age = 18
|
[
"How",
"many",
"students",
"are",
"18",
"years",
"old",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "18"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O"
] |
443
|
retail_world
|
bird:train.json:6660
|
Give the phone number of the customer who placed the order id 10264.
|
SELECT T1.Phone FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.OrderID = 10264
|
[
"Give",
"the",
"phone",
"number",
"of",
"the",
"customer",
"who",
"placed",
"the",
"order",
"i",
"d",
"10264",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "column",
"value": "orderid"
},
{
"id": 2,
"type": "table",
"value": "orders"
},
{
"id": 0,
"type": "column",
"value": "phone"
},
{
"id": 4,
"type": "value",
"value": "10264"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
445
|
movie_3
|
bird:train.json:9328
|
Please provide the address of the customer whose first name is SUSAN with the postal code 77948.
|
SELECT T1.address FROM address AS T1 INNER JOIN customer AS T2 ON T1.address_id = T2.address_id WHERE T2.first_name = 'SUSAN' AND T1.postal_code = 77948
|
[
"Please",
"provide",
"the",
"address",
"of",
"the",
"customer",
"whose",
"first",
"name",
"is",
"SUSAN",
"with",
"the",
"postal",
"code",
"77948",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "postal_code"
},
{
"id": 3,
"type": "column",
"value": "address_id"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "address"
},
{
"id": 1,
"type": "table",
"value": "address"
},
{
"id": 5,
"type": "value",
"value": "SUSAN"
},
{
"id": 7,
"type": "value",
"value": "77948"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
14,
15
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
446
|
financial
|
bird:dev.json:132
|
What is the average loan amount by male borrowers?
|
SELECT AVG(T4.amount) FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T3 ON T2.account_id = T3.account_id INNER JOIN loan AS T4 ON T3.account_id = T4.account_id WHERE T1.gender = 'M'
|
[
"What",
"is",
"the",
"average",
"loan",
"amount",
"by",
"male",
"borrowers",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "account_id"
},
{
"id": 8,
"type": "column",
"value": "client_id"
},
{
"id": 4,
"type": "table",
"value": "account"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 3,
"type": "column",
"value": "amount"
},
{
"id": 6,
"type": "table",
"value": "client"
},
{
"id": 0,
"type": "table",
"value": "loan"
},
{
"id": 7,
"type": "table",
"value": "disp"
},
{
"id": 2,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
1
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
447
|
movie_1
|
spider:train_spider.json:2523
|
What are the ids of all reviewers who have not given 4 stars at least once?
|
SELECT rID FROM Rating WHERE stars != 4
|
[
"What",
"are",
"the",
"ids",
"of",
"all",
"reviewers",
"who",
"have",
"not",
"given",
"4",
"stars",
"at",
"least",
"once",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "rating"
},
{
"id": 2,
"type": "column",
"value": "stars"
},
{
"id": 1,
"type": "column",
"value": "rid"
},
{
"id": 3,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
448
|
network_2
|
spider:train_spider.json:4466
|
Who has friends that are older than the average age? Print their friends and their ages as well
|
SELECT DISTINCT T2.name , T2.friend , T1.age FROM Person AS T1 JOIN PersonFriend AS T2 ON T1.name = T2.friend WHERE T1.age > (SELECT avg(age) FROM person)
|
[
"Who",
"has",
"friends",
"that",
"are",
"older",
"than",
"the",
"average",
"age",
"?",
"Print",
"their",
"friends",
"and",
"their",
"ages",
"as",
"well"
] |
[
{
"id": 4,
"type": "table",
"value": "personfriend"
},
{
"id": 1,
"type": "column",
"value": "friend"
},
{
"id": 3,
"type": "table",
"value": "person"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
449
|
soccer_2016
|
bird:train.json:1795
|
Please list the names of the players who use the right hand as their batting hand and are from Australia.
|
SELECT T2.Player_Name FROM Country AS T1 INNER JOIN Player AS T2 ON T2.Country_Name = T1.Country_id INNER JOIN Batting_Style AS T3 ON T2.Batting_hand = T3.Batting_Id WHERE T1.Country_Name = 'Australia' AND T3.Batting_Hand = 'Right-hand bat'
|
[
"Please",
"list",
"the",
"names",
"of",
"the",
"players",
"who",
"use",
"the",
"right",
"hand",
"as",
"their",
"batting",
"hand",
"and",
"are",
"from",
"Australia",
"."
] |
[
{
"id": 8,
"type": "value",
"value": "Right-hand bat"
},
{
"id": 1,
"type": "table",
"value": "batting_style"
},
{
"id": 4,
"type": "column",
"value": "batting_hand"
},
{
"id": 6,
"type": "column",
"value": "country_name"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 5,
"type": "column",
"value": "batting_id"
},
{
"id": 9,
"type": "column",
"value": "country_id"
},
{
"id": 7,
"type": "value",
"value": "Australia"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
19
]
},
{
"entity_id": 8,
"token_idxs": [
10,
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",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
450
|
sales_in_weather
|
bird:train.json:8204
|
How many units of item 7 have been sold by store 7 when the snow is less than 5 inches?
|
SELECT SUM(units) FROM weather AS T1 INNER JOIN relation AS T2 ON T1.station_nbr = T2.station_nbr INNER JOIN sales_in_weather AS T3 ON T2.store_nbr = T3.store_nbr WHERE T2.store_nbr = 7 AND T3.item_nbr = 7 AND T1.snowfall < 5
|
[
"How",
"many",
"units",
"of",
"item",
"7",
"have",
"been",
"sold",
"by",
"store",
"7",
"when",
"the",
"snow",
"is",
"less",
"than",
"5",
"inches",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "sales_in_weather"
},
{
"id": 9,
"type": "column",
"value": "station_nbr"
},
{
"id": 4,
"type": "column",
"value": "store_nbr"
},
{
"id": 3,
"type": "table",
"value": "relation"
},
{
"id": 6,
"type": "column",
"value": "item_nbr"
},
{
"id": 7,
"type": "column",
"value": "snowfall"
},
{
"id": 2,
"type": "table",
"value": "weather"
},
{
"id": 1,
"type": "column",
"value": "units"
},
{
"id": 5,
"type": "value",
"value": "7"
},
{
"id": 8,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
12,
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": [
18
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
451
|
world
|
bird:train.json:7916
|
Among the cities with a population between 140000 and 150000, list the country that has life expectancy greater than 80% life expectancy of all countries.
|
SELECT T2.Name FROM City AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T1.Population BETWEEN 140000 AND 150000 GROUP BY T2.Name, LifeExpectancy HAVING LifeExpectancy < ( SELECT AVG(LifeExpectancy) FROM Country ) * 0.8
|
[
"Among",
"the",
"cities",
"with",
"a",
"population",
"between",
"140000",
"and",
"150000",
",",
"list",
"the",
"country",
"that",
"has",
"life",
"expectancy",
"greater",
"than",
"80",
"%",
"life",
"expectancy",
"of",
"all",
"countries",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "lifeexpectancy"
},
{
"id": 7,
"type": "column",
"value": "countrycode"
},
{
"id": 4,
"type": "column",
"value": "population"
},
{
"id": 3,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "value",
"value": "140000"
},
{
"id": 6,
"type": "value",
"value": "150000"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 8,
"type": "column",
"value": "code"
},
{
"id": 9,
"type": "value",
"value": "0.8"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
16,
17
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
453
|
regional_sales
|
bird:train.json:2629
|
What is the average unit price of a Cookware product?
|
SELECT AVG(REPLACE(T1.`Unit Price`, ',', '')) FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID WHERE T2.`Product Name` = 'Cookware'
|
[
"What",
"is",
"the",
"average",
"unit",
"price",
"of",
"a",
"Cookware",
"product",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 2,
"type": "column",
"value": "Product Name"
},
{
"id": 5,
"type": "column",
"value": "_productid"
},
{
"id": 6,
"type": "column",
"value": "Unit Price"
},
{
"id": 4,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "value",
"value": "Cookware"
},
{
"id": 7,
"type": "value",
"value": ","
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4,
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
454
|
legislator
|
bird:train.json:4755
|
Among all the current legislators whose religion is Roman Catholic, what is the percentage of the ones without an instagram account?
|
SELECT CAST(SUM(CASE WHEN T1.instagram IS NULL THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM `social-media` AS T1 INNER JOIN current AS T2 ON T1.bioguide = T2.bioguide_id WHERE T2.religion_bio = 'Roman Catholic'
|
[
"Among",
"all",
"the",
"current",
"legislators",
"whose",
"religion",
"is",
"Roman",
"Catholic",
",",
"what",
"is",
"the",
"percentage",
"of",
"the",
"ones",
"without",
"an",
"instagram",
"account",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Roman Catholic"
},
{
"id": 0,
"type": "table",
"value": "social-media"
},
{
"id": 2,
"type": "column",
"value": "religion_bio"
},
{
"id": 5,
"type": "column",
"value": "bioguide_id"
},
{
"id": 9,
"type": "column",
"value": "instagram"
},
{
"id": 4,
"type": "column",
"value": "bioguide"
},
{
"id": 1,
"type": "table",
"value": "current"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
20
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
455
|
codebase_community
|
bird:dev.json:602
|
List out all post ID with score more than 60 and list out all the user ID that created these post.
|
SELECT PostId, UserId FROM postHistory WHERE PostId IN ( SELECT Id FROM posts WHERE Score > 60 )
|
[
"List",
"out",
"all",
"post",
"ID",
"with",
"score",
"more",
"than",
"60",
"and",
"list",
"out",
"all",
"the",
"user",
"ID",
"that",
"created",
"these",
"post",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "posthistory"
},
{
"id": 1,
"type": "column",
"value": "postid"
},
{
"id": 2,
"type": "column",
"value": "userid"
},
{
"id": 3,
"type": "table",
"value": "posts"
},
{
"id": 5,
"type": "column",
"value": "score"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "60"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
15,
16
]
},
{
"entity_id": 3,
"token_idxs": [
20
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"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",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
456
|
driving_school
|
spider:train_spider.json:6665
|
What is the status code, phone number, and email address of the customer whose last name is Kohler or whose first name is Marina?
|
SELECT customer_status_code , cell_mobile_phone_number , email_address FROM Customers WHERE first_name = "Marina" OR last_name = "Kohler"
|
[
"What",
"is",
"the",
"status",
"code",
",",
"phone",
"number",
",",
"and",
"email",
"address",
"of",
"the",
"customer",
"whose",
"last",
"name",
"is",
"Kohler",
"or",
"whose",
"first",
"name",
"is",
"Marina",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "cell_mobile_phone_number"
},
{
"id": 1,
"type": "column",
"value": "customer_status_code"
},
{
"id": 3,
"type": "column",
"value": "email_address"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "Marina"
},
{
"id": 7,
"type": "column",
"value": "Kohler"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
22,
23
]
},
{
"entity_id": 5,
"token_idxs": [
25
]
},
{
"entity_id": 6,
"token_idxs": [
16,
17
]
},
{
"entity_id": 7,
"token_idxs": [
19
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O"
] |
457
|
activity_1
|
spider:train_spider.json:6771
|
Show the ids of the faculty who don't participate in any activity.
|
SELECT FacID FROM Faculty EXCEPT SELECT FacID FROM Faculty_participates_in
|
[
"Show",
"the",
"ids",
"of",
"the",
"faculty",
"who",
"do",
"n't",
"participate",
"in",
"any",
"activity",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "faculty_participates_in"
},
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 2,
"type": "column",
"value": "facid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
458
|
cre_Doc_Workflow
|
bird:test.json:2019
|
Show the names and other details for all authors.
|
SELECT author_name , other_details FROM Authors
|
[
"Show",
"the",
"names",
"and",
"other",
"details",
"for",
"all",
"authors",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "other_details"
},
{
"id": 1,
"type": "column",
"value": "author_name"
},
{
"id": 0,
"type": "table",
"value": "authors"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
459
|
advertising_agencies
|
bird:test.json:2062
|
How many clients are there?
|
SELECT count(*) FROM Clients
|
[
"How",
"many",
"clients",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "clients"
}
] |
[
{
"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"
] |
460
|
books
|
bird:train.json:5921
|
Please list the titles of all the books in British English.
|
SELECT T1.title FROM book AS T1 INNER JOIN book_language AS T2 ON T1.language_id = T2.language_id WHERE T2.language_name = 'British English'
|
[
"Please",
"list",
"the",
"titles",
"of",
"all",
"the",
"books",
"in",
"British",
"English",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "British English"
},
{
"id": 2,
"type": "table",
"value": "book_language"
},
{
"id": 3,
"type": "column",
"value": "language_name"
},
{
"id": 5,
"type": "column",
"value": "language_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9,
10
]
},
{
"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",
"B-VALUE",
"I-VALUE",
"O"
] |
461
|
software_company
|
bird:train.json:8582
|
Find the response status to customer whose geographic ID of 134.
|
SELECT T2.RESPONSE FROM Customers AS T1 INNER JOIN mailings3 AS T2 ON T1.ID = T2.REFID WHERE T1.GEOID = 134
|
[
"Find",
"the",
"response",
"status",
"to",
"customer",
"whose",
"geographic",
"ID",
"of",
"134",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "mailings3"
},
{
"id": 0,
"type": "column",
"value": "response"
},
{
"id": 3,
"type": "column",
"value": "geoid"
},
{
"id": 6,
"type": "column",
"value": "refid"
},
{
"id": 4,
"type": "value",
"value": "134"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"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": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
0
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
462
|
student_club
|
bird:dev.json:1368
|
What does the person with the phone number "809-555-3360" major in?
|
SELECT T2.major_name FROM member AS T1 INNER JOIN major AS T2 ON T1.link_to_major = T2.major_id WHERE T1.phone = '809-555-3360'
|
[
"What",
"does",
"the",
"person",
"with",
"the",
"phone",
"number",
"\"",
"809",
"-",
"555",
"-",
"3360",
"\"",
"major",
"in",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "link_to_major"
},
{
"id": 4,
"type": "value",
"value": "809-555-3360"
},
{
"id": 0,
"type": "column",
"value": "major_name"
},
{
"id": 6,
"type": "column",
"value": "major_id"
},
{
"id": 1,
"type": "table",
"value": "member"
},
{
"id": 2,
"type": "table",
"value": "major"
},
{
"id": 3,
"type": "column",
"value": "phone"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
9,
10,
11,
12,
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O",
"O"
] |
463
|
wine_1
|
spider:train_spider.json:6525
|
List the names and scores of all wines.
|
SELECT Name , Score FROM WINE
|
[
"List",
"the",
"names",
"and",
"scores",
"of",
"all",
"wines",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "score"
},
{
"id": 0,
"type": "table",
"value": "wine"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
464
|
customers_and_orders
|
bird:test.json:292
|
What were the ids, dates, and status codes for orders made by Jeromy?
|
SELECT order_id , order_date , order_status_code FROM Customer_orders AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id WHERE T2.customer_name = "Jeromy"
|
[
"What",
"were",
"the",
"ids",
",",
"dates",
",",
"and",
"status",
"codes",
"for",
"orders",
"made",
"by",
"Jeromy",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "order_status_code"
},
{
"id": 3,
"type": "table",
"value": "customer_orders"
},
{
"id": 5,
"type": "column",
"value": "customer_name"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "column",
"value": "order_date"
},
{
"id": 4,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "column",
"value": "order_id"
},
{
"id": 6,
"type": "column",
"value": "Jeromy"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
465
|
e_learning
|
spider:train_spider.json:3833
|
On what dates did the student whose personal name is "Karson" enroll in and complete the courses?
|
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"
|
[
"On",
"what",
"dates",
"did",
"the",
"student",
"whose",
"personal",
"name",
"is",
"\"",
"Karson",
"\"",
"enroll",
"in",
"and",
"complete",
"the",
"courses",
"?"
] |
[
{
"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": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
7,
8
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
466
|
app_store
|
bird:train.json:2543
|
List all the comments on the lowest rated Mature 17+ app.
|
SELECT T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1."Content Rating" = 'Mature 17+' ORDER BY T1.Rating LIMIT 1
|
[
"List",
"all",
"the",
"comments",
"on",
"the",
"lowest",
"rated",
"Mature",
"17",
"+",
"app",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "translated_review"
},
{
"id": 3,
"type": "column",
"value": "Content Rating"
},
{
"id": 2,
"type": "table",
"value": "user_reviews"
},
{
"id": 4,
"type": "value",
"value": "Mature 17+"
},
{
"id": 1,
"type": "table",
"value": "playstore"
},
{
"id": 5,
"type": "column",
"value": "rating"
},
{
"id": 6,
"type": "column",
"value": "app"
}
] |
[
{
"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": [
8,
9,
10
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
467
|
public_review_platform
|
bird:train.json:3884
|
Among the businesses in Chandler, list the attribute of the business with a low review count.
|
SELECT DISTINCT T3.attribute_id, T3.attribute_name FROM Business AS T1 INNER JOIN Business_Attributes AS T2 ON T1.business_id = T2.attribute_id INNER JOIN Attributes AS T3 ON T2.attribute_id = T3.attribute_id WHERE T1.review_count = 'Low' AND T1.city = 'Chandler'
|
[
"Among",
"the",
"businesses",
"in",
"Chandler",
",",
"list",
"the",
"attribute",
"of",
"the",
"business",
"with",
"a",
"low",
"review",
"count",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "business_attributes"
},
{
"id": 1,
"type": "column",
"value": "attribute_name"
},
{
"id": 0,
"type": "column",
"value": "attribute_id"
},
{
"id": 5,
"type": "column",
"value": "review_count"
},
{
"id": 9,
"type": "column",
"value": "business_id"
},
{
"id": 2,
"type": "table",
"value": "attributes"
},
{
"id": 3,
"type": "table",
"value": "business"
},
{
"id": 8,
"type": "value",
"value": "Chandler"
},
{
"id": 7,
"type": "column",
"value": "city"
},
{
"id": 6,
"type": "value",
"value": "Low"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
15,
16
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
4
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
468
|
food_inspection_2
|
bird:train.json:6153
|
What are the comments of the inspector during the inspection of Taqueria La Fiesta on 1/25/2010?
|
SELECT T3.inspector_comment FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN violation AS T3 ON T2.inspection_id = T3.inspection_id WHERE T2.inspection_date = '2010-01-25' AND T1.dba_name = 'TAQUERIA LA FIESTA'
|
[
"What",
"are",
"the",
"comments",
"of",
"the",
"inspector",
"during",
"the",
"inspection",
"of",
"Taqueria",
"La",
"Fiesta",
"on",
"1/25/2010",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "TAQUERIA LA FIESTA"
},
{
"id": 0,
"type": "column",
"value": "inspector_comment"
},
{
"id": 5,
"type": "column",
"value": "inspection_date"
},
{
"id": 2,
"type": "table",
"value": "establishment"
},
{
"id": 4,
"type": "column",
"value": "inspection_id"
},
{
"id": 3,
"type": "table",
"value": "inspection"
},
{
"id": 6,
"type": "value",
"value": "2010-01-25"
},
{
"id": 9,
"type": "column",
"value": "license_no"
},
{
"id": 1,
"type": "table",
"value": "violation"
},
{
"id": 7,
"type": "column",
"value": "dba_name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
11,
12,
13
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
469
|
movielens
|
bird:train.json:2275
|
What is the difference of female and male audiences in number who viewed horror movies?
|
SELECT SUM(IIF(T2.u_gender = 'F', 1, 0)) - SUM(IIF(T2.u_gender = 'M', 1, 0)) FROM u2base AS T1 INNER JOIN users AS T2 ON T1.userid = T2.userid INNER JOIN movies2directors AS T3 ON T3.movieid = T1.movieid WHERE T3.genre = 'horror'
|
[
"What",
"is",
"the",
"difference",
"of",
"female",
"and",
"male",
"audiences",
"in",
"number",
"who",
"viewed",
"horror",
"movies",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "movies2directors"
},
{
"id": 9,
"type": "column",
"value": "u_gender"
},
{
"id": 5,
"type": "column",
"value": "movieid"
},
{
"id": 2,
"type": "value",
"value": "horror"
},
{
"id": 3,
"type": "table",
"value": "u2base"
},
{
"id": 6,
"type": "column",
"value": "userid"
},
{
"id": 1,
"type": "column",
"value": "genre"
},
{
"id": 4,
"type": "table",
"value": "users"
},
{
"id": 7,
"type": "value",
"value": "1"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "F"
},
{
"id": 11,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
4
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
470
|
mondial_geo
|
bird:train.json:8499
|
Which nation, with a population ranging from 60,000,000 to 99,000,000, has the greatest gross domestic product?
|
SELECT T1.Name, T2.GDP FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country WHERE T1.Population BETWEEN 60000000 AND 90000000 ORDER BY T2.GDP DESC LIMIT 1
|
[
"Which",
"nation",
",",
"with",
"a",
"population",
"ranging",
"from",
"60,000,000",
"to",
"99,000,000",
",",
"has",
"the",
"greatest",
"gross",
"domestic",
"product",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "population"
},
{
"id": 5,
"type": "value",
"value": "60000000"
},
{
"id": 6,
"type": "value",
"value": "90000000"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "table",
"value": "economy"
},
{
"id": 8,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "code"
},
{
"id": 1,
"type": "column",
"value": "gdp"
}
] |
[
{
"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": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
471
|
hr_1
|
spider:train_spider.json:3500
|
What are the full names and hire dates for employees in the same department as someone with the first name Clara?
|
SELECT first_name , last_name , hire_date FROM employees WHERE department_id = (SELECT department_id FROM employees WHERE first_name = "Clara")
|
[
"What",
"are",
"the",
"full",
"names",
"and",
"hire",
"dates",
"for",
"employees",
"in",
"the",
"same",
"department",
"as",
"someone",
"with",
"the",
"first",
"name",
"Clara",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "department_id"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "hire_date"
},
{
"id": 5,
"type": "column",
"value": "Clara"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
18,
19
]
},
{
"entity_id": 3,
"token_idxs": [
6,
7
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
472
|
movies_4
|
bird:train.json:420
|
Among the movie in which Dariusz Wolski works as the director of photography, what is the percentage of those movie whose vote average is over 5.0?
|
SELECT CAST(COUNT(CASE WHEN T1.vote_average > 5 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.vote_average) FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Dariusz Wolski' AND T2.job = 'Director of Photography'
|
[
"Among",
"the",
"movie",
"in",
"which",
"Dariusz",
"Wolski",
"works",
"as",
"the",
"director",
"of",
"photography",
",",
"what",
"is",
"the",
"percentage",
"of",
"those",
"movie",
"whose",
"vote",
"average",
"is",
"over",
"5.0",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Director of Photography"
},
{
"id": 5,
"type": "value",
"value": "Dariusz Wolski"
},
{
"id": 9,
"type": "column",
"value": "vote_average"
},
{
"id": 4,
"type": "column",
"value": "person_name"
},
{
"id": 2,
"type": "table",
"value": "movie_crew"
},
{
"id": 3,
"type": "column",
"value": "person_id"
},
{
"id": 10,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "table",
"value": "movie"
},
{
"id": 6,
"type": "column",
"value": "job"
},
{
"id": 8,
"type": "value",
"value": "100"
},
{
"id": 11,
"type": "value",
"value": "1"
},
{
"id": 12,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5,
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
22,
23
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
473
|
retail_complains
|
bird:train.json:284
|
Calculate the average number of complaints received from New Bedford each year which are closed with explanation.
|
SELECT STRFTIME('%Y', T3.`Date received`) , CAST(SUM(CASE WHEN T3.`Company response to consumer` = 'Closed with explanation' THEN 1 ELSE 0 END) AS REAL) / COUNT(T3.`Complaint ID`) AS average FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN events AS T3 ON T1.`Complaint ID` = T3.`Complaint ID` WHERE T2.city = 'New Bedford' GROUP BY strftime('%Y', T3.`Date received`)
|
[
"Calculate",
"the",
"average",
"number",
"of",
"complaints",
"received",
"from",
"New",
"Bedford",
"each",
"year",
"which",
"are",
"closed",
"with",
"explanation",
"."
] |
[
{
"id": 12,
"type": "column",
"value": "Company response to consumer"
},
{
"id": 13,
"type": "value",
"value": "Closed with explanation"
},
{
"id": 5,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 4,
"type": "column",
"value": "Date received"
},
{
"id": 7,
"type": "column",
"value": "Complaint ID"
},
{
"id": 2,
"type": "value",
"value": "New Bedford"
},
{
"id": 8,
"type": "column",
"value": "rand client"
},
{
"id": 9,
"type": "column",
"value": "client_id"
},
{
"id": 0,
"type": "table",
"value": "events"
},
{
"id": 6,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 3,
"type": "value",
"value": "%Y"
},
{
"id": 10,
"type": "value",
"value": "0"
},
{
"id": 11,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": [
14,
15,
16
]
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
474
|
computer_student
|
bird:train.json:998
|
Please list the IDs of the top 3 professors that teaches the most courses.
|
SELECT T1.p_id FROM taughtBy AS T1 INNER JOIN person AS T2 ON T1.p_id = T2.p_id WHERE T2.professor = 1 GROUP BY T1.p_id ORDER BY COUNT(*) DESC LIMIT 3
|
[
"Please",
"list",
"the",
"IDs",
"of",
"the",
"top",
"3",
"professors",
"that",
"teaches",
"the",
"most",
"courses",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "professor"
},
{
"id": 1,
"type": "table",
"value": "taughtby"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 0,
"type": "column",
"value": "p_id"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
476
|
donor
|
bird:train.json:3181
|
How many schools in urban area requested for books resources?
|
SELECT COUNT(T2.schoolid) FROM resources AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T2.resource_type = 'Books' AND T2.school_metro = 'urban'
|
[
"How",
"many",
"schools",
"in",
"urban",
"area",
"requested",
"for",
"books",
"resources",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "resource_type"
},
{
"id": 6,
"type": "column",
"value": "school_metro"
},
{
"id": 0,
"type": "table",
"value": "resources"
},
{
"id": 3,
"type": "column",
"value": "projectid"
},
{
"id": 1,
"type": "table",
"value": "projects"
},
{
"id": 2,
"type": "column",
"value": "schoolid"
},
{
"id": 5,
"type": "value",
"value": "Books"
},
{
"id": 7,
"type": "value",
"value": "urban"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
477
|
insurance_and_eClaims
|
spider:train_spider.json:1525
|
How many claim processing stages are there in total?
|
SELECT count(*) FROM claims_processing_stages
|
[
"How",
"many",
"claim",
"processing",
"stages",
"are",
"there",
"in",
"total",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "claims_processing_stages"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
478
|
retails
|
bird:train.json:6729
|
List any five parts name in Medium Plated Brass.
|
SELECT p_name FROM part WHERE p_type = 'MEDIUM PLATED BRASS' LIMIT 5
|
[
"List",
"any",
"five",
"parts",
"name",
"in",
"Medium",
"Plated",
"Brass",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "MEDIUM PLATED BRASS"
},
{
"id": 1,
"type": "column",
"value": "p_name"
},
{
"id": 2,
"type": "column",
"value": "p_type"
},
{
"id": 0,
"type": "table",
"value": "part"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
479
|
hockey
|
bird:train.json:7765
|
Please list the first names of the coaches who have taught the Montreal Canadiens.
|
SELECT DISTINCT T3.firstName FROM Coaches AS T1 INNER JOIN Teams AS T2 ON T1.year = T2.year AND T1.tmID = T2.tmID INNER JOIN Master AS T3 ON T1.coachID = T3.coachID WHERE T2.name = 'Montreal Canadiens'
|
[
"Please",
"list",
"the",
"first",
"names",
"of",
"the",
"coaches",
"who",
"have",
"taught",
"the",
"Montreal",
"Canadiens",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Montreal Canadiens"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 4,
"type": "table",
"value": "coaches"
},
{
"id": 6,
"type": "column",
"value": "coachid"
},
{
"id": 1,
"type": "table",
"value": "master"
},
{
"id": 5,
"type": "table",
"value": "teams"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "column",
"value": "tmid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
480
|
public_review_platform
|
bird:train.json:3834
|
How many businesses are there in Scottsdale city under the category of "Beauty & Spas"?
|
SELECT COUNT(T2.business_id) FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T3.city LIKE 'Scottsdale' AND T1.category_name LIKE 'Beauty & Spas'
|
[
"How",
"many",
"businesses",
"are",
"there",
"in",
"Scottsdale",
"city",
"under",
"the",
"category",
"of",
"\"",
"Beauty",
"&",
"Spas",
"\"",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "business_categories"
},
{
"id": 6,
"type": "column",
"value": "category_name"
},
{
"id": 7,
"type": "value",
"value": "Beauty & Spas"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 8,
"type": "column",
"value": "category_id"
},
{
"id": 2,
"type": "table",
"value": "categories"
},
{
"id": 5,
"type": "value",
"value": "Scottsdale"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
481
|
vehicle_rent
|
bird:test.json:421
|
Show all information for all discounts.
|
SELECT * FROM discount
|
[
"Show",
"all",
"information",
"for",
"all",
"discounts",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "discount"
}
] |
[
{
"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"
] |
482
|
donor
|
bird:train.json:3245
|
For the all donations to the project 'Bringing Drama to Life', what is the percentage of the donation is paid by credit card?
|
SELECT CAST(SUM(CASE WHEN T2.payment_method LIKE 'creditcard' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(donationid) FROM essays AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.title LIKE 'Bringing Drama to Life'
|
[
"For",
"the",
"all",
"donations",
"to",
"the",
"project",
"'",
"Bringing",
"Drama",
"to",
"Life",
"'",
",",
"what",
"is",
"the",
"percentage",
"of",
"the",
"donation",
"is",
"paid",
"by",
"credit",
"card",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Bringing Drama to Life"
},
{
"id": 9,
"type": "column",
"value": "payment_method"
},
{
"id": 6,
"type": "column",
"value": "donationid"
},
{
"id": 10,
"type": "value",
"value": "creditcard"
},
{
"id": 1,
"type": "table",
"value": "donations"
},
{
"id": 4,
"type": "column",
"value": "projectid"
},
{
"id": 0,
"type": "table",
"value": "essays"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
20
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
24,
25
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
483
|
simpson_episodes
|
bird:train.json:4281
|
What is the number of votes for 10-star for the episode that has the keyword "reference to the fantastic four"?
|
SELECT T2.votes FROM Keyword AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id WHERE T2.stars = 10 AND T1.keyword = 'reference to the fantastic four';
|
[
"What",
"is",
"the",
"number",
"of",
"votes",
"for",
"10",
"-",
"star",
"for",
"the",
"episode",
"that",
"has",
"the",
"keyword",
"\"",
"reference",
"to",
"the",
"fantastic",
"four",
"\"",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "reference to the fantastic four"
},
{
"id": 3,
"type": "column",
"value": "episode_id"
},
{
"id": 1,
"type": "table",
"value": "keyword"
},
{
"id": 6,
"type": "column",
"value": "keyword"
},
{
"id": 0,
"type": "column",
"value": "votes"
},
{
"id": 4,
"type": "column",
"value": "stars"
},
{
"id": 2,
"type": "table",
"value": "vote"
},
{
"id": 5,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
16
]
},
{
"entity_id": 7,
"token_idxs": [
18,
19,
20,
21,
22
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
484
|
department_store
|
spider:train_spider.json:4792
|
What are the ids and names of customers with addressed that contain WY and who do not use a credit card for payment?
|
SELECT customer_id , customer_name FROM customers WHERE customer_address LIKE "%WY%" AND payment_method_code != "Credit Card"
|
[
"What",
"are",
"the",
"ids",
"and",
"names",
"of",
"customers",
"with",
"addressed",
"that",
"contain",
"WY",
"and",
"who",
"do",
"not",
"use",
"a",
"credit",
"card",
"for",
"payment",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "payment_method_code"
},
{
"id": 3,
"type": "column",
"value": "customer_address"
},
{
"id": 2,
"type": "column",
"value": "customer_name"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 6,
"type": "column",
"value": "Credit Card"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "%WY%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
19,
20
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O"
] |
485
|
cre_Students_Information_Systems
|
bird:test.json:452
|
Return the distinct descriptions of all the detentions that have happened.
|
SELECT distinct(T1.detention_type_description) FROM Ref_Detention_Type AS T1 JOIN Detention AS T2 ON T1.detention_type_code = T2.detention_type_code
|
[
"Return",
"the",
"distinct",
"descriptions",
"of",
"all",
"the",
"detentions",
"that",
"have",
"happened",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "detention_type_description"
},
{
"id": 3,
"type": "column",
"value": "detention_type_code"
},
{
"id": 1,
"type": "table",
"value": "ref_detention_type"
},
{
"id": 2,
"type": "table",
"value": "detention"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
486
|
flight_1
|
spider:train_spider.json:357
|
Show the name of aircrafts with top three lowest distances.
|
SELECT name FROM Aircraft ORDER BY distance LIMIT 3
|
[
"Show",
"the",
"name",
"of",
"aircrafts",
"with",
"top",
"three",
"lowest",
"distances",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "aircraft"
},
{
"id": 2,
"type": "column",
"value": "distance"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
487
|
film_rank
|
spider:train_spider.json:4129
|
What are the countries for each market ordered by decreasing number of cities?
|
SELECT Country FROM market ORDER BY Number_cities DESC
|
[
"What",
"are",
"the",
"countries",
"for",
"each",
"market",
"ordered",
"by",
"decreasing",
"number",
"of",
"cities",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "number_cities"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "market"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10,
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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
489
|
college_2
|
spider:train_spider.json:1404
|
Find the year which offers the largest number of courses.
|
SELECT YEAR FROM SECTION GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"year",
"which",
"offers",
"the",
"largest",
"number",
"of",
"courses",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "section"
},
{
"id": 1,
"type": "column",
"value": "year"
}
] |
[
{
"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",
"O",
"O"
] |
490
|
movie_3
|
bird:train.json:9149
|
Tell the special features of the film Uprising Uptown.
|
SELECT special_features FROM film WHERE title = 'UPRISING UPTOWN'
|
[
"Tell",
"the",
"special",
"features",
"of",
"the",
"film",
"Uprising",
"Uptown",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "special_features"
},
{
"id": 3,
"type": "value",
"value": "UPRISING UPTOWN"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O"
] |
491
|
movie_3
|
bird:train.json:9109
|
How many films with the rental rate of $2.99 have the special feature of "Deleted Scenes"?
|
SELECT COUNT(film_id) FROM film WHERE rental_rate = 2.99 AND special_features = 'Deleted Scenes'
|
[
"How",
"many",
"films",
"with",
"the",
"rental",
"rate",
"of",
"$",
"2.99",
"have",
"the",
"special",
"feature",
"of",
"\"",
"Deleted",
"Scenes",
"\"",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "special_features"
},
{
"id": 5,
"type": "value",
"value": "Deleted Scenes"
},
{
"id": 2,
"type": "column",
"value": "rental_rate"
},
{
"id": 1,
"type": "column",
"value": "film_id"
},
{
"id": 0,
"type": "table",
"value": "film"
},
{
"id": 3,
"type": "value",
"value": "2.99"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
12,
13
]
},
{
"entity_id": 5,
"token_idxs": [
16,
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
492
|
program_share
|
spider:train_spider.json:3756
|
List all program origins in the alphabetical order.
|
SELECT origin FROM program ORDER BY origin
|
[
"List",
"all",
"program",
"origins",
"in",
"the",
"alphabetical",
"order",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "program"
},
{
"id": 1,
"type": "column",
"value": "origin"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
493
|
movie_platform
|
bird:train.json:160
|
What are the top 5 most popular movies of the 21st century? Indicate how many users gave it a rating score of 5.
|
SELECT DISTINCT T2.movie_id, SUM(T1.rating_score = 5) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id ORDER BY T2.movie_popularity DESC LIMIT 5
|
[
"What",
"are",
"the",
"top",
"5",
"most",
"popular",
"movies",
"of",
"the",
"21st",
"century",
"?",
"Indicate",
"how",
"many",
"users",
"gave",
"it",
"a",
"rating",
"score",
"of",
"5",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "movie_popularity"
},
{
"id": 4,
"type": "column",
"value": "rating_score"
},
{
"id": 0,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "ratings"
},
{
"id": 2,
"type": "table",
"value": "movies"
},
{
"id": 5,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
5,
6
]
},
{
"entity_id": 4,
"token_idxs": [
21
]
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O"
] |
494
|
book_1
|
bird:test.json:589
|
Find the title of books which are ordered by client Peter Doe but not client James Smith.
|
SELECT T4.title FROM Orders AS T1 JOIN Books_Order AS T2 ON T1.idOrder = T2.idOrder JOIN Client AS T3 ON T1.idClient = T3.idClient JOIN book AS T4 ON T2.ISBN = T4.isbn WHERE T3.name = "Peter Doe" EXCEPT SELECT T4.title FROM Orders AS T1 JOIN Books_Order AS T2 ON T1.idOrder = T2.idOrder JOIN Client AS T3 ON T1.idClient = T3.idClient JOIN book AS T4 ON T2.ISBN = T4.isbn WHERE T3.name = "James Smith"
|
[
"Find",
"the",
"title",
"of",
"books",
"which",
"are",
"ordered",
"by",
"client",
"Peter",
"Doe",
"but",
"not",
"client",
"James",
"Smith",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "James Smith"
},
{
"id": 8,
"type": "table",
"value": "books_order"
},
{
"id": 3,
"type": "column",
"value": "Peter Doe"
},
{
"id": 9,
"type": "column",
"value": "idclient"
},
{
"id": 10,
"type": "column",
"value": "idorder"
},
{
"id": 5,
"type": "table",
"value": "client"
},
{
"id": 7,
"type": "table",
"value": "orders"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "book"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "isbn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
495
|
sales_in_weather
|
bird:train.json:8180
|
Between 1/1/2012 to 12/31/2014, which date recorded the hottest temperature in weather station 1?
|
SELECT `date` FROM weather WHERE station_nbr = 1 AND CAST(SUBSTR(`date`, 1, 4) AS int) BETWEEN 2012 AND 2014 ORDER BY tmax DESC LIMIT 1
|
[
"Between",
"1/1/2012",
"to",
"12/31/2014",
",",
"which",
"date",
"recorded",
"the",
"hottest",
"temperature",
"in",
"weather",
"station",
"1",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "station_nbr"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 1,
"type": "column",
"value": "date"
},
{
"id": 2,
"type": "column",
"value": "tmax"
},
{
"id": 5,
"type": "value",
"value": "2012"
},
{
"id": 6,
"type": "value",
"value": "2014"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
1
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
496
|
codebase_comments
|
bird:train.json:682
|
What is the github address of the solution path "joeyrobert_bloomfilter\DataTypes.BloomFilter.sln"?
|
SELECT T1.Url FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T2.Path = 'joeyrobert_bloomfilterDataTypes.BloomFilter.sln'
|
[
"What",
"is",
"the",
"github",
"address",
"of",
"the",
"solution",
"path",
"\"",
"joeyrobert_bloomfilter\\DataTypes",
".",
"BloomFilter.sln",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "joeyrobert_bloomfilterDataTypes.BloomFilter.sln"
},
{
"id": 2,
"type": "table",
"value": "solution"
},
{
"id": 6,
"type": "column",
"value": "repoid"
},
{
"id": 1,
"type": "table",
"value": "repo"
},
{
"id": 3,
"type": "column",
"value": "path"
},
{
"id": 0,
"type": "column",
"value": "url"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
497
|
food_inspection
|
bird:train.json:8815
|
Among the establishments with a postal code of 94102, how many establishments have a score of 90 or more in 2015?
|
SELECT COUNT(DISTINCT T2.business_id) FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id INNER JOIN inspections AS T3 ON T2.business_id = T3.business_id WHERE STRFTIME('%Y', T1.`date`) = '2015' AND T2.postal_code = '94102' AND T3.score > 90
|
[
"Among",
"the",
"establishments",
"with",
"a",
"postal",
"code",
"of",
"94102",
",",
"how",
"many",
"establishments",
"have",
"a",
"score",
"of",
"90",
"or",
"more",
"in",
"2015",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "inspections"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 5,
"type": "column",
"value": "postal_code"
},
{
"id": 2,
"type": "table",
"value": "violations"
},
{
"id": 3,
"type": "table",
"value": "businesses"
},
{
"id": 6,
"type": "value",
"value": "94102"
},
{
"id": 7,
"type": "column",
"value": "score"
},
{
"id": 4,
"type": "value",
"value": "2015"
},
{
"id": 10,
"type": "column",
"value": "date"
},
{
"id": 8,
"type": "value",
"value": "90"
},
{
"id": 9,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
21
]
},
{
"entity_id": 5,
"token_idxs": [
5,
6
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": [
17
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
498
|
card_games
|
bird:dev.json:507
|
For all the set of cards that has Brazil Portuguese translation, what is the percentage of them are only available online?
|
SELECT CAST(SUM(CASE WHEN isOnlineOnly = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(id) FROM sets WHERE code IN ( SELECT setCode FROM set_translations WHERE language = 'Portuguese (Brazil)' )
|
[
"For",
"all",
"the",
"set",
"of",
"cards",
"that",
"has",
"Brazil",
"Portuguese",
"translation",
",",
"what",
"is",
"the",
"percentage",
"of",
"them",
"are",
"only",
"available",
"online",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Portuguese (Brazil)"
},
{
"id": 2,
"type": "table",
"value": "set_translations"
},
{
"id": 10,
"type": "column",
"value": "isonlineonly"
},
{
"id": 6,
"type": "column",
"value": "language"
},
{
"id": 5,
"type": "column",
"value": "setcode"
},
{
"id": 0,
"type": "table",
"value": "sets"
},
{
"id": 1,
"type": "column",
"value": "code"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"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": [
21
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
499
|
movie_platform
|
bird:train.json:150
|
List all movies rated by user 39115684. State the title, rating date and rating score.
|
SELECT T2.movie_title, T1.rating_timestamp_utc, T1.rating_score FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T1.user_id = 39115684
|
[
"List",
"all",
"movies",
"rated",
"by",
"user",
"39115684",
".",
"State",
"the",
"title",
",",
"rating",
"date",
"and",
"rating",
"score",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "rating_timestamp_utc"
},
{
"id": 2,
"type": "column",
"value": "rating_score"
},
{
"id": 0,
"type": "column",
"value": "movie_title"
},
{
"id": 6,
"type": "value",
"value": "39115684"
},
{
"id": 7,
"type": "column",
"value": "movie_id"
},
{
"id": 3,
"type": "table",
"value": "ratings"
},
{
"id": 5,
"type": "column",
"value": "user_id"
},
{
"id": 4,
"type": "table",
"value": "movies"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
500
|
headphone_store
|
bird:test.json:959
|
How many headphones are stored in the Woodman store?
|
SELECT sum(t2.quantity) FROM store AS t1 JOIN stock AS t2 ON t1.store_id = t2.store_id WHERE t1.name = 'Woodman'
|
[
"How",
"many",
"headphones",
"are",
"stored",
"in",
"the",
"Woodman",
"store",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "quantity"
},
{
"id": 5,
"type": "column",
"value": "store_id"
},
{
"id": 3,
"type": "value",
"value": "Woodman"
},
{
"id": 0,
"type": "table",
"value": "store"
},
{
"id": 1,
"type": "table",
"value": "stock"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
501
|
products_gen_characteristics
|
spider:train_spider.json:5526
|
Find the names of all the product characteristics.
|
SELECT DISTINCT characteristic_name FROM CHARACTERISTICS
|
[
"Find",
"the",
"names",
"of",
"all",
"the",
"product",
"characteristics",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "characteristic_name"
},
{
"id": 0,
"type": "table",
"value": "characteristics"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
502
|
video_games
|
bird:train.json:3411
|
What percentage of games are sports?
|
SELECT CAST(COUNT(CASE WHEN T1.genre_name = 'Sports' THEN T2.id ELSE NULL END) AS REAL) * 100 / COUNT(T2.id) FROM genre AS T1 INNER JOIN game AS T2 ON T1.id = T2.genre_id
|
[
"What",
"percentage",
"of",
"games",
"are",
"sports",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "genre_name"
},
{
"id": 3,
"type": "column",
"value": "genre_id"
},
{
"id": 6,
"type": "value",
"value": "Sports"
},
{
"id": 0,
"type": "table",
"value": "genre"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"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": [
1
]
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
503
|
music_platform_2
|
bird:train.json:7975
|
What is the content of the earliest review for the "Stuff You Should Know" podcast?
|
SELECT T2.content FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T1.title = 'Stuff You Should Know' ORDER BY T2.created_at ASC LIMIT 1
|
[
"What",
"is",
"the",
"content",
"of",
"the",
"earliest",
"review",
"for",
"the",
"\"",
"Stuff",
"You",
"Should",
"Know",
"\"",
"podcast",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Stuff You Should Know"
},
{
"id": 5,
"type": "column",
"value": "created_at"
},
{
"id": 6,
"type": "column",
"value": "podcast_id"
},
{
"id": 1,
"type": "table",
"value": "podcasts"
},
{
"id": 0,
"type": "column",
"value": "content"
},
{
"id": 2,
"type": "table",
"value": "reviews"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12,
13,
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
504
|
mondial_geo
|
bird:train.json:8474
|
List all countries with 'Category III' membership in 'IFAD' organization. Please also provide the capital of the country.
|
SELECT Name, Capital FROM country WHERE Code IN ( SELECT Country FROM isMember WHERE type = 'Category III' AND Organization = 'IFAD' )
|
[
"List",
"all",
"countries",
"with",
"'",
"Category",
"III",
"'",
"membership",
"in",
"'",
"IFAD",
"'",
"organization",
".",
"Please",
"also",
"provide",
"the",
"capital",
"of",
"the",
"country",
"."
] |
[
{
"id": 7,
"type": "value",
"value": "Category III"
},
{
"id": 8,
"type": "column",
"value": "organization"
},
{
"id": 4,
"type": "table",
"value": "ismember"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "capital"
},
{
"id": 5,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "column",
"value": "type"
},
{
"id": 9,
"type": "value",
"value": "IFAD"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
22
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5,
6
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
505
|
school_player
|
spider:train_spider.json:4897
|
What are the nicknames of schools whose division is not 1?
|
SELECT Nickname FROM school_details WHERE Division != "Division 1"
|
[
"What",
"are",
"the",
"nicknames",
"of",
"schools",
"whose",
"division",
"is",
"not",
"1",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "school_details"
},
{
"id": 3,
"type": "column",
"value": "Division 1"
},
{
"id": 1,
"type": "column",
"value": "nickname"
},
{
"id": 2,
"type": "column",
"value": "division"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
506
|
movie_3
|
bird:train.json:9415
|
Among all the customers of store no.1, how many of them are active?
|
SELECT COUNT(customer_id) FROM customer WHERE active = 1 AND store_id = 1
|
[
"Among",
"all",
"the",
"customers",
"of",
"store",
"no.1",
",",
"how",
"many",
"of",
"them",
"are",
"active",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 4,
"type": "column",
"value": "store_id"
},
{
"id": 2,
"type": "column",
"value": "active"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
507
|
movie_3
|
bird:train.json:9254
|
Give the total amount of rent for the movie Clockwork Paradice.
|
SELECT SUM(T1.amount) FROM payment AS T1 INNER JOIN rental AS T2 ON T1.rental_id = T2.rental_id INNER JOIN inventory AS T3 ON T2.inventory_id = T3.inventory_id INNER JOIN film AS T4 ON T3.film_id = T4.film_id WHERE T4.title = 'CLOCKWORK PARADICE'
|
[
"Give",
"the",
"total",
"amount",
"of",
"rent",
"for",
"the",
"movie",
"Clockwork",
"Paradice",
"."
] |
[
{
"id": 2,
"type": "value",
"value": "CLOCKWORK PARADICE"
},
{
"id": 8,
"type": "column",
"value": "inventory_id"
},
{
"id": 4,
"type": "table",
"value": "inventory"
},
{
"id": 9,
"type": "column",
"value": "rental_id"
},
{
"id": 5,
"type": "column",
"value": "film_id"
},
{
"id": 6,
"type": "table",
"value": "payment"
},
{
"id": 3,
"type": "column",
"value": "amount"
},
{
"id": 7,
"type": "table",
"value": "rental"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
508
|
formula_1
|
spider:train_spider.json:2190
|
For each constructor id, how many races are there?
|
SELECT count(*) , constructorid FROM constructorStandings GROUP BY constructorid
|
[
"For",
"each",
"constructor",
"i",
"d",
",",
"how",
"many",
"races",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "constructorstandings"
},
{
"id": 1,
"type": "column",
"value": "constructorid"
}
] |
[
{
"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",
"O",
"O",
"O",
"O",
"O",
"O"
] |
509
|
shipping
|
bird:train.json:5587
|
What is the maximum weight being transported to New York during a single shipment?
|
SELECT MAX(T1.weight) FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T2.city_name = 'New York'
|
[
"What",
"is",
"the",
"maximum",
"weight",
"being",
"transported",
"to",
"New",
"York",
"during",
"a",
"single",
"shipment",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "city_name"
},
{
"id": 0,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "value",
"value": "New York"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 4,
"type": "column",
"value": "weight"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
510
|
coinmarketcap
|
bird:train.json:6286
|
What is the name of the coin that creates the most total value in the past 24 hours?
|
SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.volume_24h = ( SELECT MAX(volume_24h) FROM historical )
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"coin",
"that",
"creates",
"the",
"most",
"total",
"value",
"in",
"the",
"past",
"24",
"hours",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 3,
"type": "column",
"value": "volume_24h"
},
{
"id": 5,
"type": "column",
"value": "coin_id"
},
{
"id": 1,
"type": "table",
"value": "coins"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"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": []
},
{
"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",
"O",
"O",
"O",
"O",
"O"
] |
511
|
student_loan
|
bird:train.json:4548
|
Among students with 1 month of absenses, how many of them are enlisted in the air force department?
|
SELECT COUNT(T1.name) FROM longest_absense_from_school AS T1 INNER JOIN enlist AS T2 ON T1.name = T2.name WHERE T1.month = 1 AND T2.organ = 'air_force'
|
[
"Among",
"students",
"with",
"1",
"month",
"of",
"absenses",
",",
"how",
"many",
"of",
"them",
"are",
"enlisted",
"in",
"the",
"air",
"force",
"department",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 6,
"type": "value",
"value": "air_force"
},
{
"id": 1,
"type": "table",
"value": "enlist"
},
{
"id": 3,
"type": "column",
"value": "month"
},
{
"id": 5,
"type": "column",
"value": "organ"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
16,
17
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
512
|
baseball_1
|
spider:train_spider.json:3696
|
Compute the total salary that the player with first name Len and last name Barker received between 1985 to 1990.
|
SELECT sum(T1.salary) FROM salary AS T1 JOIN player AS T2 ON T1.player_id = T2.player_id WHERE T2.name_first = 'Len' AND T2.name_last = 'Barker' AND T1.year BETWEEN 1985 AND 1990;
|
[
"Compute",
"the",
"total",
"salary",
"that",
"the",
"player",
"with",
"first",
"name",
"Len",
"and",
"last",
"name",
"Barker",
"received",
"between",
"1985",
"to",
"1990",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "name_first"
},
{
"id": 3,
"type": "column",
"value": "player_id"
},
{
"id": 6,
"type": "column",
"value": "name_last"
},
{
"id": 0,
"type": "table",
"value": "salary"
},
{
"id": 1,
"type": "table",
"value": "player"
},
{
"id": 2,
"type": "column",
"value": "salary"
},
{
"id": 7,
"type": "value",
"value": "Barker"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 9,
"type": "value",
"value": "1985"
},
{
"id": 10,
"type": "value",
"value": "1990"
},
{
"id": 5,
"type": "value",
"value": "Len"
}
] |
[
{
"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": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": [
6
]
},
{
"entity_id": 9,
"token_idxs": [
17
]
},
{
"entity_id": 10,
"token_idxs": [
19
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
513
|
simpson_episodes
|
bird:train.json:4315
|
What is the average heights of crew members from Animation Department?
|
SELECT AVG(T1.height_meters) FROM Person AS T1 INNER JOIN Credit AS T2 ON T1.name = T2.person WHERE T2.category = 'Animation Department';
|
[
"What",
"is",
"the",
"average",
"heights",
"of",
"crew",
"members",
"from",
"Animation",
"Department",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Animation Department"
},
{
"id": 4,
"type": "column",
"value": "height_meters"
},
{
"id": 2,
"type": "column",
"value": "category"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "table",
"value": "credit"
},
{
"id": 6,
"type": "column",
"value": "person"
},
{
"id": 5,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
515
|
regional_sales
|
bird:train.json:2661
|
What is the difference in order number from "WARE-MKL1006" and "WARE-NBV1002"?
|
SELECT SUM(IIF(WarehouseCode = 'WARE-MKL1006', 1, 0)) - SUM(IIF(WarehouseCode = 'WARE-NBV1002', 1, 0)) AS difference FROM `Sales Orders`
|
[
"What",
"is",
"the",
"difference",
"in",
"order",
"number",
"from",
"\"",
"WARE",
"-",
"MKL1006",
"\"",
"and",
"\"",
"WARE",
"-",
"NBV1002",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "warehousecode"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 4,
"type": "value",
"value": "WARE-MKL1006"
},
{
"id": 5,
"type": "value",
"value": "WARE-NBV1002"
},
{
"id": 1,
"type": "value",
"value": "1"
},
{
"id": 2,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 5,
"token_idxs": [
15,
16,
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
516
|
driving_school
|
spider:train_spider.json:6684
|
Which country does customer with first name as Carole and last name as Bernhard lived in?
|
SELECT T2.country FROM Customers AS T1 JOIN Addresses AS T2 ON T1.customer_address_id = T2.address_id WHERE T1.first_name = "Carole" AND T1.last_name = "Bernhard"
|
[
"Which",
"country",
"does",
"customer",
"with",
"first",
"name",
"as",
"Carole",
"and",
"last",
"name",
"as",
"Bernhard",
"lived",
"in",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "customer_address_id"
},
{
"id": 4,
"type": "column",
"value": "address_id"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "addresses"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 8,
"type": "column",
"value": "Bernhard"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "Carole"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"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": [
5,
6
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
10,
11
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
517
|
works_cycles
|
bird:train.json:7093
|
What is the job title of the newest employee in department 12?
|
SELECT T1.JobTitle FROM Employee AS T1 INNER JOIN EmployeeDepartmentHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T2.DepartmentID = 12 ORDER BY T2.StartDate DESC LIMIT 1
|
[
"What",
"is",
"the",
"job",
"title",
"of",
"the",
"newest",
"employee",
"in",
"department",
"12",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "employeedepartmenthistory"
},
{
"id": 6,
"type": "column",
"value": "businessentityid"
},
{
"id": 3,
"type": "column",
"value": "departmentid"
},
{
"id": 5,
"type": "column",
"value": "startdate"
},
{
"id": 0,
"type": "column",
"value": "jobtitle"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 4,
"type": "value",
"value": "12"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
518
|
loan_1
|
spider:train_spider.json:3046
|
Find the branch name of the bank that has the most number of customers.
|
SELECT bname FROM bank ORDER BY no_of_customers DESC LIMIT 1
|
[
"Find",
"the",
"branch",
"name",
"of",
"the",
"bank",
"that",
"has",
"the",
"most",
"number",
"of",
"customers",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "no_of_customers"
},
{
"id": 1,
"type": "column",
"value": "bname"
},
{
"id": 0,
"type": "table",
"value": "bank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
12,
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": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"I-COLUMN",
"O"
] |
519
|
public_review_platform
|
bird:train.json:3788
|
User No."63469" has got "1" like for a tip to the Yelp business, which city is that business located in?
|
SELECT T1.city FROM Business AS T1 INNER JOIN Tips AS T2 ON T1.business_id = T2.business_id WHERE T2.likes = 1 AND T2.user_id = 63469
|
[
"User",
"No",
".",
"\"63469",
"\"",
"has",
"got",
"\"",
"1",
"\"",
"like",
"for",
"a",
"tip",
"to",
"the",
"Yelp",
"business",
",",
"which",
"city",
"is",
"that",
"business",
"located",
"in",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "business"
},
{
"id": 6,
"type": "column",
"value": "user_id"
},
{
"id": 4,
"type": "column",
"value": "likes"
},
{
"id": 7,
"type": "value",
"value": "63469"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 2,
"type": "table",
"value": "tips"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
0
]
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
521
|
law_episode
|
bird:train.json:1276
|
How many people, who were born in Canada, won an award in 1999?
|
SELECT COUNT(T1.person_id) FROM Person AS T1 INNER JOIN Award AS T2 ON T1.person_id = T2.person_id WHERE T2.year = 1999 AND T1.birth_country = 'Canada'
|
[
"How",
"many",
"people",
",",
"who",
"were",
"born",
"in",
"Canada",
",",
"won",
"an",
"award",
"in",
"1999",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "birth_country"
},
{
"id": 2,
"type": "column",
"value": "person_id"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 6,
"type": "value",
"value": "Canada"
},
{
"id": 1,
"type": "table",
"value": "award"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "1999"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
522
|
image_and_language
|
bird:train.json:7575
|
State the coordinate of X and Y for the object with the attribute of 'sparse' in image 1.
|
SELECT T3.OBJ_SAMPLE_ID, T3.X, T3.Y FROM ATT_CLASSES AS T1 INNER JOIN IMG_OBJ_ATT AS T2 ON T1.ATT_CLASS_ID = T2.ATT_CLASS_ID INNER JOIN IMG_OBJ AS T3 ON T2.IMG_ID = T3.IMG_ID WHERE T3.IMG_ID = 1 AND T1.ATT_CLASS = 'sparse'
|
[
"State",
"the",
"coordinate",
"of",
"X",
"and",
"Y",
"for",
"the",
"object",
"with",
"the",
"attribute",
"of",
"'",
"sparse",
"'",
"in",
"image",
"1",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "obj_sample_id"
},
{
"id": 10,
"type": "column",
"value": "att_class_id"
},
{
"id": 4,
"type": "table",
"value": "att_classes"
},
{
"id": 5,
"type": "table",
"value": "img_obj_att"
},
{
"id": 8,
"type": "column",
"value": "att_class"
},
{
"id": 3,
"type": "table",
"value": "img_obj"
},
{
"id": 6,
"type": "column",
"value": "img_id"
},
{
"id": 9,
"type": "value",
"value": "sparse"
},
{
"id": 1,
"type": "column",
"value": "x"
},
{
"id": 2,
"type": "column",
"value": "y"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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": [
19
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
15
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
523
|
university
|
bird:train.json:8079
|
Please list the names of the universities with a score in teaching of over 90 in 2011.
|
SELECT T3.university_name FROM ranking_criteria AS T1 INNER JOIN university_ranking_year AS T2 ON T1.id = T2.ranking_criteria_id INNER JOIN university AS T3 ON T3.id = T2.university_id WHERE T1.criteria_name = 'Teaching' AND T2.year = 2011 AND T2.score > 90
|
[
"Please",
"list",
"the",
"names",
"of",
"the",
"universities",
"with",
"a",
"score",
"in",
"teaching",
"of",
"over",
"90",
"in",
"2011",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 12,
"type": "column",
"value": "ranking_criteria_id"
},
{
"id": 2,
"type": "table",
"value": "ranking_criteria"
},
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 5,
"type": "column",
"value": "university_id"
},
{
"id": 6,
"type": "column",
"value": "criteria_name"
},
{
"id": 1,
"type": "table",
"value": "university"
},
{
"id": 7,
"type": "value",
"value": "Teaching"
},
{
"id": 10,
"type": "column",
"value": "score"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 9,
"type": "value",
"value": "2011"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 11,
"type": "value",
"value": "90"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
16
]
},
{
"entity_id": 10,
"token_idxs": [
9
]
},
{
"entity_id": 11,
"token_idxs": [
14
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
524
|
works_cycles
|
bird:train.json:7330
|
Names the Sales Representative with the highest year to date sales.
|
SELECT T2.FirstName, T2.MiddleName, T2.LastName FROM SalesPerson AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID ORDER BY T1.SalesYTD DESC LIMIT 1
|
[
"Names",
"the",
"Sales",
"Representative",
"with",
"the",
"highest",
"year",
"to",
"date",
"sales",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "businessentityid"
},
{
"id": 3,
"type": "table",
"value": "salesperson"
},
{
"id": 1,
"type": "column",
"value": "middlename"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "column",
"value": "salesytd"
},
{
"id": 4,
"type": "table",
"value": "person"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
0
]
},
{
"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": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
526
|
movie_platform
|
bird:train.json:116
|
Who was the earliest user created a list but didn't get any followers? Give the user ID.
|
SELECT user_id FROM lists_users WHERE user_subscriber = 0 ORDER BY list_creation_date_utc LIMIT 1
|
[
"Who",
"was",
"the",
"earliest",
"user",
"created",
"a",
"list",
"but",
"did",
"n't",
"get",
"any",
"followers",
"?",
"Give",
"the",
"user",
"ID",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "list_creation_date_utc"
},
{
"id": 2,
"type": "column",
"value": "user_subscriber"
},
{
"id": 0,
"type": "table",
"value": "lists_users"
},
{
"id": 1,
"type": "column",
"value": "user_id"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
17,
18
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
527
|
music_4
|
spider:train_spider.json:6152
|
Give the distinct famous release dates for all artists.
|
SELECT distinct(Famous_Release_date) FROM artist
|
[
"Give",
"the",
"distinct",
"famous",
"release",
"dates",
"for",
"all",
"artists",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "famous_release_date"
},
{
"id": 0,
"type": "table",
"value": "artist"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"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",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
528
|
department_store
|
spider:train_spider.json:4775
|
What is the largest and smallest customer codes?
|
SELECT max(customer_code) , min(customer_code) FROM Customers
|
[
"What",
"is",
"the",
"largest",
"and",
"smallest",
"customer",
"codes",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "customer_code"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
529
|
debit_card_specializing
|
bird:dev.json:1475
|
How many customers in KAM had a consumption of less than 30,000 for the year 2012?
|
SELECT COUNT(*) FROM ( SELECT T2.CustomerID FROM customers AS T1 INNER JOIN yearmonth AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.Segment = 'KAM' AND SUBSTRING(T2.Date, 1, 4) = '2012' GROUP BY T2.CustomerID HAVING SUM(T2.Consumption) < 30000 ) AS t1
|
[
"How",
"many",
"customers",
"in",
"KAM",
"had",
"a",
"consumption",
"of",
"less",
"than",
"30,000",
"for",
"the",
"year",
"2012",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "consumption"
},
{
"id": 0,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "yearmonth"
},
{
"id": 4,
"type": "column",
"value": "segment"
},
{
"id": 3,
"type": "value",
"value": "30000"
},
{
"id": 6,
"type": "value",
"value": "2012"
},
{
"id": 8,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "value",
"value": "KAM"
},
{
"id": 9,
"type": "value",
"value": "1"
},
{
"id": 10,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
530
|
chinook_1
|
spider:train_spider.json:890
|
Find the titles of albums that contain tracks of both the Reggae and Rock genres.
|
SELECT T1.Title FROM Album AS T1 JOIN Track AS T2 ON T1.AlbumId = T2.AlbumId JOIN Genre AS T3 ON T2.GenreID = T3.GenreID WHERE T3.Name = 'Reggae' INTERSECT SELECT T1.Title FROM Album AS T1 JOIN Track AS T2 ON T1.AlbumId = T2.AlbumId JOIN Genre AS T3 ON T2.GenreID = T3.GenreID WHERE T3.Name = 'Rock'
|
[
"Find",
"the",
"titles",
"of",
"albums",
"that",
"contain",
"tracks",
"of",
"both",
"the",
"Reggae",
"and",
"Rock",
"genres",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "genreid"
},
{
"id": 8,
"type": "column",
"value": "albumid"
},
{
"id": 3,
"type": "value",
"value": "Reggae"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "genre"
},
{
"id": 5,
"type": "table",
"value": "album"
},
{
"id": 6,
"type": "table",
"value": "track"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "Rock"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
531
|
talkingdata
|
bird:train.json:1112
|
What is the brand of the youngest user's device?
|
SELECT device_model FROM phone_brand_device_model2 WHERE device_id IN ( SELECT device_id FROM gender_age WHERE age = ( SELECT MIN(age) FROM gender_age ) )
|
[
"What",
"is",
"the",
"brand",
"of",
"the",
"youngest",
"user",
"'s",
"device",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 1,
"type": "column",
"value": "device_model"
},
{
"id": 3,
"type": "table",
"value": "gender_age"
},
{
"id": 2,
"type": "column",
"value": "device_id"
},
{
"id": 4,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
532
|
codebase_community
|
bird:dev.json:700
|
Identify the number of posts that offer a bounty amount over 30.
|
SELECT COUNT(id) FROM votes WHERE BountyAmount >= 30
|
[
"Identify",
"the",
"number",
"of",
"posts",
"that",
"offer",
"a",
"bounty",
"amount",
"over",
"30",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "bountyamount"
},
{
"id": 0,
"type": "table",
"value": "votes"
},
{
"id": 2,
"type": "value",
"value": "30"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
533
|
world
|
bird:train.json:7886
|
What are the cities for country called "´Uman" in local name.
|
SELECT T1.Name FROM City AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T2.LocalName = '´Uman'
|
[
"What",
"are",
"the",
"cities",
"for",
"country",
"called",
"\"",
"´Uman",
"\"",
"in",
"local",
"name",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 3,
"type": "column",
"value": "localname"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "value",
"value": "´Uman"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.