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
|
|---|---|---|---|---|---|---|---|---|
638
|
device
|
spider:train_spider.json:5084
|
Show the locations shared by shops with open year later than 2012 and shops with open year before 2008.
|
SELECT LOCATION FROM shop WHERE Open_Year > 2012 INTERSECT SELECT LOCATION FROM shop WHERE Open_Year < 2008
|
[
"Show",
"the",
"locations",
"shared",
"by",
"shops",
"with",
"open",
"year",
"later",
"than",
"2012",
"and",
"shops",
"with",
"open",
"year",
"before",
"2008",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "open_year"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "shop"
},
{
"id": 3,
"type": "value",
"value": "2012"
},
{
"id": 4,
"type": "value",
"value": "2008"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
639
|
product_catalog
|
spider:train_spider.json:301
|
Find the names of all the catalog entries.
|
SELECT distinct(catalog_entry_name) FROM catalog_contents
|
[
"Find",
"the",
"names",
"of",
"all",
"the",
"catalog",
"entries",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "catalog_entry_name"
},
{
"id": 0,
"type": "table",
"value": "catalog_contents"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
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",
"B-TABLE",
"I-TABLE",
"O"
] |
640
|
company_office
|
spider:train_spider.json:4549
|
What are the name and assets of each company, sorted in ascending order of company name?
|
SELECT name , Assets_billion FROM Companies ORDER BY name ASC
|
[
"What",
"are",
"the",
"name",
"and",
"assets",
"of",
"each",
"company",
",",
"sorted",
"in",
"ascending",
"order",
"of",
"company",
"name",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "assets_billion"
},
{
"id": 0,
"type": "table",
"value": "companies"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
641
|
synthea
|
bird:train.json:1479
|
How many mothers have taken immunization during prenatal visit?
|
SELECT COUNT(DISTINCT T2.PATIENT) FROM encounters AS T1 INNER JOIN immunizations AS T2 ON T1.PATIENT = T2.PATIENT WHERE T1.REASONDESCRIPTION = 'Normal pregnancy' AND T1.DATE = T2.DATE
|
[
"How",
"many",
"mothers",
"have",
"taken",
"immunization",
"during",
"prenatal",
"visit",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "reasondescription"
},
{
"id": 4,
"type": "value",
"value": "Normal pregnancy"
},
{
"id": 1,
"type": "table",
"value": "immunizations"
},
{
"id": 0,
"type": "table",
"value": "encounters"
},
{
"id": 2,
"type": "column",
"value": "patient"
},
{
"id": 5,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
642
|
customers_card_transactions
|
spider:train_spider.json:715
|
Show id, first and last names for all customers with at least two cards.
|
SELECT T1.customer_id , T2.customer_first_name , T2.customer_last_name FROM Customers_cards AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id HAVING count(*) >= 2
|
[
"Show",
"i",
"d",
",",
"first",
"and",
"last",
"names",
"for",
"all",
"customers",
"with",
"at",
"least",
"two",
"cards",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "customer_first_name"
},
{
"id": 2,
"type": "column",
"value": "customer_last_name"
},
{
"id": 3,
"type": "table",
"value": "customers_cards"
},
{
"id": 0,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"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": [
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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
643
|
college_2
|
spider:train_spider.json:1322
|
Find the buildings which have rooms with capacity more than 50.
|
SELECT DISTINCT building FROM classroom WHERE capacity > 50
|
[
"Find",
"the",
"buildings",
"which",
"have",
"rooms",
"with",
"capacity",
"more",
"than",
"50",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "classroom"
},
{
"id": 1,
"type": "column",
"value": "building"
},
{
"id": 2,
"type": "column",
"value": "capacity"
},
{
"id": 3,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
644
|
synthea
|
bird:train.json:1498
|
How long did Elly Koss have to take Acetaminophen 160 MG?
|
SELECT strftime('%J', T2.STOP) - strftime('%J', T2.START) AS days FROM patients AS T1 INNER JOIN medications AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND last = 'Koss' AND T2.DESCRIPTION = 'Acetaminophen 160 MG'
|
[
"How",
"long",
"did",
"Elly",
"Koss",
"have",
"to",
"take",
"Acetaminophen",
"160",
"MG",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Acetaminophen 160 MG"
},
{
"id": 1,
"type": "table",
"value": "medications"
},
{
"id": 7,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "table",
"value": "patients"
},
{
"id": 2,
"type": "column",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "first"
},
{
"id": 11,
"type": "column",
"value": "start"
},
{
"id": 4,
"type": "value",
"value": "Elly"
},
{
"id": 5,
"type": "column",
"value": "last"
},
{
"id": 6,
"type": "value",
"value": "Koss"
},
{
"id": 10,
"type": "column",
"value": "stop"
},
{
"id": 9,
"type": "value",
"value": "%J"
}
] |
[
{
"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": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
6
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
645
|
beer_factory
|
bird:train.json:5252
|
Tell the number of reviews given by James House.
|
SELECT COUNT(T2.CustomerID) FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.First = 'James' AND T1.Last = 'House'
|
[
"Tell",
"the",
"number",
"of",
"reviews",
"given",
"by",
"James",
"House",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "rootbeerreview"
},
{
"id": 2,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "column",
"value": "first"
},
{
"id": 4,
"type": "value",
"value": "James"
},
{
"id": 6,
"type": "value",
"value": "House"
},
{
"id": 5,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
646
|
wine_1
|
spider:train_spider.json:6521
|
Find the names of all wines produced in 2008.
|
SELECT Name FROM WINE WHERE YEAR = "2008"
|
[
"Find",
"the",
"names",
"of",
"all",
"wines",
"produced",
"in",
"2008",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "wine"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "column",
"value": "2008"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
647
|
card_games
|
bird:dev.json:448
|
Name the foreign name of the card that has abzan watermark? List out the type of this card.
|
SELECT DISTINCT T1.name, T1.type FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T2.uuid = T1.uuid WHERE T1.watermark = 'abzan'
|
[
"Name",
"the",
"foreign",
"name",
"of",
"the",
"card",
"that",
"has",
"abzan",
"watermark",
"?",
"List",
"out",
"the",
"type",
"of",
"this",
"card",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "foreign_data"
},
{
"id": 4,
"type": "column",
"value": "watermark"
},
{
"id": 2,
"type": "table",
"value": "cards"
},
{
"id": 5,
"type": "value",
"value": "abzan"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "type"
},
{
"id": 6,
"type": "column",
"value": "uuid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_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-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
648
|
debate
|
spider:train_spider.json:1503
|
Show the names of people that are on affirmative side of debates with number of audience bigger than 200.
|
SELECT T3.Name FROM debate_people AS T1 JOIN debate AS T2 ON T1.Debate_ID = T2.Debate_ID JOIN people AS T3 ON T1.Affirmative = T3.People_ID WHERE T2.Num_of_Audience > 200
|
[
"Show",
"the",
"names",
"of",
"people",
"that",
"are",
"on",
"affirmative",
"side",
"of",
"debates",
"with",
"number",
"of",
"audience",
"bigger",
"than",
"200",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "num_of_audience"
},
{
"id": 4,
"type": "table",
"value": "debate_people"
},
{
"id": 6,
"type": "column",
"value": "affirmative"
},
{
"id": 7,
"type": "column",
"value": "people_id"
},
{
"id": 8,
"type": "column",
"value": "debate_id"
},
{
"id": 1,
"type": "table",
"value": "people"
},
{
"id": 5,
"type": "table",
"value": "debate"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "200"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
649
|
student_1
|
spider:train_spider.json:4087
|
For each classroom, show the classroom number and find how many students are using it.
|
SELECT classroom , count(*) FROM list GROUP BY classroom
|
[
"For",
"each",
"classroom",
",",
"show",
"the",
"classroom",
"number",
"and",
"find",
"how",
"many",
"students",
"are",
"using",
"it",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "classroom"
},
{
"id": 0,
"type": "table",
"value": "list"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
650
|
hr_1
|
spider:train_spider.json:3501
|
display the employee name ( first name and last name ) and hire date for all employees in the same department as Clara excluding Clara.
|
SELECT first_name , last_name , hire_date FROM employees WHERE department_id = ( SELECT department_id FROM employees WHERE first_name = "Clara") AND first_name != "Clara"
|
[
"display",
"the",
"employee",
"name",
"(",
"first",
"name",
"and",
"last",
"name",
")",
"and",
"hire",
"date",
"for",
"all",
"employees",
"in",
"the",
"same",
"department",
"as",
"Clara",
"excluding",
"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": [
16
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
20
]
},
{
"entity_id": 5,
"token_idxs": [
24
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
652
|
cre_Doc_Workflow
|
bird:test.json:2042
|
What are the details for the staff member with id 100.
|
SELECT staff_details FROM Staff WHERE staff_id = 100
|
[
"What",
"are",
"the",
"details",
"for",
"the",
"staff",
"member",
"with",
"i",
"d",
"100",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "staff_details"
},
{
"id": 2,
"type": "column",
"value": "staff_id"
},
{
"id": 0,
"type": "table",
"value": "staff"
},
{
"id": 3,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
654
|
csu_1
|
spider:train_spider.json:2341
|
How many universities have a campus fee higher than average?
|
SELECT count(*) FROM csu_fees WHERE campusfee > (SELECT avg(campusfee) FROM csu_fees)
|
[
"How",
"many",
"universities",
"have",
"a",
"campus",
"fee",
"higher",
"than",
"average",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "campusfee"
},
{
"id": 0,
"type": "table",
"value": "csu_fees"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
655
|
regional_sales
|
bird:train.json:2688
|
What is the highest discount applied by the store located in a city of the state of Colorado whose land area is 111039036.
|
SELECT MAX(T1.`Discount Applied`) FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T2.State = 'Colorado' AND T2.`Land Area` = 111039036
|
[
"What",
"is",
"the",
"highest",
"discount",
"applied",
"by",
"the",
"store",
"located",
"in",
"a",
"city",
"of",
"the",
"state",
"of",
"Colorado",
"whose",
"land",
"area",
"is",
"111039036",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "Discount Applied"
},
{
"id": 1,
"type": "table",
"value": "Store Locations"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 7,
"type": "column",
"value": "Land Area"
},
{
"id": 8,
"type": "value",
"value": "111039036"
},
{
"id": 4,
"type": "column",
"value": "_storeid"
},
{
"id": 6,
"type": "value",
"value": "Colorado"
},
{
"id": 3,
"type": "column",
"value": "storeid"
},
{
"id": 5,
"type": "column",
"value": "state"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": [
19,
20
]
},
{
"entity_id": 8,
"token_idxs": [
22
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
656
|
restaurant
|
bird:train.json:1714
|
How many Thai restaurants can be found in San Pablo Ave, Albany?
|
SELECT COUNT(T1.id_restaurant) FROM generalinfo AS T1 INNER JOIN location AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T1.food_type = 'thai' AND T1.city = 'albany' AND T2.street_name = 'san pablo ave'
|
[
"How",
"many",
"Thai",
"restaurants",
"can",
"be",
"found",
"in",
"San",
"Pablo",
"Ave",
",",
"Albany",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "id_restaurant"
},
{
"id": 8,
"type": "value",
"value": "san pablo ave"
},
{
"id": 0,
"type": "table",
"value": "generalinfo"
},
{
"id": 7,
"type": "column",
"value": "street_name"
},
{
"id": 3,
"type": "column",
"value": "food_type"
},
{
"id": 1,
"type": "table",
"value": "location"
},
{
"id": 6,
"type": "value",
"value": "albany"
},
{
"id": 4,
"type": "value",
"value": "thai"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
657
|
customers_and_addresses
|
spider:train_spider.json:6113
|
How many types of products have Rodrick Heaney bought in total?
|
SELECT count(DISTINCT t3.product_id) FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id JOIN order_items AS t3 ON t2.order_id = t3.order_id WHERE t1.customer_name = "Rodrick Heaney"
|
[
"How",
"many",
"types",
"of",
"products",
"have",
"Rodrick",
"Heaney",
"bought",
"in",
"total",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "customer_orders"
},
{
"id": 2,
"type": "column",
"value": "Rodrick Heaney"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "table",
"value": "order_items"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "column",
"value": "product_id"
},
{
"id": 4,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "order_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
658
|
document_management
|
spider:train_spider.json:4526
|
What are the names of documents that do not have any images?
|
SELECT document_name FROM documents EXCEPT SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code JOIN document_sections_images AS t3 ON t2.section_id = t3.section_id
|
[
"What",
"are",
"the",
"names",
"of",
"documents",
"that",
"do",
"not",
"have",
"any",
"images",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "document_sections_images"
},
{
"id": 3,
"type": "table",
"value": "document_sections"
},
{
"id": 1,
"type": "column",
"value": "document_name"
},
{
"id": 5,
"type": "column",
"value": "document_code"
},
{
"id": 4,
"type": "column",
"value": "section_id"
},
{
"id": 0,
"type": "table",
"value": "documents"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
659
|
club_1
|
spider:train_spider.json:4275
|
Which members of "Bootup Baltimore" major in "600"? Give me their first names and last names.
|
SELECT t3.fname , t3.lname FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t1.clubname = "Bootup Baltimore" AND t3.major = "600"
|
[
"Which",
"members",
"of",
"\"",
"Bootup",
"Baltimore",
"\"",
"major",
"in",
"\"",
"600",
"\"",
"?",
"Give",
"me",
"their",
"first",
"names",
"and",
"last",
"names",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "Bootup Baltimore"
},
{
"id": 4,
"type": "table",
"value": "member_of_club"
},
{
"id": 6,
"type": "column",
"value": "clubname"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 10,
"type": "column",
"value": "clubid"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 5,
"type": "column",
"value": "stuid"
},
{
"id": 8,
"type": "column",
"value": "major"
},
{
"id": 3,
"type": "table",
"value": "club"
},
{
"id": 9,
"type": "column",
"value": "600"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
1,
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": [
4,
5
]
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": [
10
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
660
|
mondial_geo
|
bird:train.json:8279
|
Which two countries share the second highest mountain? Give the country code.
|
SELECT T1.Code FROM country AS T1 INNER JOIN geo_mountain AS T2 ON T1.Code = T2.Country WHERE T2.Mountain = ( SELECT Name FROM mountain ORDER BY Height DESC LIMIT 1, 1 )
|
[
"Which",
"two",
"countries",
"share",
"the",
"second",
"highest",
"mountain",
"?",
"Give",
"the",
"country",
"code",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "geo_mountain"
},
{
"id": 3,
"type": "column",
"value": "mountain"
},
{
"id": 5,
"type": "table",
"value": "mountain"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "country"
},
{
"id": 7,
"type": "column",
"value": "height"
},
{
"id": 0,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
661
|
theme_gallery
|
spider:train_spider.json:1673
|
What is the theme and artist name for the exhibition with a ticket price higher than the average?
|
SELECT T1.theme , T2.name FROM exhibition AS T1 JOIN artist AS T2 ON T1.artist_id = T2.artist_id WHERE T1.ticket_price > (SELECT avg(ticket_price) FROM exhibition)
|
[
"What",
"is",
"the",
"theme",
"and",
"artist",
"name",
"for",
"the",
"exhibition",
"with",
"a",
"ticket",
"price",
"higher",
"than",
"the",
"average",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "ticket_price"
},
{
"id": 2,
"type": "table",
"value": "exhibition"
},
{
"id": 5,
"type": "column",
"value": "artist_id"
},
{
"id": 3,
"type": "table",
"value": "artist"
},
{
"id": 0,
"type": "column",
"value": "theme"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
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",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
662
|
beer_factory
|
bird:train.json:5274
|
Which brewery does the most purchased root beer in 2016 belong to?
|
SELECT T2.BreweryName FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID WHERE T1.PurchaseDate BETWEEN '2016-01-01' AND '2016-12-31' GROUP BY T2.BrandID ORDER BY COUNT(T1.BrandID) DESC LIMIT 1
|
[
"Which",
"brewery",
"does",
"the",
"most",
"purchased",
"root",
"beer",
"in",
"2016",
"belong",
"to",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "rootbeerbrand"
},
{
"id": 4,
"type": "column",
"value": "purchasedate"
},
{
"id": 1,
"type": "column",
"value": "breweryname"
},
{
"id": 5,
"type": "value",
"value": "2016-01-01"
},
{
"id": 6,
"type": "value",
"value": "2016-12-31"
},
{
"id": 2,
"type": "table",
"value": "rootbeer"
},
{
"id": 0,
"type": "column",
"value": "brandid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
663
|
public_review_platform
|
bird:train.json:3855
|
Under which categories is Yelp_Business no. 1?
|
SELECT T1.category_name FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id WHERE T2.business_id = 1
|
[
"Under",
"which",
"categories",
"is",
"Yelp_Business",
"no",
".",
"1",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "business_categories"
},
{
"id": 0,
"type": "column",
"value": "category_name"
},
{
"id": 3,
"type": "column",
"value": "business_id"
},
{
"id": 5,
"type": "column",
"value": "category_id"
},
{
"id": 1,
"type": "table",
"value": "categories"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
664
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5106
|
What is the description of the marketing region China?
|
SELECT Marketing_Region_Descriptrion FROM Marketing_Regions WHERE Marketing_Region_Name = "China"
|
[
"What",
"is",
"the",
"description",
"of",
"the",
"marketing",
"region",
"China",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "marketing_region_descriptrion"
},
{
"id": 2,
"type": "column",
"value": "marketing_region_name"
},
{
"id": 0,
"type": "table",
"value": "marketing_regions"
},
{
"id": 3,
"type": "column",
"value": "China"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7
]
},
{
"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",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O"
] |
665
|
public_review_platform
|
bird:train.json:4113
|
How many users who have received a low cool vote have also received at least 1 low cool vote for some of their reviews?
|
SELECT COUNT(DISTINCT T1.user_id) FROM Users AS T1 INNER JOIN Reviews AS T2 ON T1.user_id = T2.user_id WHERE T1.user_votes_cool = 'Low' AND T2.review_votes_cool = 'Low'
|
[
"How",
"many",
"users",
"who",
"have",
"received",
"a",
"low",
"cool",
"vote",
"have",
"also",
"received",
"at",
"least",
"1",
"low",
"cool",
"vote",
"for",
"some",
"of",
"their",
"reviews",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "review_votes_cool"
},
{
"id": 3,
"type": "column",
"value": "user_votes_cool"
},
{
"id": 1,
"type": "table",
"value": "reviews"
},
{
"id": 2,
"type": "column",
"value": "user_id"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 4,
"type": "value",
"value": "Low"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
23
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
666
|
party_host
|
spider:train_spider.json:2675
|
Which nationality has the most hosts?
|
SELECT Nationality FROM HOST GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Which",
"nationality",
"has",
"the",
"most",
"hosts",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "table",
"value": "host"
}
] |
[
{
"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"
] |
667
|
student_1
|
spider:train_spider.json:4062
|
Find the first and last name of all the teachers that teach EVELINA BROMLEY.
|
SELECT T2.firstname , T2.lastname FROM list AS T1 JOIN teachers AS T2 ON T1.classroom = T2.classroom WHERE T1.firstname = "EVELINA" AND T1.lastname = "BROMLEY"
|
[
"Find",
"the",
"first",
"and",
"last",
"name",
"of",
"all",
"the",
"teachers",
"that",
"teach",
"EVELINA",
"BROMLEY",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 4,
"type": "column",
"value": "classroom"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "table",
"value": "teachers"
},
{
"id": 5,
"type": "column",
"value": "EVELINA"
},
{
"id": 6,
"type": "column",
"value": "BROMLEY"
},
{
"id": 2,
"type": "table",
"value": "list"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
668
|
regional_sales
|
bird:train.json:2715
|
What is the store id of the store located in the most populous county?
|
SELECT CASE WHEN MAX(Population) THEN StoreID END FROM `Store Locations`
|
[
"What",
"is",
"the",
"store",
"i",
"d",
"of",
"the",
"store",
"located",
"in",
"the",
"most",
"populous",
"county",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "Store Locations"
},
{
"id": 2,
"type": "column",
"value": "population"
},
{
"id": 1,
"type": "column",
"value": "storeid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-TABLE",
"I-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
669
|
allergy_1
|
spider:train_spider.json:533
|
Find the number of students who are older than 18 and do not have allergy to either food or animal.
|
SELECT count(*) FROM Student WHERE age > 18 AND StuID NOT IN ( SELECT StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food" OR T2.allergytype = "animal")
|
[
"Find",
"the",
"number",
"of",
"students",
"who",
"are",
"older",
"than",
"18",
"and",
"do",
"not",
"have",
"allergy",
"to",
"either",
"food",
"or",
"animal",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "allergy_type"
},
{
"id": 4,
"type": "table",
"value": "has_allergy"
},
{
"id": 7,
"type": "column",
"value": "allergytype"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 6,
"type": "column",
"value": "allergy"
},
{
"id": 9,
"type": "column",
"value": "animal"
},
{
"id": 3,
"type": "column",
"value": "stuid"
},
{
"id": 8,
"type": "column",
"value": "food"
},
{
"id": 1,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "18"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"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": [
17
]
},
{
"entity_id": 9,
"token_idxs": [
19
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
670
|
retail_complains
|
bird:train.json:316
|
How many clients who live in Kansas City provided a 1-star review?
|
SELECT COUNT(T1.Stars) FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.city = 'Kansas City' AND T1.Stars = 1
|
[
"How",
"many",
"clients",
"who",
"live",
"in",
"Kansas",
"City",
"provided",
"a",
"1",
"-",
"star",
"review",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "district_id"
},
{
"id": 5,
"type": "value",
"value": "Kansas City"
},
{
"id": 1,
"type": "table",
"value": "district"
},
{
"id": 0,
"type": "table",
"value": "reviews"
},
{
"id": 2,
"type": "column",
"value": "stars"
},
{
"id": 4,
"type": "column",
"value": "city"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"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",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
671
|
works_cycles
|
bird:train.json:7136
|
Please list the businesses along with their numbers that have their accounts located in Duvall.
|
SELECT T2.BusinessEntityID FROM Address AS T1 INNER JOIN BusinessEntityAddress AS T2 ON T1.AddressID = T2.AddressID WHERE T1.City = 'Duvall'
|
[
"Please",
"list",
"the",
"businesses",
"along",
"with",
"their",
"numbers",
"that",
"have",
"their",
"accounts",
"located",
"in",
"Duvall",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "businessentityaddress"
},
{
"id": 0,
"type": "column",
"value": "businessentityid"
},
{
"id": 5,
"type": "column",
"value": "addressid"
},
{
"id": 1,
"type": "table",
"value": "address"
},
{
"id": 4,
"type": "value",
"value": "Duvall"
},
{
"id": 3,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
672
|
customers_and_invoices
|
spider:train_spider.json:1564
|
What are the customer ids for customers who do not have an account?
|
SELECT customer_id FROM Customers EXCEPT SELECT customer_id FROM Accounts
|
[
"What",
"are",
"the",
"customer",
"ids",
"for",
"customers",
"who",
"do",
"not",
"have",
"an",
"account",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "table",
"value": "accounts"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
3,
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",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
673
|
mountain_photos
|
spider:train_spider.json:3716
|
What are the name, height and prominence of mountains which do not belong to the range 'Aberdare Range'?
|
SELECT name , height , prominence FROM mountain WHERE range != 'Aberdare Range'
|
[
"What",
"are",
"the",
"name",
",",
"height",
"and",
"prominence",
"of",
"mountains",
"which",
"do",
"not",
"belong",
"to",
"the",
"range",
"'",
"Aberdare",
"Range",
"'",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Aberdare Range"
},
{
"id": 3,
"type": "column",
"value": "prominence"
},
{
"id": 0,
"type": "table",
"value": "mountain"
},
{
"id": 2,
"type": "column",
"value": "height"
},
{
"id": 4,
"type": "column",
"value": "range"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
19
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O"
] |
674
|
driving_school
|
spider:train_spider.json:6680
|
List the first name and last name of customers have the amount of outstanding between 1000 and 3000.
|
SELECT first_name , last_name FROM Customers WHERE amount_outstanding BETWEEN 1000 AND 3000;
|
[
"List",
"the",
"first",
"name",
"and",
"last",
"name",
"of",
"customers",
"have",
"the",
"amount",
"of",
"outstanding",
"between",
"1000",
"and",
"3000",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "amount_outstanding"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "value",
"value": "1000"
},
{
"id": 5,
"type": "value",
"value": "3000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
675
|
legislator
|
bird:train.json:4909
|
Give the type and start date of the term of the legislator born on November 26, 1727.
|
SELECT T2.type, T2.start FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.birthday_bio = '1727-11-26'
|
[
"Give",
"the",
"type",
"and",
"start",
"date",
"of",
"the",
"term",
"of",
"the",
"legislator",
"born",
"on",
"November",
"26",
",",
"1727",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "historical-terms"
},
{
"id": 4,
"type": "column",
"value": "birthday_bio"
},
{
"id": 6,
"type": "column",
"value": "bioguide_id"
},
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 5,
"type": "value",
"value": "1727-11-26"
},
{
"id": 7,
"type": "column",
"value": "bioguide"
},
{
"id": 1,
"type": "column",
"value": "start"
},
{
"id": 0,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
676
|
real_estate_rentals
|
bird:test.json:1454
|
What are the date stamps and property names for each item of property history, ordered by date stamp?
|
SELECT T1.datestamp , T2.property_name FROM User_Property_History AS T1 JOIN Properties AS T2 ON T1.property_id = T2.property_id ORDER BY datestamp;
|
[
"What",
"are",
"the",
"date",
"stamps",
"and",
"property",
"names",
"for",
"each",
"item",
"of",
"property",
"history",
",",
"ordered",
"by",
"date",
"stamp",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "user_property_history"
},
{
"id": 1,
"type": "column",
"value": "property_name"
},
{
"id": 4,
"type": "column",
"value": "property_id"
},
{
"id": 3,
"type": "table",
"value": "properties"
},
{
"id": 0,
"type": "column",
"value": "datestamp"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17,
18
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
677
|
professional_basketball
|
bird:train.json:2818
|
Of all the teams coached by the winner of the 1994 NBA Coach of the Year award, which team has lost the most times playing at home?
|
SELECT T3.tmID FROM awards_coaches AS T1 INNER JOIN coaches AS T2 ON T1.coachID = T2.coachID INNER JOIN teams AS T3 ON T3.tmID = T2.tmID WHERE T1.year = 1994 AND T1.award = 'NBA Coach of the Year' GROUP BY T3.tmID ORDER BY SUM(T3.homeLost) DESC LIMIT 1
|
[
"Of",
"all",
"the",
"teams",
"coached",
"by",
"the",
"winner",
"of",
"the",
"1994",
"NBA",
"Coach",
"of",
"the",
"Year",
"award",
",",
"which",
"team",
"has",
"lost",
"the",
"most",
"times",
"playing",
"at",
"home",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "NBA Coach of the Year"
},
{
"id": 2,
"type": "table",
"value": "awards_coaches"
},
{
"id": 8,
"type": "column",
"value": "homelost"
},
{
"id": 3,
"type": "table",
"value": "coaches"
},
{
"id": 9,
"type": "column",
"value": "coachid"
},
{
"id": 1,
"type": "table",
"value": "teams"
},
{
"id": 6,
"type": "column",
"value": "award"
},
{
"id": 0,
"type": "column",
"value": "tmid"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "1994"
}
] |
[
{
"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": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
16
]
},
{
"entity_id": 7,
"token_idxs": [
11,
12,
13,
14
]
},
{
"entity_id": 8,
"token_idxs": [
21
]
},
{
"entity_id": 9,
"token_idxs": [
4
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
678
|
beer_factory
|
bird:train.json:5290
|
Among the transactions, what percentage is done by using a visa card?
|
SELECT CAST(COUNT(CASE WHEN CreditCardType = 'Visa' THEN TransactionID ELSE NULL END) AS REAL) * 100 / COUNT(TransactionID) FROM `transaction`
|
[
"Among",
"the",
"transactions",
",",
"what",
"percentage",
"is",
"done",
"by",
"using",
"a",
"visa",
"card",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "creditcardtype"
},
{
"id": 2,
"type": "column",
"value": "transactionid"
},
{
"id": 0,
"type": "table",
"value": "transaction"
},
{
"id": 4,
"type": "value",
"value": "Visa"
},
{
"id": 1,
"type": "value",
"value": "100"
}
] |
[
{
"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": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
679
|
cs_semester
|
bird:train.json:950
|
What is the difference in the average GPA of students who took the hardest and easiest courses?
|
SELECT AVG(T1.gpa) FROM student AS T1 INNER JOIN registration AS T2 ON T1.student_id = T2.student_id INNER JOIN course AS T3 ON T2.course_id = T3.course_id WHERE T3.diff IN (2, 1) GROUP BY T3.diff
|
[
"What",
"is",
"the",
"difference",
"in",
"the",
"average",
"GPA",
"of",
"students",
"who",
"took",
"the",
"hardest",
"and",
"easiest",
"courses",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "registration"
},
{
"id": 8,
"type": "column",
"value": "student_id"
},
{
"id": 7,
"type": "column",
"value": "course_id"
},
{
"id": 5,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "table",
"value": "course"
},
{
"id": 0,
"type": "column",
"value": "diff"
},
{
"id": 4,
"type": "column",
"value": "gpa"
},
{
"id": 2,
"type": "value",
"value": "2"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
680
|
california_schools
|
bird:dev.json:31
|
What is the eligible free rate of the 10th and 11th schools with the highest enrolment for students in grades 1 through 12?
|
SELECT CAST(`Free Meal Count (K-12)` AS REAL) / `Enrollment (K-12)` FROM frpm ORDER BY `Enrollment (K-12)` DESC LIMIT 9, 2
|
[
"What",
"is",
"the",
"eligible",
"free",
"rate",
"of",
"the",
"10th",
"and",
"11th",
"schools",
"with",
"the",
"highest",
"enrolment",
"for",
"students",
"in",
"grades",
"1",
"through",
"12",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "Free Meal Count (K-12)"
},
{
"id": 1,
"type": "column",
"value": "Enrollment (K-12)"
},
{
"id": 0,
"type": "table",
"value": "frpm"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
681
|
bike_racing
|
bird:test.json:1474
|
What is the average price of the bikes made of material 'Carbon CC'?
|
SELECT avg(price) FROM bike WHERE material = 'Carbon CC'
|
[
"What",
"is",
"the",
"average",
"price",
"of",
"the",
"bikes",
"made",
"of",
"material",
"'",
"Carbon",
"CC",
"'",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "Carbon CC"
},
{
"id": 1,
"type": "column",
"value": "material"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "table",
"value": "bike"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
12,
13
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
682
|
movie_3
|
bird:train.json:9387
|
How many customers are still active?
|
SELECT COUNT(customer_id) FROM customer WHERE active = 1
|
[
"How",
"many",
"customers",
"are",
"still",
"active",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 1,
"type": "column",
"value": "active"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
683
|
movie_platform
|
bird:train.json:30
|
How much is the popularity of the movie that has the highest popularity between 1920 to 1929 and when did the movie received its first rating score of 1 from the users who were a paying subscriber when they rated the movie ?
|
SELECT MAX(T2.movie_popularity), MIN(T1.rating_timestamp_utc) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_release_year BETWEEN 1920 AND 1929 AND T1.rating_score = 1 AND T1.user_has_payment_method = 1
|
[
"How",
"much",
"is",
"the",
"popularity",
"of",
"the",
"movie",
"that",
"has",
"the",
"highest",
"popularity",
"between",
"1920",
"to",
"1929",
"and",
"when",
"did",
"the",
"movie",
"received",
"its",
"first",
"rating",
"score",
"of",
"1",
"from",
"the",
"users",
"who",
"were",
"a",
"paying",
"subscriber",
"when",
"they",
"rated",
"the",
"movie",
"?"
] |
[
{
"id": 10,
"type": "column",
"value": "user_has_payment_method"
},
{
"id": 3,
"type": "column",
"value": "rating_timestamp_utc"
},
{
"id": 5,
"type": "column",
"value": "movie_release_year"
},
{
"id": 2,
"type": "column",
"value": "movie_popularity"
},
{
"id": 8,
"type": "column",
"value": "rating_score"
},
{
"id": 4,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "table",
"value": "ratings"
},
{
"id": 1,
"type": "table",
"value": "movies"
},
{
"id": 6,
"type": "value",
"value": "1920"
},
{
"id": 7,
"type": "value",
"value": "1929"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
25
]
},
{
"entity_id": 1,
"token_idxs": [
21
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": [
26
]
},
{
"entity_id": 9,
"token_idxs": [
28
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
684
|
thrombosis_prediction
|
bird:dev.json:1205
|
Was the patient with the number 57266's uric acid within a normal range?
|
SELECT CASE WHEN (T1.SEX = 'F' AND T2.UA > 6.5) OR (T1.SEX = 'M' AND T2.UA > 8.0) THEN true ELSE false END FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T1.ID = 57266
|
[
"Was",
"the",
"patient",
"with",
"the",
"number",
"57266",
"'s",
"uric",
"acid",
"within",
"a",
"normal",
"range",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "value",
"value": "57266"
},
{
"id": 4,
"type": "column",
"value": "sex"
},
{
"id": 7,
"type": "value",
"value": "6.5"
},
{
"id": 9,
"type": "value",
"value": "8.0"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "column",
"value": "ua"
},
{
"id": 5,
"type": "value",
"value": "F"
},
{
"id": 8,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
686
|
soccer_2
|
spider:train_spider.json:5032
|
Find the names of schools that have some players in the mid position but not in the goalie position.
|
SELECT cName FROM tryout WHERE pPos = 'mid' EXCEPT SELECT cName FROM tryout WHERE pPos = 'goalie'
|
[
"Find",
"the",
"names",
"of",
"schools",
"that",
"have",
"some",
"players",
"in",
"the",
"mid",
"position",
"but",
"not",
"in",
"the",
"goalie",
"position",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "tryout"
},
{
"id": 4,
"type": "value",
"value": "goalie"
},
{
"id": 1,
"type": "column",
"value": "cname"
},
{
"id": 2,
"type": "column",
"value": "ppos"
},
{
"id": 3,
"type": "value",
"value": "mid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
687
|
climbing
|
spider:train_spider.json:1144
|
Show the countries that have mountains with height more than 5600 stories and mountains with height less than 5200.
|
SELECT Country FROM mountain WHERE Height > 5600 INTERSECT SELECT Country FROM mountain WHERE Height < 5200
|
[
"Show",
"the",
"countries",
"that",
"have",
"mountains",
"with",
"height",
"more",
"than",
"5600",
"stories",
"and",
"mountains",
"with",
"height",
"less",
"than",
"5200",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "mountain"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "height"
},
{
"id": 3,
"type": "value",
"value": "5600"
},
{
"id": 4,
"type": "value",
"value": "5200"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
688
|
aan_1
|
bird:test.json:996
|
What are the names of authors who have exactly 1 paper?
|
SELECT T1.name FROM Author AS T1 JOIN Author_list AS T2 ON T1.author_id = T2.author_id GROUP BY T1.author_id HAVING count(*) = 1
|
[
"What",
"are",
"the",
"names",
"of",
"authors",
"who",
"have",
"exactly",
"1",
"paper",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "author_list"
},
{
"id": 0,
"type": "column",
"value": "author_id"
},
{
"id": 2,
"type": "table",
"value": "author"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
689
|
student_loan
|
bird:train.json:4456
|
How many SMC's students that absent for 7 months?
|
SELECT COUNT(T1.name) FROM enrolled AS T1 INNER JOIN longest_absense_from_school AS T2 ON T1.name = T2.name WHERE T1.school = 'smc' AND T2.month = 7
|
[
"How",
"many",
"SMC",
"'s",
"students",
"that",
"absent",
"for",
"7",
"months",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 0,
"type": "table",
"value": "enrolled"
},
{
"id": 3,
"type": "column",
"value": "school"
},
{
"id": 5,
"type": "column",
"value": "month"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "smc"
},
{
"id": 6,
"type": "value",
"value": "7"
}
] |
[
{
"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": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
690
|
university_basketball
|
spider:train_spider.json:996
|
Return the average enrollment of universities founded before 1850.
|
SELECT avg(enrollment) FROM university WHERE founded < 1850
|
[
"Return",
"the",
"average",
"enrollment",
"of",
"universities",
"founded",
"before",
"1850",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 3,
"type": "column",
"value": "enrollment"
},
{
"id": 1,
"type": "column",
"value": "founded"
},
{
"id": 2,
"type": "value",
"value": "1850"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
691
|
address
|
bird:train.json:5163
|
Among the cities belonging to the country named Arroyo, calculate the percentage of increase in the population in these cities from 2010 to 2020.
|
SELECT CAST((SUM(T2.population_2020) - SUM(T2.population_2010)) AS REAL) * 100 / SUM(T2.population_2010) FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Arroyo'
|
[
"Among",
"the",
"cities",
"belonging",
"to",
"the",
"country",
"named",
"Arroyo",
",",
"calculate",
"the",
"percentage",
"of",
"increase",
"in",
"the",
"population",
"in",
"these",
"cities",
"from",
"2010",
"to",
"2020",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "population_2010"
},
{
"id": 7,
"type": "column",
"value": "population_2020"
},
{
"id": 1,
"type": "table",
"value": "zip_data"
},
{
"id": 4,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "value",
"value": "Arroyo"
},
{
"id": 2,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
17
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
692
|
bike_share_1
|
bird:train.json:9010
|
What is the maximum dew point in Fahrenheit degree on 7/15/2014 in the area with a zip code of 94301?
|
SELECT DISTINCT CASE WHEN date = '7/15/2014' AND zip_code = 94301 THEN max_dew_point_f END FROM weather
|
[
"What",
"is",
"the",
"maximum",
"dew",
"point",
"in",
"Fahrenheit",
"degree",
"on",
"7/15/2014",
"in",
"the",
"area",
"with",
"a",
"zip",
"code",
"of",
"94301",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "max_dew_point_f"
},
{
"id": 3,
"type": "value",
"value": "7/15/2014"
},
{
"id": 4,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 5,
"type": "value",
"value": "94301"
},
{
"id": 2,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
16,
17
]
},
{
"entity_id": 5,
"token_idxs": [
19
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
693
|
customer_complaints
|
spider:train_spider.json:5797
|
Return complaint status codes have more than 3 corresponding complaints?
|
SELECT complaint_status_code FROM complaints GROUP BY complaint_status_code HAVING count(*) > 3
|
[
"Return",
"complaint",
"status",
"codes",
"have",
"more",
"than",
"3",
"corresponding",
"complaints",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "complaint_status_code"
},
{
"id": 0,
"type": "table",
"value": "complaints"
},
{
"id": 2,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
1,
2,
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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O"
] |
694
|
mondial_geo
|
bird:train.json:8489
|
When did the United States of America attained it's Independence?
|
SELECT T1.Independence FROM politics AS T1 INNER JOIN country AS T2 ON T1.Country = T2.Code WHERE T2.Name = 'United States'
|
[
"When",
"did",
"the",
"United",
"States",
"of",
"America",
"attained",
"it",
"'s",
"Independence",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "United States"
},
{
"id": 0,
"type": "column",
"value": "independence"
},
{
"id": 1,
"type": "table",
"value": "politics"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
3,
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",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
695
|
city_record
|
spider:train_spider.json:6279
|
What is the temperature of "Shanghai" city in January?
|
SELECT T2.Jan FROM city AS T1 JOIN temperature AS T2 ON T1.city_id = T2.city_id WHERE T1.city = "Shanghai"
|
[
"What",
"is",
"the",
"temperature",
"of",
"\"",
"Shanghai",
"\"",
"city",
"in",
"January",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "temperature"
},
{
"id": 4,
"type": "column",
"value": "Shanghai"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 0,
"type": "column",
"value": "jan"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
696
|
soccer_2016
|
bird:train.json:1965
|
How many overs were there in each innings of match ID "336011"?
|
SELECT SUM(CASE WHEN Innings_No = 1 THEN 1 ELSE 0 END) AS IN1 , SUM(CASE WHEN Innings_No = 2 THEN 1 ELSE 0 END) AS IN2 FROM Ball_by_Ball WHERE Match_Id = 336011
|
[
"How",
"many",
"overs",
"were",
"there",
"in",
"each",
"innings",
"of",
"match",
"ID",
"\"",
"336011",
"\"",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "ball_by_ball"
},
{
"id": 5,
"type": "column",
"value": "innings_no"
},
{
"id": 1,
"type": "column",
"value": "match_id"
},
{
"id": 2,
"type": "value",
"value": "336011"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
697
|
wine_1
|
spider:train_spider.json:6519
|
Which winery is the wine that has the highest score from?
|
SELECT Winery FROM WINE ORDER BY SCORE LIMIT 1
|
[
"Which",
"winery",
"is",
"the",
"wine",
"that",
"has",
"the",
"highest",
"score",
"from",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "winery"
},
{
"id": 2,
"type": "column",
"value": "score"
},
{
"id": 0,
"type": "table",
"value": "wine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
698
|
car_retails
|
bird:train.json:1584
|
List out full name and email of employees who are working in Paris?
|
SELECT T1.firstName, T1.lastName, T1.email FROM employees AS T1 INNER JOIN offices AS T2 ON T1.officeCode = T2.officeCode WHERE T2.city = 'Paris'
|
[
"List",
"out",
"full",
"name",
"and",
"email",
"of",
"employees",
"who",
"are",
"working",
"in",
"Paris",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "officecode"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 3,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 4,
"type": "table",
"value": "offices"
},
{
"id": 2,
"type": "column",
"value": "email"
},
{
"id": 6,
"type": "value",
"value": "Paris"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
699
|
soccer_2016
|
bird:train.json:2025
|
How many seasons did Pune Warriors participate in?
|
SELECT COUNT(T.Season_Year) FROM ( SELECT T4.Season_Year FROM Team AS T1 INNER JOIN Match AS T2 ON T1.team_id = T2.match_winner INNER JOIN Player_Match AS T3 ON T1.Team_Id = T3.Team_Id INNER JOIN Season AS T4 ON T2.Season_Id = T4.Season_Id WHERE T1.Team_Name = 'Pune Warriors' GROUP BY T4.Season_Year ) T
|
[
"How",
"many",
"seasons",
"did",
"Pune",
"Warriors",
"participate",
"in",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Pune Warriors"
},
{
"id": 4,
"type": "table",
"value": "player_match"
},
{
"id": 9,
"type": "column",
"value": "match_winner"
},
{
"id": 0,
"type": "column",
"value": "season_year"
},
{
"id": 2,
"type": "column",
"value": "team_name"
},
{
"id": 5,
"type": "column",
"value": "season_id"
},
{
"id": 8,
"type": "column",
"value": "team_id"
},
{
"id": 1,
"type": "table",
"value": "season"
},
{
"id": 7,
"type": "table",
"value": "match"
},
{
"id": 6,
"type": "table",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
700
|
hockey
|
bird:train.json:7615
|
Who is the youngest player who is still living. State the given name and date of birth.
|
SELECT nameGiven , nameGiven , birthYear, birthMon, birthDay FROM Master WHERE deathYear IS NULL ORDER BY birthYear DESC, birthMon DESC, birthday DESC LIMIT 1
|
[
"Who",
"is",
"the",
"youngest",
"player",
"who",
"is",
"still",
"living",
".",
"State",
"the",
"given",
"name",
"and",
"date",
"of",
"birth",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "namegiven"
},
{
"id": 2,
"type": "column",
"value": "birthyear"
},
{
"id": 5,
"type": "column",
"value": "deathyear"
},
{
"id": 3,
"type": "column",
"value": "birthmon"
},
{
"id": 4,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "master"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O"
] |
701
|
sales_in_weather
|
bird:train.json:8158
|
How many no.9 items from store no.11 were sold on 2012/12/7?
|
SELECT units FROM sales_in_weather WHERE `date` = '2012-12-07' AND store_nbr = 11 AND item_nbr = 9
|
[
"How",
"many",
"no.9",
"items",
"from",
"store",
"no.11",
"were",
"sold",
"on",
"2012/12/7",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "sales_in_weather"
},
{
"id": 3,
"type": "value",
"value": "2012-12-07"
},
{
"id": 4,
"type": "column",
"value": "store_nbr"
},
{
"id": 6,
"type": "column",
"value": "item_nbr"
},
{
"id": 1,
"type": "column",
"value": "units"
},
{
"id": 2,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "value",
"value": "11"
},
{
"id": 7,
"type": "value",
"value": "9"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
702
|
loan_1
|
spider:train_spider.json:3029
|
In how many different states are banks located?
|
SELECT count(DISTINCT state) FROM bank
|
[
"In",
"how",
"many",
"different",
"states",
"are",
"banks",
"located",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "table",
"value": "bank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O"
] |
703
|
coffee_shop
|
spider:train_spider.json:794
|
Which membership card has more than 5 members?
|
SELECT Membership_card FROM member GROUP BY Membership_card HAVING count(*) > 5
|
[
"Which",
"membership",
"card",
"has",
"more",
"than",
"5",
"members",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "membership_card"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 2,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
1,
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
704
|
cookbook
|
bird:train.json:8863
|
What is the unsaturated fat content in the recipe "Raspberry Chiffon Pie"?
|
SELECT T2.total_fat - T2.sat_fat FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Raspberry Chiffon Pie'
|
[
"What",
"is",
"the",
"unsaturated",
"fat",
"content",
"in",
"the",
"recipe",
"\"",
"Raspberry",
"Chiffon",
"Pie",
"\"",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Raspberry Chiffon Pie"
},
{
"id": 1,
"type": "table",
"value": "nutrition"
},
{
"id": 4,
"type": "column",
"value": "total_fat"
},
{
"id": 6,
"type": "column",
"value": "recipe_id"
},
{
"id": 5,
"type": "column",
"value": "sat_fat"
},
{
"id": 0,
"type": "table",
"value": "recipe"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10,
11,
12
]
},
{
"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",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
705
|
e_learning
|
spider:train_spider.json:3772
|
What are the addresses of the course authors or tutors with personal name "Cathrine"
|
SELECT address_line_1 FROM Course_Authors_and_Tutors WHERE personal_name = "Cathrine"
|
[
"What",
"are",
"the",
"addresses",
"of",
"the",
"course",
"authors",
"or",
"tutors",
"with",
"personal",
"name",
"\"",
"Cathrine",
"\""
] |
[
{
"id": 0,
"type": "table",
"value": "course_authors_and_tutors"
},
{
"id": 1,
"type": "column",
"value": "address_line_1"
},
{
"id": 2,
"type": "column",
"value": "personal_name"
},
{
"id": 3,
"type": "column",
"value": "Cathrine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7,
8,
9
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11,
12
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O"
] |
706
|
movie_3
|
bird:train.json:9423
|
Among the times Mary Smith had rented a movie, how many of them happened in June, 2005?
|
SELECT COUNT(T1.customer_id) FROM payment AS T1 INNER JOIN customer AS T2 ON T1.customer_id = T2.customer_id WHERE T2.first_name = 'MARY' AND T2.last_name = 'SMITH' AND STRFTIME('%Y',T1.payment_date) = '2005' AND STRFTIME('%Y', T1.payment_date) = '6'
|
[
"Among",
"the",
"times",
"Mary",
"Smith",
"had",
"rented",
"a",
"movie",
",",
"how",
"many",
"of",
"them",
"happened",
"in",
"June",
",",
"2005",
"?"
] |
[
{
"id": 10,
"type": "column",
"value": "payment_date"
},
{
"id": 2,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "column",
"value": "first_name"
},
{
"id": 5,
"type": "column",
"value": "last_name"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "table",
"value": "payment"
},
{
"id": 6,
"type": "value",
"value": "SMITH"
},
{
"id": 4,
"type": "value",
"value": "MARY"
},
{
"id": 7,
"type": "value",
"value": "2005"
},
{
"id": 9,
"type": "value",
"value": "%Y"
},
{
"id": 8,
"type": "value",
"value": "6"
}
] |
[
{
"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": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": [
18
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
707
|
professional_basketball
|
bird:train.json:2928
|
What is the number of NBA titles that Ray Allen has won throughout his NBA career?
|
SELECT COUNT(T1.playerID) FROM player_allstar AS T1 INNER JOIN awards_players AS T2 ON T1.playerID = T2.playerID WHERE first_name = 'Ray' AND last_name = 'Allen'
|
[
"What",
"is",
"the",
"number",
"of",
"NBA",
"titles",
"that",
"Ray",
"Allen",
"has",
"won",
"throughout",
"his",
"NBA",
"career",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "player_allstar"
},
{
"id": 1,
"type": "table",
"value": "awards_players"
},
{
"id": 3,
"type": "column",
"value": "first_name"
},
{
"id": 5,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "column",
"value": "playerid"
},
{
"id": 6,
"type": "value",
"value": "Allen"
},
{
"id": 4,
"type": "value",
"value": "Ray"
}
] |
[
{
"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
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
708
|
flight_4
|
spider:train_spider.json:6829
|
Find the name, city, and country of the airport that has the lowest altitude.
|
SELECT name , city , country FROM airports ORDER BY elevation LIMIT 1
|
[
"Find",
"the",
"name",
",",
"city",
",",
"and",
"country",
"of",
"the",
"airport",
"that",
"has",
"the",
"lowest",
"altitude",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "elevation"
},
{
"id": 0,
"type": "table",
"value": "airports"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
709
|
food_inspection_2
|
bird:train.json:6137
|
What is the average number of inspections did risk level 3 taverns have?
|
SELECT CAST(COUNT(T2.inspection_id) AS REAL) / COUNT(DISTINCT T1.license_no) FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no WHERE T1.risk_level = 3 AND T1.facility_type = 'TAVERN'
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"inspections",
"did",
"risk",
"level",
"3",
"taverns",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "establishment"
},
{
"id": 5,
"type": "column",
"value": "facility_type"
},
{
"id": 7,
"type": "column",
"value": "inspection_id"
},
{
"id": 1,
"type": "table",
"value": "inspection"
},
{
"id": 2,
"type": "column",
"value": "license_no"
},
{
"id": 3,
"type": "column",
"value": "risk_level"
},
{
"id": 6,
"type": "value",
"value": "TAVERN"
},
{
"id": 4,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"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",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
710
|
retail_world
|
bird:train.json:6545
|
List all the product names and categories of the highest reorder level.
|
SELECT T2.ProductName, T1.CategoryName FROM Categories AS T1 INNER JOIN Products AS T2 ON T1.CategoryID = T2.CategoryID ORDER BY T2.ReorderLevel DESC LIMIT 1
|
[
"List",
"all",
"the",
"product",
"names",
"and",
"categories",
"of",
"the",
"highest",
"reorder",
"level",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "categoryname"
},
{
"id": 4,
"type": "column",
"value": "reorderlevel"
},
{
"id": 0,
"type": "column",
"value": "productname"
},
{
"id": 2,
"type": "table",
"value": "categories"
},
{
"id": 5,
"type": "column",
"value": "categoryid"
},
{
"id": 3,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": [
10,
11
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
712
|
department_store
|
spider:train_spider.json:4713
|
Find the number of different product types.
|
SELECT count(DISTINCT product_type_code) FROM products
|
[
"Find",
"the",
"number",
"of",
"different",
"product",
"types",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "product_type_code"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
713
|
retails
|
bird:train.json:6831
|
What is the region with the most customers?
|
SELECT T.r_name FROM ( SELECT T3.r_name, COUNT(T2.c_custkey) AS num FROM nation AS T1 INNER JOIN customer AS T2 ON T1.n_nationkey = T2.c_nationkey INNER JOIN region AS T3 ON T1.n_regionkey = T3.r_regionkey GROUP BY T3.r_name ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"What",
"is",
"the",
"region",
"with",
"the",
"most",
"customers",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "n_regionkey"
},
{
"id": 7,
"type": "column",
"value": "r_regionkey"
},
{
"id": 8,
"type": "column",
"value": "n_nationkey"
},
{
"id": 9,
"type": "column",
"value": "c_nationkey"
},
{
"id": 3,
"type": "column",
"value": "c_custkey"
},
{
"id": 5,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "r_name"
},
{
"id": 2,
"type": "table",
"value": "region"
},
{
"id": 4,
"type": "table",
"value": "nation"
},
{
"id": 1,
"type": "column",
"value": "num"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
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",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
714
|
planet_1
|
bird:test.json:1897
|
List all shipment ids for the planet Mars and under the management of Turanga Leela.
|
SELECT T1.ShipmentID FROM Shipment AS T1 JOIN Planet AS T2 ON T1.Planet = T2.PlanetID JOIN Employee AS T3 ON T3.EmployeeID = T1.Manager WHERE T2.Name = "Mars" AND T3.Name = "Turanga Leela";
|
[
"List",
"all",
"shipment",
"ids",
"for",
"the",
"planet",
"Mars",
"and",
"under",
"the",
"management",
"of",
"Turanga",
"Leela",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "Turanga Leela"
},
{
"id": 0,
"type": "column",
"value": "shipmentid"
},
{
"id": 4,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 10,
"type": "column",
"value": "planetid"
},
{
"id": 5,
"type": "column",
"value": "manager"
},
{
"id": 3,
"type": "table",
"value": "planet"
},
{
"id": 9,
"type": "column",
"value": "planet"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "Mars"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": [
13,
14
]
},
{
"entity_id": 9,
"token_idxs": [
6
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
715
|
car_retails
|
bird:train.json:1593
|
Who is the sales agent of the customer who has made the highest payment? Include the full names of employee and his/her supervisor.
|
SELECT T1.firstName, T1.lastName, T1.reportsTo FROM employees AS T1 INNER JOIN customers AS T2 ON T1.employeeNumber = T2.salesRepEmployeeNumber INNER JOIN payments AS T3 ON T2.customerNumber = T3.customerNumber ORDER BY T3.amount DESC LIMIT 1
|
[
"Who",
"is",
"the",
"sales",
"agent",
"of",
"the",
"customer",
"who",
"has",
"made",
"the",
"highest",
"payment",
"?",
"Include",
"the",
"full",
"names",
"of",
"employee",
"and",
"his",
"/",
"her",
"supervisor",
"."
] |
[
{
"id": 9,
"type": "column",
"value": "salesrepemployeenumber"
},
{
"id": 7,
"type": "column",
"value": "customernumber"
},
{
"id": 8,
"type": "column",
"value": "employeenumber"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "column",
"value": "reportsto"
},
{
"id": 5,
"type": "table",
"value": "employees"
},
{
"id": 6,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "table",
"value": "payments"
},
{
"id": 4,
"type": "column",
"value": "amount"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
18
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"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",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
716
|
wine_1
|
spider:train_spider.json:6567
|
Find the distinct names of wines produced before the year of 2000 or after the year of 2010.
|
SELECT DISTINCT Name FROM WINE WHERE YEAR < 2000 OR YEAR > 2010
|
[
"Find",
"the",
"distinct",
"names",
"of",
"wines",
"produced",
"before",
"the",
"year",
"of",
"2000",
"or",
"after",
"the",
"year",
"of",
"2010",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "wine"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2000"
},
{
"id": 4,
"type": "value",
"value": "2010"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
717
|
movie_3
|
bird:train.json:9263
|
How many payments were made throughout the month of August 2005?
|
SELECT SUM(amount) FROM payment WHERE payment_date LIKE '2005-08%'
|
[
"How",
"many",
"payments",
"were",
"made",
"throughout",
"the",
"month",
"of",
"August",
"2005",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "payment_date"
},
{
"id": 2,
"type": "value",
"value": "2005-08%"
},
{
"id": 0,
"type": "table",
"value": "payment"
},
{
"id": 3,
"type": "column",
"value": "amount"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
718
|
trains
|
bird:train.json:700
|
Please list the directions in which the trains with at least one empty-loaded car run.
|
SELECT T2.direction FROM cars AS T1 INNER JOIN trains AS T2 ON T1.train_id = T2.id WHERE T1.load_num = 0
|
[
"Please",
"list",
"the",
"directions",
"in",
"which",
"the",
"trains",
"with",
"at",
"least",
"one",
"empty",
"-",
"loaded",
"car",
"run",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "direction"
},
{
"id": 3,
"type": "column",
"value": "load_num"
},
{
"id": 5,
"type": "column",
"value": "train_id"
},
{
"id": 2,
"type": "table",
"value": "trains"
},
{
"id": 1,
"type": "table",
"value": "cars"
},
{
"id": 6,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"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",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
719
|
restaurant_1
|
spider:train_spider.json:2824
|
What is the description of the restaurant type Sandwich?
|
SELECT ResTypeDescription FROM Restaurant_Type WHERE ResTypeName = "Sandwich";
|
[
"What",
"is",
"the",
"description",
"of",
"the",
"restaurant",
"type",
"Sandwich",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "restypedescription"
},
{
"id": 0,
"type": "table",
"value": "restaurant_type"
},
{
"id": 2,
"type": "column",
"value": "restypename"
},
{
"id": 3,
"type": "column",
"value": "Sandwich"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O"
] |
720
|
customers_campaigns_ecommerce
|
spider:train_spider.json:4627
|
Show the outcome code of mailshots along with the number of mailshots in each outcome code.
|
SELECT outcome_code , count(*) FROM mailshot_customers GROUP BY outcome_code
|
[
"Show",
"the",
"outcome",
"code",
"of",
"mailshots",
"along",
"with",
"the",
"number",
"of",
"mailshots",
"in",
"each",
"outcome",
"code",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "mailshot_customers"
},
{
"id": 1,
"type": "column",
"value": "outcome_code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
2,
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-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
721
|
culture_company
|
spider:train_spider.json:6968
|
Show the years, book titles, and publishers for all books, in descending order by year.
|
SELECT YEAR , book_title , publisher FROM book_club ORDER BY YEAR DESC
|
[
"Show",
"the",
"years",
",",
"book",
"titles",
",",
"and",
"publishers",
"for",
"all",
"books",
",",
"in",
"descending",
"order",
"by",
"year",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "book_title"
},
{
"id": 0,
"type": "table",
"value": "book_club"
},
{
"id": 3,
"type": "column",
"value": "publisher"
},
{
"id": 1,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
723
|
manufactory_1
|
spider:train_spider.json:5289
|
Who is the founders of companies whose first letter is S?
|
SELECT founder FROM manufacturers WHERE name LIKE 'S%'
|
[
"Who",
"is",
"the",
"founders",
"of",
"companies",
"whose",
"first",
"letter",
"is",
"S",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "manufacturers"
},
{
"id": 1,
"type": "column",
"value": "founder"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "S%"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
724
|
public_review_platform
|
bird:train.json:3995
|
How many business have low check-in on Sunday at 10AM?
|
SELECT COUNT(T2.business_id) FROM Days AS T1 INNER JOIN Checkins AS T2 ON T1.day_id = T2.day_id WHERE T1.day_of_week = 'Sunday' AND T2.label_time_10 = 'Low'
|
[
"How",
"many",
"business",
"have",
"low",
"check",
"-",
"in",
"on",
"Sunday",
"at",
"10AM",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "label_time_10"
},
{
"id": 2,
"type": "column",
"value": "business_id"
},
{
"id": 4,
"type": "column",
"value": "day_of_week"
},
{
"id": 1,
"type": "table",
"value": "checkins"
},
{
"id": 3,
"type": "column",
"value": "day_id"
},
{
"id": 5,
"type": "value",
"value": "Sunday"
},
{
"id": 0,
"type": "table",
"value": "days"
},
{
"id": 7,
"type": "value",
"value": "Low"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
725
|
hockey
|
bird:train.json:7639
|
Among the coaches who was never a player, who has highest percentage of game winning? Provide the given name of the coach and team he coached.
|
SELECT T2.nameGiven, T3.name FROM Coaches AS T1 INNER JOIN Master AS T2 ON T2.coachID = T1.coachID INNER JOIN Teams AS T3 ON T1.lgID = T3.lgID WHERE T1.coachID IS NOT NULL ORDER BY CAST(T1.w AS REAL) / T1.g DESC LIMIT 1
|
[
"Among",
"the",
"coaches",
"who",
"was",
"never",
"a",
"player",
",",
"who",
"has",
"highest",
"percentage",
"of",
"game",
"winning",
"?",
"Provide",
"the",
"given",
"name",
"of",
"the",
"coach",
"and",
"team",
"he",
"coached",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "namegiven"
},
{
"id": 3,
"type": "column",
"value": "coachid"
},
{
"id": 4,
"type": "table",
"value": "coaches"
},
{
"id": 5,
"type": "table",
"value": "master"
},
{
"id": 2,
"type": "table",
"value": "teams"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "lgid"
},
{
"id": 7,
"type": "column",
"value": "g"
},
{
"id": 8,
"type": "column",
"value": "w"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
25
]
},
{
"entity_id": 3,
"token_idxs": [
27
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O"
] |
726
|
law_episode
|
bird:train.json:1314
|
What are the names of all the people who worked on episode 19 of season 9?
|
SELECT T3.name FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T1.episode = 19 AND T1.season = 9
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"the",
"people",
"who",
"worked",
"on",
"episode",
"19",
"of",
"season",
"9",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "episode_id"
},
{
"id": 4,
"type": "column",
"value": "person_id"
},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 5,
"type": "column",
"value": "episode"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "table",
"value": "credit"
},
{
"id": 7,
"type": "column",
"value": "season"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "19"
},
{
"id": 8,
"type": "value",
"value": "9"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": [
15
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
728
|
movie
|
bird:train.json:764
|
List the height and net worth of actors starred in Three Men and a Little Lady.
|
SELECT T3.`Height (Inches)`, T3.NetWorth FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE T1.Title = 'Three Men and a Little Lady'
|
[
"List",
"the",
"height",
"and",
"net",
"worth",
"of",
"actors",
"starred",
"in",
"Three",
"Men",
"and",
"a",
"Little",
"Lady",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Three Men and a Little Lady"
},
{
"id": 0,
"type": "column",
"value": "Height (Inches)"
},
{
"id": 6,
"type": "table",
"value": "characters"
},
{
"id": 1,
"type": "column",
"value": "networth"
},
{
"id": 7,
"type": "column",
"value": "actorid"
},
{
"id": 8,
"type": "column",
"value": "movieid"
},
{
"id": 2,
"type": "table",
"value": "actor"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "table",
"value": "movie"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
10,
11,
12,
13,
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"B-VALUE",
"O"
] |
729
|
chicago_crime
|
bird:train.json:8632
|
In the most populated ward, how many incidents of domestic violence were reported in a bar or tavern?
|
SELECT COUNT(T2.report_no) FROM Ward AS T1 INNER JOIN Crime AS T2 ON T1.ward_no = T2.ward_no WHERE T2.domestic = 'TRUE' AND T2.location_description = 'BAR OR TAVERN' ORDER BY T1.Population DESC LIMIT 1
|
[
"In",
"the",
"most",
"populated",
"ward",
",",
"how",
"many",
"incidents",
"of",
"domestic",
"violence",
"were",
"reported",
"in",
"a",
"bar",
"or",
"tavern",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "location_description"
},
{
"id": 8,
"type": "value",
"value": "BAR OR TAVERN"
},
{
"id": 2,
"type": "column",
"value": "population"
},
{
"id": 3,
"type": "column",
"value": "report_no"
},
{
"id": 5,
"type": "column",
"value": "domestic"
},
{
"id": 4,
"type": "column",
"value": "ward_no"
},
{
"id": 1,
"type": "table",
"value": "crime"
},
{
"id": 0,
"type": "table",
"value": "ward"
},
{
"id": 6,
"type": "value",
"value": "TRUE"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"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": [
16,
17,
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",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
730
|
simpson_episodes
|
bird:train.json:4342
|
Which are the years that character Mr. Burns won an award?
|
SELECT DISTINCT T1.year FROM Award AS T1 INNER JOIN Character_Award AS T2 ON T1.award_id = T2.award_id WHERE T2.character = 'Mr. Burns';
|
[
"Which",
"are",
"the",
"years",
"that",
"character",
"Mr.",
"Burns",
"won",
"an",
"award",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "character_award"
},
{
"id": 3,
"type": "column",
"value": "character"
},
{
"id": 4,
"type": "value",
"value": "Mr. Burns"
},
{
"id": 5,
"type": "column",
"value": "award_id"
},
{
"id": 1,
"type": "table",
"value": "award"
},
{
"id": 0,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
6,
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
731
|
books
|
bird:train.json:6091
|
List down the ISBN of the books purchased by the customer with an email of fsier3e@ihg.com.
|
SELECT T1.isbn13 FROM book AS T1 INNER JOIN order_line AS T2 ON T1.book_id = T2.book_id INNER JOIN cust_order AS T3 ON T3.order_id = T2.order_id INNER JOIN customer AS T4 ON T4.customer_id = T3.customer_id WHERE T4.email = 'fsier3e@ihg.com'
|
[
"List",
"down",
"the",
"ISBN",
"of",
"the",
"books",
"purchased",
"by",
"the",
"customer",
"with",
"an",
"email",
"of",
"fsier3e@ihg.com",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "fsier3e@ihg.com"
},
{
"id": 5,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "table",
"value": "cust_order"
},
{
"id": 7,
"type": "table",
"value": "order_line"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 8,
"type": "column",
"value": "order_id"
},
{
"id": 9,
"type": "column",
"value": "book_id"
},
{
"id": 0,
"type": "column",
"value": "isbn13"
},
{
"id": 2,
"type": "column",
"value": "email"
},
{
"id": 6,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
732
|
airline
|
bird:train.json:5903
|
What is the tail number of the flight with air carrier named Iscargo Hf: ICQ and arrival time of 1000 and below?
|
SELECT T2.TAIL_NUM FROM `Air Carriers` AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.OP_CARRIER_AIRLINE_ID WHERE T2.ARR_TIME <= 1000 AND T1.Description = 'Iscargo Hf: ICQ'
|
[
"What",
"is",
"the",
"tail",
"number",
"of",
"the",
"flight",
"with",
"air",
"carrier",
"named",
"Iscargo",
"Hf",
":",
"ICQ",
"and",
"arrival",
"time",
"of",
"1000",
"and",
"below",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 8,
"type": "value",
"value": "Iscargo Hf: ICQ"
},
{
"id": 1,
"type": "table",
"value": "Air Carriers"
},
{
"id": 7,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "column",
"value": "tail_num"
},
{
"id": 2,
"type": "table",
"value": "airlines"
},
{
"id": 5,
"type": "column",
"value": "arr_time"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "value",
"value": "1000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
17,
18
]
},
{
"entity_id": 6,
"token_idxs": [
20
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
12,
13,
14,
15
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
733
|
financial
|
bird:dev.json:117
|
What is the percentage of loan amount that has been fully paid with no issue.
|
SELECT (CAST(SUM(CASE WHEN status = 'A' THEN amount ELSE 0 END) AS REAL) * 100) / SUM(amount) FROM loan
|
[
"What",
"is",
"the",
"percentage",
"of",
"loan",
"amount",
"that",
"has",
"been",
"fully",
"paid",
"with",
"no",
"issue",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "amount"
},
{
"id": 4,
"type": "column",
"value": "status"
},
{
"id": 0,
"type": "table",
"value": "loan"
},
{
"id": 1,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "A"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
734
|
card_games
|
bird:dev.json:520
|
Who is the illustrator that illustrated the least amount of cards? List the format of play of the cards that he/she illustrated.
|
SELECT T1.artist, T2.format FROM cards AS T1 INNER JOIN legalities AS T2 ON T2.uuid = T1.uuid GROUP BY T1.artist ORDER BY COUNT(T1.id) ASC LIMIT 1
|
[
"Who",
"is",
"the",
"illustrator",
"that",
"illustrated",
"the",
"least",
"amount",
"of",
"cards",
"?",
"List",
"the",
"format",
"of",
"play",
"of",
"the",
"cards",
"that",
"he",
"/",
"she",
"illustrated",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "legalities"
},
{
"id": 0,
"type": "column",
"value": "artist"
},
{
"id": 1,
"type": "column",
"value": "format"
},
{
"id": 2,
"type": "table",
"value": "cards"
},
{
"id": 4,
"type": "column",
"value": "uuid"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
735
|
station_weather
|
spider:train_spider.json:3172
|
Find the origins from which more than 1 train starts.
|
SELECT origin FROM train GROUP BY origin HAVING count(*) > 1
|
[
"Find",
"the",
"origins",
"from",
"which",
"more",
"than",
"1",
"train",
"starts",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "origin"
},
{
"id": 0,
"type": "table",
"value": "train"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O"
] |
736
|
movie_platform
|
bird:train.json:38
|
How many users who created a list in the February of 2016 were eligible for trial when they created the list? Indicate the user id of the user who has the most number of followers in his list in February of 2016.
|
SELECT T1.list_followers FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.user_id = T2.user_id AND T1.list_id = T2.list_id WHERE T2.list_creation_date_utc BETWEEN '2016-02-01' AND '2016-02-29' AND T2.user_eligible_for_trial = 1
|
[
"How",
"many",
"users",
"who",
"created",
"a",
"list",
"in",
"the",
"February",
"of",
"2016",
"were",
"eligible",
"for",
"trial",
"when",
"they",
"created",
"the",
"list",
"?",
"Indicate",
"the",
"user",
"i",
"d",
"of",
"the",
"user",
"who",
"has",
"the",
"most",
"number",
"of",
"followers",
"in",
"his",
"list",
"in",
"February",
"of",
"2016",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "user_eligible_for_trial"
},
{
"id": 3,
"type": "column",
"value": "list_creation_date_utc"
},
{
"id": 0,
"type": "column",
"value": "list_followers"
},
{
"id": 2,
"type": "table",
"value": "lists_users"
},
{
"id": 4,
"type": "value",
"value": "2016-02-01"
},
{
"id": 5,
"type": "value",
"value": "2016-02-29"
},
{
"id": 8,
"type": "column",
"value": "user_id"
},
{
"id": 9,
"type": "column",
"value": "list_id"
},
{
"id": 1,
"type": "table",
"value": "lists"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
36
]
},
{
"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": [
13,
14,
15
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
24,
25,
26
]
},
{
"entity_id": 9,
"token_idxs": [
39
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
737
|
authors
|
bird:train.json:3613
|
Who authored the paper titled "Testing timed automata
"?
|
SELECT T2.Name FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Title = 'Testing timed automata'
|
[
"Who",
"authored",
"the",
"paper",
"titled",
"\"",
"Testing",
"timed",
"automata",
"\n",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Testing timed automata"
},
{
"id": 2,
"type": "table",
"value": "paperauthor"
},
{
"id": 6,
"type": "column",
"value": "paperid"
},
{
"id": 1,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
6,
7,
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",
"B-TABLE",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
738
|
synthea
|
bird:train.json:1455
|
How many patients with care plan for 'concussion with loss of consciousness' are married?
|
SELECT COUNT(DISTINCT T1.patient) FROM patients AS T1 INNER JOIN careplans AS T2 ON T1.patient = T2.PATIENT WHERE T1.marital = 'M' AND T2.REASONDESCRIPTION = 'Concussion with loss of consciousness'
|
[
"How",
"many",
"patients",
"with",
"care",
"plan",
"for",
"'",
"concussion",
"with",
"loss",
"of",
"consciousness",
"'",
"are",
"married",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Concussion with loss of consciousness"
},
{
"id": 5,
"type": "column",
"value": "reasondescription"
},
{
"id": 1,
"type": "table",
"value": "careplans"
},
{
"id": 0,
"type": "table",
"value": "patients"
},
{
"id": 2,
"type": "column",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "marital"
},
{
"id": 4,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8,
9,
10,
11,
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
739
|
mondial_geo
|
bird:train.json:8295
|
What is the most populated city of the 12th highest density country?
|
SELECT T2.Name FROM country AS T1 INNER JOIN city AS T2 ON T1.Code = T2.Country WHERE T1.Name = ( SELECT Name FROM country ORDER BY CAST(Population AS REAL) / Area LIMIT 11, 1 ) ORDER BY T2.Population DESC LIMIT 1
|
[
"What",
"is",
"the",
"most",
"populated",
"city",
"of",
"the",
"12th",
"highest",
"density",
"country",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "population"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "column",
"value": "area"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
740
|
movie_1
|
spider:train_spider.json:2521
|
What are the ids of all reviewers who did not give 4 stars?
|
SELECT rID FROM Rating EXCEPT SELECT rID FROM Rating WHERE stars = 4
|
[
"What",
"are",
"the",
"ids",
"of",
"all",
"reviewers",
"who",
"did",
"not",
"give",
"4",
"stars",
"?"
] |
[
{
"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": [
8
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
741
|
toxicology
|
bird:dev.json:218
|
What percentage of carcinogenic-type molecules does not contain fluorine?
|
SELECT CAST(COUNT(DISTINCT CASE WHEN T1.element <> 'f' THEN T2.molecule_id ELSE NULL END) AS REAL) * 100 / COUNT(DISTINCT T2.molecule_id) FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T2.label = '+'
|
[
"What",
"percentage",
"of",
"carcinogenic",
"-",
"type",
"molecules",
"does",
"not",
"contain",
"fluorine",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "molecule_id"
},
{
"id": 1,
"type": "table",
"value": "molecule"
},
{
"id": 6,
"type": "column",
"value": "element"
},
{
"id": 2,
"type": "column",
"value": "label"
},
{
"id": 0,
"type": "table",
"value": "atom"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "+"
},
{
"id": 7,
"type": "value",
"value": "f"
}
] |
[
{
"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": [
2
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
742
|
professional_basketball
|
bird:train.json:2894
|
Name the youngest player who ever won "Rookie of the Year".
|
SELECT T1.firstName, T1.middleName, T1.lastName FROM players AS T1 INNER JOIN awards_players AS T2 ON T1.playerID = T2.playerID WHERE T2.award = 'Rookie of the Year' ORDER BY T1.birthDate DESC LIMIT 1
|
[
"Name",
"the",
"youngest",
"player",
"who",
"ever",
"won",
"\"",
"Rookie",
"of",
"the",
"Year",
"\"",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "Rookie of the Year"
},
{
"id": 4,
"type": "table",
"value": "awards_players"
},
{
"id": 1,
"type": "column",
"value": "middlename"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 7,
"type": "column",
"value": "birthdate"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 8,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "table",
"value": "players"
},
{
"id": 5,
"type": "column",
"value": "award"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
0
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8,
9,
10,
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": []
}
] |
[
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
743
|
superhero
|
bird:dev.json:800
|
Calculate the percentage of superheroes with blue eyes.
|
SELECT CAST(COUNT(CASE WHEN T2.colour = 'Blue' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.id) FROM superhero AS T1 INNER JOIN colour AS T2 ON T1.eye_colour_id = T2.id
|
[
"Calculate",
"the",
"percentage",
"of",
"superheroes",
"with",
"blue",
"eyes",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "eye_colour_id"
},
{
"id": 0,
"type": "table",
"value": "superhero"
},
{
"id": 1,
"type": "table",
"value": "colour"
},
{
"id": 6,
"type": "column",
"value": "colour"
},
{
"id": 7,
"type": "value",
"value": "Blue"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O"
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.