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16.1k
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5,753
|
legislator
|
bird:train.json:4775
|
Give the YouTube ID of the channel 'RepWassermanSchultz.'
|
SELECT youtube_id FROM `social-media` WHERE youtube = 'RepWassermanSchultz'
|
[
"Give",
"the",
"YouTube",
"ID",
"of",
"the",
"channel",
"'",
"RepWassermanSchultz",
".",
"'"
] |
[
{
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{
"id": 0,
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{
"id": 1,
"type": "column",
"value": "youtube_id"
},
{
"id": 2,
"type": "column",
"value": "youtube"
}
] |
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[
"O",
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"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,219
|
sales
|
bird:train.json:5415
|
List the full name of the customer who purchased the most quantity of products.
|
SELECT T1.FirstName, T1.LastName FROM Customers AS T1 INNER JOIN Sales AS T2 ON T1.CustomerID = T2.CustomerID ORDER BY T2.Quantity DESC LIMIT 1
|
[
"List",
"the",
"full",
"name",
"of",
"the",
"customer",
"who",
"purchased",
"the",
"most",
"quantity",
"of",
"products",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 4,
"type": "column",
"value": "quantity"
},
{
"id": 3,
"type": "table",
"value": "sales"
}
] |
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"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
4,471
|
customers_and_addresses
|
spider:train_spider.json:6059
|
What is the average amount of items ordered in each order?
|
SELECT avg(order_quantity) FROM order_items
|
[
"What",
"is",
"the",
"average",
"amount",
"of",
"items",
"ordered",
"in",
"each",
"order",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "order_quantity"
},
{
"id": 0,
"type": "table",
"value": "order_items"
}
] |
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[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
5,507
|
tracking_share_transactions
|
spider:train_spider.json:5859
|
How many distinct transaction types are used in the transactions?
|
SELECT COUNT(DISTINCT transaction_type_code) FROM TRANSACTIONS
|
[
"How",
"many",
"distinct",
"transaction",
"types",
"are",
"used",
"in",
"the",
"transactions",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "transaction_type_code"
},
{
"id": 0,
"type": "table",
"value": "transactions"
}
] |
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[
"O",
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"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,485
|
movie_platform
|
bird:train.json:13
|
For movie titled 'Welcome to the Dollhouse', how many percentage of the ratings were rated with highest score.
|
SELECT CAST(SUM(CASE WHEN T2.rating_score = 5 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM movies AS T1 INNER JOIN ratings AS T2 ON T1.movie_id = T2.movie_id WHERE T1.movie_title = 'Welcome to the Dollhouse'
|
[
"For",
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"'",
"Welcome",
"to",
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"Dollhouse",
"'",
",",
"how",
"many",
"percentage",
"of",
"the",
"ratings",
"were",
"rated",
"with",
"highest",
"score",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Welcome to the Dollhouse"
},
{
"id": 8,
"type": "column",
"value": "rating_score"
},
{
"id": 2,
"type": "column",
"value": "movie_title"
},
{
"id": 4,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "ratings"
},
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "5"
}
] |
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[
"O",
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"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
6,455
|
hockey
|
bird:train.json:7689
|
Did legendsID "P194502" personally attend his Hall of Fame dedication?
|
SELECT IIF(T1.note = 'posthumous', 'YES', 'NO') FROM AwardsMisc AS T1 RIGHT JOIN Master AS T2 ON T1.ID = T2.playerID WHERE T2.legendsID = 'P194502'
|
[
"Did",
"legendsID",
"\"",
"P194502",
"\"",
"personally",
"attend",
"his",
"Hall",
"of",
"Fame",
"dedication",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "awardsmisc"
},
{
"id": 9,
"type": "value",
"value": "posthumous"
},
{
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"type": "column",
"value": "legendsid"
},
{
"id": 7,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "value",
"value": "P194502"
},
{
"id": 1,
"type": "table",
"value": "master"
},
{
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"type": "column",
"value": "note"
},
{
"id": 4,
"type": "value",
"value": "YES"
},
{
"id": 5,
"type": "value",
"value": "NO"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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[
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"O",
"O",
"O",
"O",
"O",
"O"
] |
9,883
|
manufacturer
|
spider:train_spider.json:3389
|
How many furniture components are there in total?
|
SELECT sum(num_of_component) FROM furniture
|
[
"How",
"many",
"furniture",
"components",
"are",
"there",
"in",
"total",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "num_of_component"
},
{
"id": 0,
"type": "table",
"value": "furniture"
}
] |
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[
"O",
"O",
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"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
10,926
|
works_cycles
|
bird:train.json:7148
|
What is the minimum shipping charge for "OVERSEAS - DELUXE"?
|
SELECT ShipBase FROM ShipMethod WHERE Name = 'OVERSEAS - DELUXE'
|
[
"What",
"is",
"the",
"minimum",
"shipping",
"charge",
"for",
"\"",
"OVERSEAS",
"-",
"DELUXE",
"\"",
"?"
] |
[
{
"id": 3,
"type": "value",
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},
{
"id": 0,
"type": "table",
"value": "shipmethod"
},
{
"id": 1,
"type": "column",
"value": "shipbase"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
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[
"O",
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"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
3,295
|
car_racing
|
bird:test.json:1629
|
List the names of teams that do not have any drivers.
|
SELECT Team FROM team WHERE Team_ID NOT IN (SELECT Team_ID FROM team_driver)
|
[
"List",
"the",
"names",
"of",
"teams",
"that",
"do",
"not",
"have",
"any",
"drivers",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "team_driver"
},
{
"id": 2,
"type": "column",
"value": "team_id"
},
{
"id": 0,
"type": "table",
"value": "team"
},
{
"id": 1,
"type": "column",
"value": "team"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
16,027
|
gas_company
|
spider:train_spider.json:2028
|
What are the names of the managers for gas stations that are operated by the ExxonMobil company?
|
SELECT T3.manager_name FROM station_company AS T1 JOIN company AS T2 ON T1.company_id = T2.company_id JOIN gas_station AS T3 ON T1.station_id = T3.station_id WHERE T2.company = 'ExxonMobil'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"managers",
"for",
"gas",
"stations",
"that",
"are",
"operated",
"by",
"the",
"ExxonMobil",
"company",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "station_company"
},
{
"id": 0,
"type": "column",
"value": "manager_name"
},
{
"id": 1,
"type": "table",
"value": "gas_station"
},
{
"id": 3,
"type": "value",
"value": "ExxonMobil"
},
{
"id": 6,
"type": "column",
"value": "station_id"
},
{
"id": 7,
"type": "column",
"value": "company_id"
},
{
"id": 2,
"type": "column",
"value": "company"
},
{
"id": 5,
"type": "table",
"value": "company"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
6
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
11,769
|
chicago_crime
|
bird:train.json:8684
|
Find the ward office's address and phone number of the ward where the most crimes without arrest occurred.
|
SELECT T2.ward_office_address, T2.ward_office_phone FROM Crime AS T1 INNER JOIN Ward AS T2 ON T2.ward_no = T1.ward_no WHERE T1.arrest = 'FALSE' GROUP BY T2.ward_office_address, T2.ward_office_phone ORDER BY COUNT(T1.arrest) DESC LIMIT 1
|
[
"Find",
"the",
"ward",
"office",
"'s",
"address",
"and",
"phone",
"number",
"of",
"the",
"ward",
"where",
"the",
"most",
"crimes",
"without",
"arrest",
"occurred",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "ward_office_address"
},
{
"id": 1,
"type": "column",
"value": "ward_office_phone"
},
{
"id": 6,
"type": "column",
"value": "ward_no"
},
{
"id": 4,
"type": "column",
"value": "arrest"
},
{
"id": 2,
"type": "table",
"value": "crime"
},
{
"id": 5,
"type": "value",
"value": "FALSE"
},
{
"id": 3,
"type": "table",
"value": "ward"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O"
] |
9,977
|
law_episode
|
bird:train.json:1340
|
What is the episode rating with the most award won?
|
SELECT T1.rating FROM Episode AS T1 INNER JOIN Award AS T2 ON T1.episode_id = T2.episode_id WHERE T2.result = 'Winner' GROUP BY T1.episode_id ORDER BY COUNT(T2.award_id) DESC LIMIT 1
|
[
"What",
"is",
"the",
"episode",
"rating",
"with",
"the",
"most",
"award",
"won",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "episode_id"
},
{
"id": 6,
"type": "column",
"value": "award_id"
},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 1,
"type": "column",
"value": "rating"
},
{
"id": 4,
"type": "column",
"value": "result"
},
{
"id": 5,
"type": "value",
"value": "Winner"
},
{
"id": 3,
"type": "table",
"value": "award"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,063
|
music_tracker
|
bird:train.json:2079
|
List the name of artists who have released albums and mixtape from 1980 to 1985 in "dance" genre.
|
SELECT COUNT(T1.artist) FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T2.tag = 'dance' AND T1.groupYear BETWEEN 1980 AND 1985 AND T1.releaseType LIKE 'album' OR T1.releaseType LIKE 'mixtape'
|
[
"List",
"the",
"name",
"of",
"artists",
"who",
"have",
"released",
"albums",
"and",
"mixtape",
"from",
"1980",
"to",
"1985",
"in",
"\"",
"dance",
"\"",
"genre",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "releasetype"
},
{
"id": 8,
"type": "column",
"value": "groupyear"
},
{
"id": 0,
"type": "table",
"value": "torrents"
},
{
"id": 5,
"type": "value",
"value": "mixtape"
},
{
"id": 2,
"type": "column",
"value": "artist"
},
{
"id": 7,
"type": "value",
"value": "dance"
},
{
"id": 11,
"type": "value",
"value": "album"
},
{
"id": 1,
"type": "table",
"value": "tags"
},
{
"id": 9,
"type": "value",
"value": "1980"
},
{
"id": 10,
"type": "value",
"value": "1985"
},
{
"id": 6,
"type": "column",
"value": "tag"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
10,647
|
books
|
bird:train.json:5930
|
List the title of the earliest published Japanese book.
|
SELECT T1.title FROM book AS T1 INNER JOIN book_language AS T2 ON T1.language_id = T2.language_id WHERE T2.language_name = 'Japanese' ORDER BY T1.publication_date ASC LIMIT 1
|
[
"List",
"the",
"title",
"of",
"the",
"earliest",
"published",
"Japanese",
"book",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "publication_date"
},
{
"id": 2,
"type": "table",
"value": "book_language"
},
{
"id": 3,
"type": "column",
"value": "language_name"
},
{
"id": 6,
"type": "column",
"value": "language_id"
},
{
"id": 4,
"type": "value",
"value": "Japanese"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"B-TABLE",
"O"
] |
14,327
|
store_1
|
spider:train_spider.json:601
|
List top 10 employee work longest in the company. List employee's first and last name.
|
SELECT first_name , last_name FROM employees ORDER BY hire_date ASC LIMIT 10;
|
[
"List",
"top",
"10",
"employee",
"work",
"longest",
"in",
"the",
"company",
".",
"List",
"employee",
"'s",
"first",
"and",
"last",
"name",
"."
] |
[
{
"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"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
14,097
|
bike_share_1
|
bird:train.json:9074
|
List out all end stations for a bicycle that were making a trip starting from 2nd at South Park station? Only retain the unique value.
|
SELECT DISTINCT end_station_name FROM trip WHERE start_station_name = '2nd at South Park'
|
[
"List",
"out",
"all",
"end",
"stations",
"for",
"a",
"bicycle",
"that",
"were",
"making",
"a",
"trip",
"starting",
"from",
"2nd",
"at",
"South",
"Park",
"station",
"?",
"Only",
"retain",
"the",
"unique",
"value",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "start_station_name"
},
{
"id": 3,
"type": "value",
"value": "2nd at South Park"
},
{
"id": 1,
"type": "column",
"value": "end_station_name"
},
{
"id": 0,
"type": "table",
"value": "trip"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": [
15,
16,
17,
18
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,834
|
customers_card_transactions
|
spider:train_spider.json:730
|
What are the different card type codes?
|
SELECT DISTINCT card_type_code FROM Customers_Cards
|
[
"What",
"are",
"the",
"different",
"card",
"type",
"codes",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "customers_cards"
},
{
"id": 1,
"type": "column",
"value": "card_type_code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
12,634
|
university_basketball
|
spider:train_spider.json:987
|
What is the highest acc percent score in the competition?
|
SELECT acc_percent FROM basketball_match ORDER BY acc_percent DESC LIMIT 1
|
[
"What",
"is",
"the",
"highest",
"acc",
"percent",
"score",
"in",
"the",
"competition",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "basketball_match"
},
{
"id": 1,
"type": "column",
"value": "acc_percent"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
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},
{
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},
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},
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
9
|
shipping
|
bird:train.json:5667
|
What model year of truck delivered the ship ID 1233?
|
SELECT T1.model_year FROM truck AS T1 INNER JOIN shipment AS T2 ON T1.truck_id = T2.truck_id WHERE T2.ship_id = '1233'
|
[
"What",
"model",
"year",
"of",
"truck",
"delivered",
"the",
"ship",
"ID",
"1233",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "model_year"
},
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 5,
"type": "column",
"value": "truck_id"
},
{
"id": 3,
"type": "column",
"value": "ship_id"
},
{
"id": 1,
"type": "table",
"value": "truck"
},
{
"id": 4,
"type": "value",
"value": "1233"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
14,494
|
movie_3
|
bird:train.json:9131
|
Among the films that the customer RUTH MARTINEZ has rented, what is the title of the one with the highest replacement cost?
|
SELECT T4.title FROM customer AS T1 INNER JOIN rental AS T2 ON T1.customer_id = T2.customer_id INNER JOIN inventory AS T3 ON T2.inventory_id = T3.inventory_id INNER JOIN film AS T4 ON T3.film_id = T4.film_id WHERE T1.first_name = 'RUTH' AND T1.last_name = 'MARTINEZ' ORDER BY T4.replacement_cost DESC LIMIT 1
|
[
"Among",
"the",
"films",
"that",
"the",
"customer",
"RUTH",
"MARTINEZ",
"has",
"rented",
",",
"what",
"is",
"the",
"title",
"of",
"the",
"one",
"with",
"the",
"highest",
"replacement",
"cost",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "replacement_cost"
},
{
"id": 11,
"type": "column",
"value": "inventory_id"
},
{
"id": 12,
"type": "column",
"value": "customer_id"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "table",
"value": "inventory"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 8,
"type": "value",
"value": "MARTINEZ"
},
{
"id": 9,
"type": "table",
"value": "customer"
},
{
"id": 4,
"type": "column",
"value": "film_id"
},
{
"id": 10,
"type": "table",
"value": "rental"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "film"
},
{
"id": 6,
"type": "value",
"value": "RUTH"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
21,
22
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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": [
7
]
},
{
"entity_id": 9,
"token_idxs": [
5
]
},
{
"entity_id": 10,
"token_idxs": [
9
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
128
|
college_2
|
spider:train_spider.json:1419
|
What are the ids of courses without prerequisites?
|
SELECT course_id FROM course EXCEPT SELECT course_id FROM prereq
|
[
"What",
"are",
"the",
"ids",
"of",
"courses",
"without",
"prerequisites",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "course_id"
},
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 1,
"type": "table",
"value": "prereq"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O"
] |
10,844
|
address
|
bird:train.json:5231
|
Calculate the percentage of congress representatives from the Democrat party. Among them, how many postal points are in the Hawaii state?
|
SELECT CAST(SUM(CASE WHEN T1.party = 'Democrat' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*), SUM(CASE WHEN T1.state = 'Hawaii' THEN 1 ELSE 0 END) FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district
|
[
"Calculate",
"the",
"percentage",
"of",
"congress",
"representatives",
"from",
"the",
"Democrat",
"party",
".",
"Among",
"them",
",",
"how",
"many",
"postal",
"points",
"are",
"in",
"the",
"Hawaii",
"state",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "cognress_rep_id"
},
{
"id": 1,
"type": "table",
"value": "zip_congress"
},
{
"id": 0,
"type": "table",
"value": "congress"
},
{
"id": 3,
"type": "column",
"value": "district"
},
{
"id": 10,
"type": "value",
"value": "Democrat"
},
{
"id": 8,
"type": "value",
"value": "Hawaii"
},
{
"id": 7,
"type": "column",
"value": "state"
},
{
"id": 9,
"type": "column",
"value": "party"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
21
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
3,164
|
bakery_1
|
bird:test.json:1570
|
Give the ids of cookes that are cheaper than any croissant.
|
SELECT id FROM goods WHERE food = "Cookie" AND price < (SELECT min(price) FROM goods WHERE food = 'Croissant')
|
[
"Give",
"the",
"ids",
"of",
"cookes",
"that",
"are",
"cheaper",
"than",
"any",
"croissant",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Croissant"
},
{
"id": 3,
"type": "column",
"value": "Cookie"
},
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 4,
"type": "column",
"value": "price"
},
{
"id": 2,
"type": "column",
"value": "food"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"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": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
11,169
|
loan_1
|
spider:train_spider.json:3009
|
What is the total number of customers across banks?
|
SELECT sum(no_of_customers) FROM bank
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"customers",
"across",
"banks",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "no_of_customers"
},
{
"id": 0,
"type": "table",
"value": "bank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
6
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN"
] |
2,426
|
music_tracker
|
bird:train.json:2055
|
Please list the releases that have been downloaded for more than 20000 times.
|
SELECT groupName FROM torrents WHERE totalSnatched > 20000
|
[
"Please",
"list",
"the",
"releases",
"that",
"have",
"been",
"downloaded",
"for",
"more",
"than",
"20000",
"times",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "totalsnatched"
},
{
"id": 1,
"type": "column",
"value": "groupname"
},
{
"id": 0,
"type": "table",
"value": "torrents"
},
{
"id": 3,
"type": "value",
"value": "20000"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
7,953
|
human_resources
|
bird:train.json:8961
|
If Jose Rodriguez tried his best, how many percentage can his salary raise without changing his position?
|
SELECT 100 * (CAST(REPLACE(SUBSTR(T2.maxsalary, 4), ',', '') AS REAL) - CAST(REPLACE(SUBSTR(T1.salary, 4), ',', '') AS REAL)) / CAST(REPLACE(SUBSTR(T1.salary, 4), ',', '') AS REAL) AS per FROM employee AS T1 INNER JOIN position AS T2 ON T1.positionID = T2.positionID WHERE T1.firstname = 'Jose' AND T1.lastname = 'Rodriguez'
|
[
"If",
"Jose",
"Rodriguez",
"tried",
"his",
"best",
",",
"how",
"many",
"percentage",
"can",
"his",
"salary",
"raise",
"without",
"changing",
"his",
"position",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "positionid"
},
{
"id": 3,
"type": "column",
"value": "firstname"
},
{
"id": 6,
"type": "value",
"value": "Rodriguez"
},
{
"id": 11,
"type": "column",
"value": "maxsalary"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "table",
"value": "position"
},
{
"id": 5,
"type": "column",
"value": "lastname"
},
{
"id": 9,
"type": "column",
"value": "salary"
},
{
"id": 4,
"type": "value",
"value": "Jose"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": ","
},
{
"id": 10,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
1
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
12
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,753
|
activity_1
|
spider:train_spider.json:6761
|
Show the ids for all the faculty members who have at least 2 students.
|
SELECT T1.FacID FROM Faculty AS T1 JOIN Student AS T2 ON T1.FacID = T2.advisor GROUP BY T1.FacID HAVING count(*) >= 2
|
[
"Show",
"the",
"ids",
"for",
"all",
"the",
"faculty",
"members",
"who",
"have",
"at",
"least",
"2",
"students",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "faculty"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 4,
"type": "column",
"value": "advisor"
},
{
"id": 0,
"type": "column",
"value": "facid"
},
{
"id": 3,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
11,612
|
works_cycles
|
bird:train.json:7279
|
How many products are out of stock?
|
SELECT COUNT(ProductID) FROM ProductVendor WHERE OnOrderQty = 0
|
[
"How",
"many",
"products",
"are",
"out",
"of",
"stock",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "productvendor"
},
{
"id": 1,
"type": "column",
"value": "onorderqty"
},
{
"id": 3,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
11,864
|
legislator
|
bird:train.json:4876
|
How many districts did John Conyers, Jr. serve in total?
|
SELECT COUNT(T3.district) FROM ( SELECT T2.district FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.official_full_name = 'John Conyers, Jr.' GROUP BY T2.district ) T3
|
[
"How",
"many",
"districts",
"did",
"John",
"Conyers",
",",
"Jr.",
"serve",
"in",
"total",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "official_full_name"
},
{
"id": 4,
"type": "value",
"value": "John Conyers, Jr."
},
{
"id": 2,
"type": "table",
"value": "current-terms"
},
{
"id": 5,
"type": "column",
"value": "bioguide_id"
},
{
"id": 0,
"type": "column",
"value": "district"
},
{
"id": 6,
"type": "column",
"value": "bioguide"
},
{
"id": 1,
"type": "table",
"value": "current"
}
] |
[
{
"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": [
4,
5,
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",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
8,666
|
dorm_1
|
spider:train_spider.json:5681
|
How many diffrent dorm amenities are there?
|
SELECT count(*) FROM dorm_amenity
|
[
"How",
"many",
"diffrent",
"dorm",
"amenities",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "dorm_amenity"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
7,373
|
bike_share_1
|
bird:train.json:9034
|
List the days in 2013 when rain and fog occurred together and find the id of bikes borrowed on these days.
|
SELECT T2.date, T1.bike_id FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE SUBSTR(CAST(T2.date AS TEXT), -4) = '2013' AND T2.events = 'Fog-Rain'
|
[
"List",
"the",
"days",
"in",
"2013",
"when",
"rain",
"and",
"fog",
"occurred",
"together",
"and",
"find",
"the",
"i",
"d",
"of",
"bikes",
"borrowed",
"on",
"these",
"days",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "zip_code"
},
{
"id": 7,
"type": "value",
"value": "Fog-Rain"
},
{
"id": 1,
"type": "column",
"value": "bike_id"
},
{
"id": 3,
"type": "table",
"value": "weather"
},
{
"id": 6,
"type": "column",
"value": "events"
},
{
"id": 0,
"type": "column",
"value": "date"
},
{
"id": 2,
"type": "table",
"value": "trip"
},
{
"id": 5,
"type": "value",
"value": "2013"
},
{
"id": 8,
"type": "value",
"value": "-4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14,
15,
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
1,988
|
car_retails
|
bird:train.json:1583
|
How many customers who are in Norway and have credit line under 220000?
|
SELECT COUNT(creditLimit) FROM customers WHERE creditLimit < 220000 AND country = 'Norway'
|
[
"How",
"many",
"customers",
"who",
"are",
"in",
"Norway",
"and",
"have",
"credit",
"line",
"under",
"220000",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "creditlimit"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "value",
"value": "220000"
},
{
"id": 4,
"type": "value",
"value": "Norway"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
4,499
|
retails
|
bird:train.json:6877
|
Please list the names of all the suppliers for parts under Brand#55.
|
SELECT T3.s_name FROM part AS T1 INNER JOIN partsupp AS T2 ON T1.p_partkey = T2.ps_partkey INNER JOIN supplier AS T3 ON T2.ps_suppkey = T3.s_suppkey WHERE T1.p_brand = 'Brand#55'
|
[
"Please",
"list",
"the",
"names",
"of",
"all",
"the",
"suppliers",
"for",
"parts",
"under",
"Brand#55",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 9,
"type": "column",
"value": "ps_partkey"
},
{
"id": 7,
"type": "column",
"value": "s_suppkey"
},
{
"id": 8,
"type": "column",
"value": "p_partkey"
},
{
"id": 1,
"type": "table",
"value": "supplier"
},
{
"id": 3,
"type": "value",
"value": "Brand#55"
},
{
"id": 5,
"type": "table",
"value": "partsupp"
},
{
"id": 2,
"type": "column",
"value": "p_brand"
},
{
"id": 0,
"type": "column",
"value": "s_name"
},
{
"id": 4,
"type": "table",
"value": "part"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"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",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
5,559
|
browser_web
|
spider:train_spider.json:1839
|
List the names of the browser that are compatible with both 'CACHEbox' and 'Fasterfox'.
|
SELECT T3.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T1.name = 'CACHEbox' INTERSECT SELECT T3.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T1.name = 'Fasterfox'
|
[
"List",
"the",
"names",
"of",
"the",
"browser",
"that",
"are",
"compatible",
"with",
"both",
"'",
"CACHEbox",
"'",
"and",
"'",
"Fasterfox",
"'",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "accelerator_compatible_browser"
},
{
"id": 4,
"type": "table",
"value": "web_client_accelerator"
},
{
"id": 8,
"type": "column",
"value": "accelerator_id"
},
{
"id": 6,
"type": "column",
"value": "browser_id"
},
{
"id": 3,
"type": "value",
"value": "Fasterfox"
},
{
"id": 2,
"type": "value",
"value": "CACHEbox"
},
{
"id": 1,
"type": "table",
"value": "browser"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
14,101
|
olympics
|
bird:train.json:5078
|
Provide the age of the tallest competitor.
|
SELECT T2.age FROM person AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.person_id ORDER BY T1.height DESC LIMIT 1
|
[
"Provide",
"the",
"age",
"of",
"the",
"tallest",
"competitor",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "games_competitor"
},
{
"id": 5,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "column",
"value": "height"
},
{
"id": 0,
"type": "column",
"value": "age"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
5,085
|
vehicle_rent
|
bird:test.json:434
|
Return the name of the discount that corresponds to the most rental history records.
|
SELECT T2.name FROM renting_history AS T1 JOIN discount AS T2 ON T1.discount_id = T2.id GROUP BY T2.id ORDER BY count(*) DESC LIMIT 1
|
[
"Return",
"the",
"name",
"of",
"the",
"discount",
"that",
"corresponds",
"to",
"the",
"most",
"rental",
"history",
"records",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "renting_history"
},
{
"id": 4,
"type": "column",
"value": "discount_id"
},
{
"id": 3,
"type": "table",
"value": "discount"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
11,
12
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
7,668
|
allergy_1
|
spider:train_spider.json:530
|
How many male students (sex is 'M') are allergic to any type of food?
|
SELECT count(*) FROM Student WHERE sex = "M" AND StuID IN (SELECT StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food")
|
[
"How",
"many",
"male",
"students",
"(",
"sex",
"is",
"'",
"M",
"'",
")",
"are",
"allergic",
"to",
"any",
"type",
"of",
"food",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "allergy_type"
},
{
"id": 4,
"type": "table",
"value": "has_allergy"
},
{
"id": 6,
"type": "column",
"value": "allergytype"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 8,
"type": "column",
"value": "allergy"
},
{
"id": 3,
"type": "column",
"value": "stuid"
},
{
"id": 7,
"type": "column",
"value": "food"
},
{
"id": 1,
"type": "column",
"value": "sex"
},
{
"id": 2,
"type": "column",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
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17
]
},
{
"entity_id": 8,
"token_idxs": [
12
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
15,943
|
retails
|
bird:train.json:6776
|
What is the average discount for the parts made by Manufacturer#5?
|
SELECT AVG(T3.l_discount) FROM part AS T1 INNER JOIN partsupp AS T2 ON T1.p_partkey = T2.ps_partkey INNER JOIN lineitem AS T3 ON T2.ps_suppkey = T3.l_suppkey WHERE T1.p_mfgr = 'Manufacturer#5'
|
[
"What",
"is",
"the",
"average",
"discount",
"for",
"the",
"parts",
"made",
"by",
"Manufacturer#5",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "Manufacturer#5"
},
{
"id": 3,
"type": "column",
"value": "l_discount"
},
{
"id": 6,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 9,
"type": "column",
"value": "ps_partkey"
},
{
"id": 7,
"type": "column",
"value": "l_suppkey"
},
{
"id": 8,
"type": "column",
"value": "p_partkey"
},
{
"id": 0,
"type": "table",
"value": "lineitem"
},
{
"id": 5,
"type": "table",
"value": "partsupp"
},
{
"id": 1,
"type": "column",
"value": "p_mfgr"
},
{
"id": 4,
"type": "table",
"value": "part"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
1,612
|
chicago_crime
|
bird:train.json:8694
|
List all the crimes of the narcotic type that exist.
|
SELECT secondary_description FROM IUCR WHERE primary_description = 'NARCOTICS' GROUP BY secondary_description
|
[
"List",
"all",
"the",
"crimes",
"of",
"the",
"narcotic",
"type",
"that",
"exist",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "secondary_description"
},
{
"id": 2,
"type": "column",
"value": "primary_description"
},
{
"id": 3,
"type": "value",
"value": "NARCOTICS"
},
{
"id": 0,
"type": "table",
"value": "iucr"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
12,590
|
baseball_1
|
spider:train_spider.json:3676
|
Find the number of tied games (the value of "ties" is '1') in 1885 postseason.
|
SELECT count(*) FROM postseason WHERE YEAR = 1885 AND ties = 1;
|
[
"Find",
"the",
"number",
"of",
"tied",
"games",
"(",
"the",
"value",
"of",
"\"",
"ties",
"\"",
"is",
"'",
"1",
"'",
")",
"in",
"1885",
"postseason",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "postseason"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "1885"
},
{
"id": 3,
"type": "column",
"value": "ties"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
7,633
|
works_cycles
|
bird:train.json:7111
|
How many vendors are having their products ordered with an average delivery time of 25 days?
|
SELECT COUNT(DISTINCT BusinessEntityID) FROM ProductVendor WHERE AverageLeadTime = 25
|
[
"How",
"many",
"vendors",
"are",
"having",
"their",
"products",
"ordered",
"with",
"an",
"average",
"delivery",
"time",
"of",
"25",
"days",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "businessentityid"
},
{
"id": 1,
"type": "column",
"value": "averageleadtime"
},
{
"id": 0,
"type": "table",
"value": "productvendor"
},
{
"id": 2,
"type": "value",
"value": "25"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
96
|
world_development_indicators
|
bird:train.json:2216
|
What are the full names of the countries in South Asia that belongs to the low income group?
|
SELECT LongName FROM Country WHERE IncomeGroup = 'Low income' AND Region = 'South Asia'
|
[
"What",
"are",
"the",
"full",
"names",
"of",
"the",
"countries",
"in",
"South",
"Asia",
"that",
"belongs",
"to",
"the",
"low",
"income",
"group",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "incomegroup"
},
{
"id": 3,
"type": "value",
"value": "Low income"
},
{
"id": 5,
"type": "value",
"value": "South Asia"
},
{
"id": 1,
"type": "column",
"value": "longname"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "region"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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17
]
},
{
"entity_id": 3,
"token_idxs": [
15,
16
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9,
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
475
|
works_cycles
|
bird:train.json:7181
|
What is the stocked quantity of products manufactured from location ID 40?
|
SELECT COUNT(*) FROM WorkOrderRouting AS T1 INNER JOIN BillOfMaterials AS T2 ON T1.LocationID = T2.ProductAssemblyID INNER JOIN WorkOrder AS T3 ON T3.WorkOrderID = T1.WorkOrderID WHERE T1.LocationID = 40
|
[
"What",
"is",
"the",
"stocked",
"quantity",
"of",
"products",
"manufactured",
"from",
"location",
"ID",
"40",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "productassemblyid"
},
{
"id": 3,
"type": "table",
"value": "workorderrouting"
},
{
"id": 4,
"type": "table",
"value": "billofmaterials"
},
{
"id": 5,
"type": "column",
"value": "workorderid"
},
{
"id": 1,
"type": "column",
"value": "locationid"
},
{
"id": 0,
"type": "table",
"value": "workorder"
},
{
"id": 2,
"type": "value",
"value": "40"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
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11
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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{
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},
{
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{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
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},
{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
15,327
|
institution_sports
|
bird:test.json:1646
|
What are the names of institutions, ordered by the years in which they were founded?
|
SELECT Name FROM institution ORDER BY Founded ASC
|
[
"What",
"are",
"the",
"names",
"of",
"institutions",
",",
"ordered",
"by",
"the",
"years",
"in",
"which",
"they",
"were",
"founded",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "institution"
},
{
"id": 2,
"type": "column",
"value": "founded"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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{
"entity_id": 8,
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{
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},
{
"entity_id": 13,
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,746
|
works_cycles
|
bird:train.json:7314
|
List all staff in the Shipping and Receiving department who are hired in 2009.
|
SELECT T1.FirstName, T1.LastName FROM Person AS T1 INNER JOIN Employee AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN EmployeeDepartmentHistory AS T3 ON T2.BusinessEntityID = T3.BusinessEntityID INNER JOIN Department AS T4 ON T3.DepartmentID = T4.DepartmentID WHERE STRFTIME('%Y', T2.HireDate) = '2009' AND T4.Name = 'Shipping and Receiving'
|
[
"List",
"all",
"staff",
"in",
"the",
"Shipping",
"and",
"Receiving",
"department",
"who",
"are",
"hired",
"in",
"2009",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "employeedepartmenthistory"
},
{
"id": 7,
"type": "value",
"value": "Shipping and Receiving"
},
{
"id": 10,
"type": "column",
"value": "businessentityid"
},
{
"id": 4,
"type": "column",
"value": "departmentid"
},
{
"id": 2,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 9,
"type": "table",
"value": "employee"
},
{
"id": 12,
"type": "column",
"value": "hiredate"
},
{
"id": 8,
"type": "table",
"value": "person"
},
{
"id": 5,
"type": "value",
"value": "2009"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 11,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5,
6,
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": [
11
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
7,886
|
flight_company
|
spider:train_spider.json:6374
|
What are the ids and names of the companies that operated more than one flight?
|
SELECT T1.id , T1.name FROM operate_company AS T1 JOIN flight AS t2 ON T1.id = T2.company_id GROUP BY T1.id HAVING count(*) > 1
|
[
"What",
"are",
"the",
"ids",
"and",
"names",
"of",
"the",
"companies",
"that",
"operated",
"more",
"than",
"one",
"flight",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "operate_company"
},
{
"id": 5,
"type": "column",
"value": "company_id"
},
{
"id": 3,
"type": "table",
"value": "flight"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
10,770
|
talkingdata
|
bird:train.json:1243
|
Which brand is most common among people in their twenties?
|
SELECT T.phone_brand FROM ( SELECT T2.phone_brand, COUNT(T2.phone_brand) AS num FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.age BETWEEN 20 AND 30 GROUP BY T2.phone_brand ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"Which",
"brand",
"is",
"most",
"common",
"among",
"people",
"in",
"their",
"twenties",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 0,
"type": "column",
"value": "phone_brand"
},
{
"id": 2,
"type": "table",
"value": "gender_age"
},
{
"id": 7,
"type": "column",
"value": "device_id"
},
{
"id": 1,
"type": "column",
"value": "num"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "value",
"value": "20"
},
{
"id": 6,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
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3
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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},
{
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},
{
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},
{
"entity_id": 11,
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},
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
2,724
|
thrombosis_prediction
|
bird:dev.json:1243
|
For all patients who are older than 55 years old, what is the percentage of female who has abnormal prothrombin time (PT)?
|
SELECT CAST(SUM(CASE WHEN T2.PT >= 14 AND T1.SEX = 'F' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE STRFTIME('%Y', CURRENT_TIMESTAMP) - STRFTIME('%Y', T1.Birthday) > 55
|
[
"For",
"all",
"patients",
"who",
"are",
"older",
"than",
"55",
"years",
"old",
",",
"what",
"is",
"the",
"percentage",
"of",
"female",
"who",
"has",
"abnormal",
"prothrombin",
"time",
"(",
"PT",
")",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 6,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 11,
"type": "column",
"value": "sex"
},
{
"id": 2,
"type": "value",
"value": "55"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "%Y"
},
{
"id": 9,
"type": "column",
"value": "pt"
},
{
"id": 10,
"type": "value",
"value": "14"
},
{
"id": 7,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "1"
},
{
"id": 12,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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7
]
},
{
"entity_id": 3,
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},
{
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},
{
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8
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},
{
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},
{
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},
{
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},
{
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22,
23,
24
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},
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
16
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
11,597
|
chinook_1
|
spider:train_spider.json:853
|
How many distinct cities does the employees live in?
|
SELECT COUNT(DISTINCT city) FROM EMPLOYEE
|
[
"How",
"many",
"distinct",
"cities",
"does",
"the",
"employees",
"live",
"in",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
4,279
|
movie_3
|
bird:train.json:9214
|
Mention the language of Untouchables Sunrise film and calculate its rental cost per day.
|
SELECT T2.name, T1.replacement_cost / T1.rental_duration AS cost FROM film AS T1 INNER JOIN language AS T2 ON T1.language_id = T2.language_id WHERE T1.title = 'UNTOUCHABLES SUNRISE'
|
[
"Mention",
"the",
"language",
"of",
"Untouchables",
"Sunrise",
"film",
"and",
"calculate",
"its",
"rental",
"cost",
"per",
"day",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "UNTOUCHABLES SUNRISE"
},
{
"id": 5,
"type": "column",
"value": "replacement_cost"
},
{
"id": 6,
"type": "column",
"value": "rental_duration"
},
{
"id": 7,
"type": "column",
"value": "language_id"
},
{
"id": 2,
"type": "table",
"value": "language"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "film"
}
] |
[
{
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"token_idxs": []
},
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"entity_id": 1,
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6
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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4,
5
]
},
{
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11
]
},
{
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10
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},
{
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"token_idxs": []
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O"
] |
12,257
|
donor
|
bird:train.json:3262
|
Which resource type is commonly bought by the Los Angeles Unified School District?
|
SELECT T1.project_resource_type FROM resources AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T2.school_district = 'Los Angeles Unif Sch Dist' GROUP BY T2.school_district ORDER BY COUNT(T1.project_resource_type) DESC LIMIT 1
|
[
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"type",
"is",
"commonly",
"bought",
"by",
"the",
"Los",
"Angeles",
"Unified",
"School",
"District",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Los Angeles Unif Sch Dist"
},
{
"id": 1,
"type": "column",
"value": "project_resource_type"
},
{
"id": 0,
"type": "column",
"value": "school_district"
},
{
"id": 2,
"type": "table",
"value": "resources"
},
{
"id": 5,
"type": "column",
"value": "projectid"
},
{
"id": 3,
"type": "table",
"value": "projects"
}
] |
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
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"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
5,763
|
bakery_1
|
bird:test.json:1490
|
What is the id and flavor of the cheapest cookie?
|
SELECT id , flavor FROM goods WHERE food = "Cookie" ORDER BY price LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"and",
"flavor",
"of",
"the",
"cheapest",
"cookie",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "flavor"
},
{
"id": 4,
"type": "column",
"value": "Cookie"
},
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 5,
"type": "column",
"value": "price"
},
{
"id": 3,
"type": "column",
"value": "food"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
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1
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3,
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},
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,343
|
thrombosis_prediction
|
bird:dev.json:1283
|
For the patients with the normal glutamic pylvic transaminase level, how many of them are male?
|
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.GOT < 60 AND T1.SEX = 'M'
|
[
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"glutamic",
"pylvic",
"transaminase",
"level",
",",
"how",
"many",
"of",
"them",
"are",
"male",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "got"
},
{
"id": 5,
"type": "column",
"value": "sex"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "60"
},
{
"id": 6,
"type": "value",
"value": "M"
}
] |
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4,
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},
{
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},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
10,868
|
college_1
|
spider:train_spider.json:3284
|
What are the course codes for every class that the student with the last name Smithson took?
|
SELECT T1.crs_code FROM CLASS AS T1 JOIN enroll AS T2 ON T1.class_code = T2.class_code JOIN student AS T3 ON T3.stu_num = T2.stu_num WHERE T3.stu_lname = 'Smithson'
|
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"student",
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"name",
"Smithson",
"took",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "class_code"
},
{
"id": 2,
"type": "column",
"value": "stu_lname"
},
{
"id": 0,
"type": "column",
"value": "crs_code"
},
{
"id": 3,
"type": "value",
"value": "Smithson"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 6,
"type": "column",
"value": "stu_num"
},
{
"id": 5,
"type": "table",
"value": "enroll"
},
{
"id": 4,
"type": "table",
"value": "class"
}
] |
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4
]
},
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7
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},
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{
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},
{
"entity_id": 15,
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},
{
"entity_id": 16,
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},
{
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},
{
"entity_id": 18,
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O"
] |
10,975
|
driving_school
|
spider:train_spider.json:6667
|
What is the date of birth of every customer whose status code is 'Good Customer'?
|
SELECT date_of_birth FROM Customers WHERE customer_status_code = 'Good Customer'
|
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"is",
"the",
"date",
"of",
"birth",
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"every",
"customer",
"whose",
"status",
"code",
"is",
"'",
"Good",
"Customer",
"'",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "customer_status_code"
},
{
"id": 1,
"type": "column",
"value": "date_of_birth"
},
{
"id": 3,
"type": "value",
"value": "Good Customer"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
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15
]
},
{
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8,
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},
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{
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{
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},
{
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{
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{
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},
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O"
] |
9,224
|
airline
|
bird:train.json:5839
|
Give the number of planes that took off from Los Angeles International airport on 2018/8/27.
|
SELECT SUM(CASE WHEN T2.FL_DATE = '2018/8/27' THEN 1 ELSE 0 END) AS count FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.ORIGIN WHERE T1.Description = 'Los Angeles, CA: Los Angeles International'
|
[
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"number",
"of",
"planes",
"that",
"took",
"off",
"from",
"Los",
"Angeles",
"International",
"airport",
"on",
"2018/8/27",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Los Angeles, CA: Los Angeles International"
},
{
"id": 2,
"type": "column",
"value": "description"
},
{
"id": 9,
"type": "value",
"value": "2018/8/27"
},
{
"id": 0,
"type": "table",
"value": "airports"
},
{
"id": 1,
"type": "table",
"value": "airlines"
},
{
"id": 8,
"type": "column",
"value": "fl_date"
},
{
"id": 5,
"type": "column",
"value": "origin"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
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{
"entity_id": 16,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
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"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
11,145
|
apartment_rentals
|
spider:train_spider.json:1249
|
How many bookings does each booking status have? List the booking status code and the number of corresponding bookings.
|
SELECT booking_status_code , COUNT(*) FROM Apartment_Bookings GROUP BY booking_status_code
|
[
"How",
"many",
"bookings",
"does",
"each",
"booking",
"status",
"have",
"?",
"List",
"the",
"booking",
"status",
"code",
"and",
"the",
"number",
"of",
"corresponding",
"bookings",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "booking_status_code"
},
{
"id": 0,
"type": "table",
"value": "apartment_bookings"
}
] |
[
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},
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},
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"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
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},
{
"entity_id": 16,
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},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,385
|
college_1
|
spider:train_spider.json:3325
|
What is the last name of the student who got a grade A in the class with code 10018.
|
SELECT T1.stu_lname FROM student AS T1 JOIN enroll AS T2 ON T1.stu_num = T2.stu_num WHERE T2.enroll_grade = 'A' AND T2.class_code = 10018
|
[
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"last",
"name",
"of",
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"student",
"who",
"got",
"a",
"grade",
"A",
"in",
"the",
"class",
"with",
"code",
"10018",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "enroll_grade"
},
{
"id": 6,
"type": "column",
"value": "class_code"
},
{
"id": 0,
"type": "column",
"value": "stu_lname"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 3,
"type": "column",
"value": "stu_num"
},
{
"id": 2,
"type": "table",
"value": "enroll"
},
{
"id": 7,
"type": "value",
"value": "10018"
},
{
"id": 5,
"type": "value",
"value": "A"
}
] |
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{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
15,
17
]
},
{
"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-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
9,932
|
public_review_platform
|
bird:train.json:3775
|
What percentage more for the "Women's Clothing" Yelp businesses to "Men's Clothing"?
|
SELECT CAST(SUM(CASE WHEN T2.category_name LIKE 'Women''s Clothing' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) - CAST(SUM(CASE WHEN T2.category_name LIKE 'Men''s Clothing' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) AS "more percentage" FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id
|
[
"What",
"percentage",
"more",
"for",
"the",
"\"",
"Women",
"'s",
"Clothing",
"\"",
"Yelp",
"businesses",
"to",
"\"",
"Men",
"'s",
"Clothing",
"\"",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "business_categories"
},
{
"id": 8,
"type": "value",
"value": "Women's Clothing"
},
{
"id": 9,
"type": "value",
"value": "Men's Clothing"
},
{
"id": 7,
"type": "column",
"value": "category_name"
},
{
"id": 2,
"type": "column",
"value": "category_id"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "categories"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"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": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 9,
"token_idxs": [
14,
15,
16
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
6,888
|
student_loan
|
bird:train.json:4480
|
How many students enlisted in the navy?
|
SELECT COUNT(name) FROM enlist WHERE organ = 'navy'
|
[
"How",
"many",
"students",
"enlisted",
"in",
"the",
"navy",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "enlist"
},
{
"id": 1,
"type": "column",
"value": "organ"
},
{
"id": 2,
"type": "value",
"value": "navy"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"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",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
14,809
|
sales
|
bird:train.json:5429
|
Give the product's name brought by Aaron Alexander.
|
SELECT DISTINCT T1.Name FROM Products AS T1 INNER JOIN Sales AS T2 ON T1.ProductID = T2.ProductID INNER JOIN Customers AS T3 ON T2.CustomerID = T3.CustomerID WHERE T3.FirstName = 'Aaron' AND T3.LastName = 'Alexander'
|
[
"Give",
"the",
"product",
"'s",
"name",
"brought",
"by",
"Aaron",
"Alexander",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "column",
"value": "firstname"
},
{
"id": 8,
"type": "value",
"value": "Alexander"
},
{
"id": 9,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "table",
"value": "sales"
},
{
"id": 6,
"type": "value",
"value": "Aaron"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-VALUE",
"O"
] |
12,205
|
college_2
|
spider:train_spider.json:1418
|
Find the id of the courses that do not have any prerequisite?
|
SELECT course_id FROM course EXCEPT SELECT course_id FROM prereq
|
[
"Find",
"the",
"i",
"d",
"of",
"the",
"courses",
"that",
"do",
"not",
"have",
"any",
"prerequisite",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "course_id"
},
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 1,
"type": "table",
"value": "prereq"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
2,
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,167
|
customers_and_orders
|
bird:test.json:287
|
What is the product type with least number of products?
|
SELECT product_type_code FROM Products GROUP BY product_type_code ORDER BY count(*) ASC LIMIT 1
|
[
"What",
"is",
"the",
"product",
"type",
"with",
"least",
"number",
"of",
"products",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "product_type_code"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
3,872
|
address_1
|
bird:test.json:798
|
Give the state that has the most students.
|
SELECT T1.state FROM City AS T1 JOIN Student AS T2 ON T1.city_code = T2.city_code GROUP BY T1.state ORDER BY count(*) DESC LIMIT 1
|
[
"Give",
"the",
"state",
"that",
"has",
"the",
"most",
"students",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "city_code"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
7,564
|
world_development_indicators
|
bird:train.json:2165
|
Which high income group countries are from Asia?
|
SELECT CountryCode, Region FROM Country WHERE (IncomeGroup = 'High income: OECD' OR IncomeGroup = 'High income: nonOECD') AND Region LIKE '%Asia%'
|
[
"Which",
"high",
"income",
"group",
"countries",
"are",
"from",
"Asia",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "High income: nonOECD"
},
{
"id": 5,
"type": "value",
"value": "High income: OECD"
},
{
"id": 1,
"type": "column",
"value": "countrycode"
},
{
"id": 4,
"type": "column",
"value": "incomegroup"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "region"
},
{
"id": 3,
"type": "value",
"value": "%Asia%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
2,
3
]
},
{
"entity_id": 5,
"token_idxs": [
1
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
5,663
|
formula_1
|
spider:train_spider.json:2224
|
For each race name, What is the maximum fastest lap speed for races after 2004 ordered by year?
|
SELECT max(T2.fastestlapspeed) , T1.name , T1.year FROM races AS T1 JOIN results AS T2 ON T1.raceid = T2.raceid WHERE T1.year > 2014 GROUP BY T1.name ORDER BY T1.year
|
[
"For",
"each",
"race",
"name",
",",
"What",
"is",
"the",
"maximum",
"fastest",
"lap",
"speed",
"for",
"races",
"after",
"2004",
"ordered",
"by",
"year",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "fastestlapspeed"
},
{
"id": 3,
"type": "table",
"value": "results"
},
{
"id": 6,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "2014"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
18
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
14,117
|
medicine_enzyme_interaction
|
spider:train_spider.json:954
|
What is the id and name of the enzyme that can interact with the most medicines as an activator?
|
SELECT T1.id , T1.name FROM enzyme AS T1 JOIN medicine_enzyme_interaction AS T2 ON T1.id = T2.enzyme_id WHERE T2.interaction_type = 'activitor' GROUP BY T1.id ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"and",
"name",
"of",
"the",
"enzyme",
"that",
"can",
"interact",
"with",
"the",
"most",
"medicines",
"as",
"an",
"activator",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "medicine_enzyme_interaction"
},
{
"id": 4,
"type": "column",
"value": "interaction_type"
},
{
"id": 5,
"type": "value",
"value": "activitor"
},
{
"id": 6,
"type": "column",
"value": "enzyme_id"
},
{
"id": 2,
"type": "table",
"value": "enzyme"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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6
]
},
{
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9
]
},
{
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16
]
},
{
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12
]
},
{
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19
]
},
{
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},
{
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},
{
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},
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},
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},
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
90
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4234
|
What are the names of the employees who authorised the destruction and the employees who destroyed the corresponding documents?
|
SELECT T2.employee_name , T3.employee_name FROM Documents_to_be_destroyed AS T1 JOIN Employees AS T2 ON T1.Destruction_Authorised_by_Employee_ID = T2.employee_id JOIN Employees AS T3 ON T1.Destroyed_by_Employee_ID = T3.employee_id;
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"employees",
"who",
"authorised",
"the",
"destruction",
"and",
"the",
"employees",
"who",
"destroyed",
"the",
"corresponding",
"documents",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "destruction_authorised_by_employee_id"
},
{
"id": 2,
"type": "table",
"value": "documents_to_be_destroyed"
},
{
"id": 3,
"type": "column",
"value": "destroyed_by_employee_id"
},
{
"id": 0,
"type": "column",
"value": "employee_name"
},
{
"id": 4,
"type": "column",
"value": "employee_id"
},
{
"id": 1,
"type": "table",
"value": "employees"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
960
|
superhero
|
bird:dev.json:812
|
List down at least five full names of superheroes with blue eyes.
|
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN colour AS T2 ON T1.eye_colour_id = T2.id WHERE T2.colour = 'Blue' LIMIT 5
|
[
"List",
"down",
"at",
"least",
"five",
"full",
"names",
"of",
"superheroes",
"with",
"blue",
"eyes",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "superhero_name"
},
{
"id": 5,
"type": "column",
"value": "eye_colour_id"
},
{
"id": 1,
"type": "table",
"value": "superhero"
},
{
"id": 2,
"type": "table",
"value": "colour"
},
{
"id": 3,
"type": "column",
"value": "colour"
},
{
"id": 4,
"type": "value",
"value": "Blue"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
6,227
|
student_club
|
bird:dev.json:1384
|
How many income generated by Grant Gilmour?
|
SELECT T2.amount FROM member AS T1 INNER JOIN income AS T2 ON T1.member_id = T2.link_to_member WHERE T1.first_name = 'Grant' AND T1.last_name = 'Gilmour'
|
[
"How",
"many",
"income",
"generated",
"by",
"Grant",
"Gilmour",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "link_to_member"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "column",
"value": "member_id"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 8,
"type": "value",
"value": "Gilmour"
},
{
"id": 0,
"type": "column",
"value": "amount"
},
{
"id": 1,
"type": "table",
"value": "member"
},
{
"id": 2,
"type": "table",
"value": "income"
},
{
"id": 6,
"type": "value",
"value": "Grant"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
6
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
9,432
|
chinook_1
|
spider:train_spider.json:857
|
Find all the customer last names that do not have invoice totals larger than 20.
|
SELECT LastName FROM CUSTOMER EXCEPT SELECT T1.LastName FROM CUSTOMER AS T1 JOIN Invoice AS T2 ON T1.CustomerId = T2.CustomerId WHERE T2.total > 20
|
[
"Find",
"all",
"the",
"customer",
"last",
"names",
"that",
"do",
"not",
"have",
"invoice",
"totals",
"larger",
"than",
"20",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 2,
"type": "table",
"value": "invoice"
},
{
"id": 3,
"type": "column",
"value": "total"
},
{
"id": 4,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
10,177
|
boat_1
|
bird:test.json:904
|
What is the name, rating, and age for every sailor? And order them by rating and age.
|
SELECT name , rating , age FROM Sailors ORDER BY rating , age
|
[
"What",
"is",
"the",
"name",
",",
"rating",
",",
"and",
"age",
"for",
"every",
"sailor",
"?",
"And",
"order",
"them",
"by",
"rating",
"and",
"age",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "sailors"
},
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2,
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
6,615
|
simpson_episodes
|
bird:train.json:4323
|
Which title is the winner of Best International TV Series in 2017?
|
SELECT T2.title FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id WHERE T1.award = 'Best International TV Series' AND SUBSTR(T1.year, 1, 4) = '2017';
|
[
"Which",
"title",
"is",
"the",
"winner",
"of",
"Best",
"International",
"TV",
"Series",
"in",
"2017",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Best International TV Series"
},
{
"id": 3,
"type": "column",
"value": "episode_id"
},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "award"
},
{
"id": 4,
"type": "column",
"value": "award"
},
{
"id": 6,
"type": "value",
"value": "2017"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,218
|
works_cycles
|
bird:train.json:7295
|
Please list the website purchasing links of the vendors from whom the product Hex Nut 5 can be purchased.
|
SELECT T3.PurchasingWebServiceURL FROM ProductVendor AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID INNER JOIN Vendor AS T3 ON T1.BusinessEntityID = T3.BusinessEntityID WHERE T2.Name = 'Hex Nut 5'
|
[
"Please",
"list",
"the",
"website",
"purchasing",
"links",
"of",
"the",
"vendors",
"from",
"whom",
"the",
"product",
"Hex",
"Nut",
"5",
"can",
"be",
"purchased",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "purchasingwebserviceurl"
},
{
"id": 6,
"type": "column",
"value": "businessentityid"
},
{
"id": 4,
"type": "table",
"value": "productvendor"
},
{
"id": 3,
"type": "value",
"value": "Hex Nut 5"
},
{
"id": 7,
"type": "column",
"value": "productid"
},
{
"id": 5,
"type": "table",
"value": "product"
},
{
"id": 1,
"type": "table",
"value": "vendor"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
13,443
|
tracking_orders
|
spider:train_spider.json:6942
|
What are the names of the customers who bought product "food" at least once?
|
SELECT T1.customer_name FROM customers AS T1 JOIN orders AS T2 JOIN order_items AS T3 JOIN products AS T4 ON T1.customer_id = T2.customer_id AND T2.order_id = T3.order_id AND T3.product_id = T4.product_id WHERE T4.product_name = "food" GROUP BY T1.customer_id HAVING count(*) >= 1
|
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"who",
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"product",
"\"",
"food",
"\"",
"at",
"least",
"once",
"?"
] |
[] |
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"entity_id": 14,
"token_idxs": []
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"entity_id": 15,
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"entity_id": 16,
"token_idxs": []
},
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"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
7,752
|
ice_hockey_draft
|
bird:train.json:6952
|
How many players who were drafted by the Toronto Maple Leafs have played over 300 games in their first 7 years of the NHL career?
|
SELECT COUNT(ELITEID) FROM PlayerInfo WHERE overallby = 'Toronto Maple Leafs' AND sum_7yr_GP > 300
|
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"who",
"were",
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"in",
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"?"
] |
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{
"id": 3,
"type": "value",
"value": "Toronto Maple Leafs"
},
{
"id": 0,
"type": "table",
"value": "playerinfo"
},
{
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"type": "column",
"value": "sum_7yr_gp"
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{
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"type": "column",
"value": "overallby"
},
{
"id": 1,
"type": "column",
"value": "eliteid"
},
{
"id": 5,
"type": "value",
"value": "300"
}
] |
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"O",
"O",
"B-VALUE",
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"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
8,346
|
machine_repair
|
spider:train_spider.json:2241
|
Show the name of technicians aged either 36 or 37
|
SELECT Name FROM technician WHERE Age = 36 OR Age = 37
|
[
"Show",
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"name",
"of",
"technicians",
"aged",
"either",
"36",
"or",
"37"
] |
[
{
"id": 0,
"type": "table",
"value": "technician"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "36"
},
{
"id": 4,
"type": "value",
"value": "37"
}
] |
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"entity_id": 0,
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4
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"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE"
] |
916
|
tracking_software_problems
|
spider:train_spider.json:5356
|
Find all the ids and dates of the logs for the problem whose id is 10.
|
SELECT problem_log_id , log_entry_date FROM problem_log WHERE problem_id = 10
|
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"Find",
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"and",
"dates",
"of",
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"logs",
"for",
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"problem",
"whose",
"i",
"d",
"is",
"10",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "problem_log_id"
},
{
"id": 2,
"type": "column",
"value": "log_entry_date"
},
{
"id": 0,
"type": "table",
"value": "problem_log"
},
{
"id": 3,
"type": "column",
"value": "problem_id"
},
{
"id": 4,
"type": "value",
"value": "10"
}
] |
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{
"entity_id": 0,
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]
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3
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5
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14
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,608
|
superstore
|
bird:train.json:2357
|
What was the original price of Xerox 1952 ordered by Aimee Bixby on 2014/9/10?
|
SELECT DISTINCT T2.Sales / (1 - T2.Discount) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T2.`Product ID` WHERE T1.`Customer Name` = 'Aimee Bixby' AND T3.`Product Name` = 'Xerox 1952' AND T2.`Order Date` = '2014-09-10'
|
[
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"Xerox",
"1952",
"ordered",
"by",
"Aimee",
"Bixby",
"on",
"2014/9/10",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "central_superstore"
},
{
"id": 5,
"type": "column",
"value": "Customer Name"
},
{
"id": 7,
"type": "column",
"value": "Product Name"
},
{
"id": 6,
"type": "value",
"value": "Aimee Bixby"
},
{
"id": 13,
"type": "column",
"value": "Customer ID"
},
{
"id": 4,
"type": "column",
"value": "Product ID"
},
{
"id": 8,
"type": "value",
"value": "Xerox 1952"
},
{
"id": 9,
"type": "column",
"value": "Order Date"
},
{
"id": 10,
"type": "value",
"value": "2014-09-10"
},
{
"id": 12,
"type": "column",
"value": "discount"
},
{
"id": 0,
"type": "table",
"value": "product"
},
{
"id": 2,
"type": "table",
"value": "people"
},
{
"id": 1,
"type": "column",
"value": "sales"
},
{
"id": 11,
"type": "value",
"value": "1"
}
] |
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
12,272
|
hr_1
|
spider:train_spider.json:3447
|
display the employee ID for each employee and the date on which he ended his previous job.
|
SELECT employee_id , MAX(end_date) FROM job_history GROUP BY employee_id
|
[
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"he",
"ended",
"his",
"previous",
"job",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "job_history"
},
{
"id": 1,
"type": "column",
"value": "employee_id"
},
{
"id": 2,
"type": "column",
"value": "end_date"
}
] |
[
{
"entity_id": 0,
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16
]
},
{
"entity_id": 1,
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2,
3
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{
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9
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{
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},
{
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{
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{
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},
{
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},
{
"entity_id": 14,
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,588
|
toxicology
|
bird:dev.json:270
|
Among the molecules with element Calcium, are they mostly carcinogenic or non carcinogenic?
|
SELECT T2.label FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.element = 'ca' GROUP BY T2.label ORDER BY COUNT(T2.label) DESC LIMIT 1
|
[
"Among",
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"with",
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"Calcium",
",",
"are",
"they",
"mostly",
"carcinogenic",
"or",
"non",
"carcinogenic",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "molecule_id"
},
{
"id": 2,
"type": "table",
"value": "molecule"
},
{
"id": 3,
"type": "column",
"value": "element"
},
{
"id": 0,
"type": "column",
"value": "label"
},
{
"id": 1,
"type": "table",
"value": "atom"
},
{
"id": 4,
"type": "value",
"value": "ca"
}
] |
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{
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},
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{
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{
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{
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
3,608
|
book_publishing_company
|
bird:train.json:184
|
List all employees who are at the maximum level in their job designation.
|
SELECT T1.fname, T1.lname FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.job_lvl = T2.max_lvl
|
[
"List",
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"employees",
"who",
"are",
"at",
"the",
"maximum",
"level",
"in",
"their",
"job",
"designation",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "employee"
},
{
"id": 4,
"type": "column",
"value": "job_lvl"
},
{
"id": 5,
"type": "column",
"value": "max_lvl"
},
{
"id": 6,
"type": "column",
"value": "job_id"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 3,
"type": "table",
"value": "jobs"
}
] |
[
{
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"token_idxs": []
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{
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},
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2
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11
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8
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7
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},
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},
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},
{
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"token_idxs": []
},
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
4,386
|
soccer_2016
|
bird:train.json:1903
|
Which player became the man of the series in the year 2012? Give the name and country of this player.
|
SELECT T2.Player_Name, T3.Country_Name FROM Season AS T1 INNER JOIN Player AS T2 ON T1.Man_of_the_Series = T2.Player_Id INNER JOIN Country AS T3 ON T2.Country_Name = T3.Country_Id WHERE T1.Season_Year = 2012
|
[
"Which",
"player",
"became",
"the",
"man",
"of",
"the",
"series",
"in",
"the",
"year",
"2012",
"?",
"Give",
"the",
"name",
"and",
"country",
"of",
"this",
"player",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "man_of_the_series"
},
{
"id": 1,
"type": "column",
"value": "country_name"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 3,
"type": "column",
"value": "season_year"
},
{
"id": 7,
"type": "column",
"value": "country_id"
},
{
"id": 9,
"type": "column",
"value": "player_id"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "table",
"value": "season"
},
{
"id": 6,
"type": "table",
"value": "player"
},
{
"id": 4,
"type": "value",
"value": "2012"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
1
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
4,
5,
6,
7
]
},
{
"entity_id": 9,
"token_idxs": [
20
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
14,013
|
hr_1
|
spider:train_spider.json:3511
|
display the department id and the total salary for those departments which contains at least two employees.
|
SELECT department_id , SUM(salary) FROM employees GROUP BY department_id HAVING count(*) >= 2
|
[
"display",
"the",
"department",
"i",
"d",
"and",
"the",
"total",
"salary",
"for",
"those",
"departments",
"which",
"contains",
"at",
"least",
"two",
"employees",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "salary"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
8,834
|
superhero
|
bird:dev.json:725
|
How many superheroes are published by Marvel Comics?
|
SELECT COUNT(T1.id) FROM superhero AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id WHERE T2.publisher_name = 'Marvel Comics'
|
[
"How",
"many",
"superheroes",
"are",
"published",
"by",
"Marvel",
"Comics",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "publisher_name"
},
{
"id": 3,
"type": "value",
"value": "Marvel Comics"
},
{
"id": 5,
"type": "column",
"value": "publisher_id"
},
{
"id": 0,
"type": "table",
"value": "superhero"
},
{
"id": 1,
"type": "table",
"value": "publisher"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
4,351
|
legislator
|
bird:train.json:4840
|
Provide the full name and birth date of the legislator with a contact form of http://www.brown.senate.gov/contact/.
|
SELECT T1.official_full_name, T1.birthday_bio FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.contact_form = 'http://www.brown.senate.gov/contact/'
|
[
"Provide",
"the",
"full",
"name",
"and",
"birth",
"date",
"of",
"the",
"legislator",
"with",
"a",
"contact",
"form",
"of",
"http://www.brown.senate.gov/contact/."
] |
[
{
"id": 5,
"type": "value",
"value": "http://www.brown.senate.gov/contact/"
},
{
"id": 0,
"type": "column",
"value": "official_full_name"
},
{
"id": 3,
"type": "table",
"value": "current-terms"
},
{
"id": 1,
"type": "column",
"value": "birthday_bio"
},
{
"id": 4,
"type": "column",
"value": "contact_form"
},
{
"id": 6,
"type": "column",
"value": "bioguide_id"
},
{
"id": 7,
"type": "column",
"value": "bioguide"
},
{
"id": 2,
"type": "table",
"value": "current"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"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-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,848
|
shipping
|
bird:train.json:5592
|
State the headquarter of the truck which completed shipment no.1045.
|
SELECT T1.make FROM truck AS T1 INNER JOIN shipment AS T2 ON T1.truck_id = T2.truck_id WHERE T2.ship_id = 1045
|
[
"State",
"the",
"headquarter",
"of",
"the",
"truck",
"which",
"completed",
"shipment",
"no.1045",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 5,
"type": "column",
"value": "truck_id"
},
{
"id": 3,
"type": "column",
"value": "ship_id"
},
{
"id": 1,
"type": "table",
"value": "truck"
},
{
"id": 0,
"type": "column",
"value": "make"
},
{
"id": 4,
"type": "value",
"value": "1045"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"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": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
13,353
|
boat_1
|
bird:test.json:900
|
How many reservations for each boat did the sailors with an id greater than 1 make?
|
SELECT bid , count(*) FROM Reserves WHERE sid > 1 GROUP BY bid
|
[
"How",
"many",
"reservations",
"for",
"each",
"boat",
"did",
"the",
"sailors",
"with",
"an",
"i",
"d",
"greater",
"than",
"1",
"make",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "reserves"
},
{
"id": 1,
"type": "column",
"value": "bid"
},
{
"id": 2,
"type": "column",
"value": "sid"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
11,
12
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
6,275
|
movie_3
|
bird:train.json:9291
|
Which city does the address 1623 Kingstown Drive belong to?
|
SELECT T1.city FROM city AS T1 INNER JOIN address AS T2 ON T2.city_id = T1.city_id WHERE T2.address = '1623 Kingstown Drive'
|
[
"Which",
"city",
"does",
"the",
"address",
"1623",
"Kingstown",
"Drive",
"belong",
"to",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "1623 Kingstown Drive"
},
{
"id": 2,
"type": "table",
"value": "address"
},
{
"id": 3,
"type": "column",
"value": "address"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
5,
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",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
15,126
|
movie_platform
|
bird:train.json:126
|
How many critics were given to the movie that got the most movie popularity number.
|
SELECT COUNT(T1.critic) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_popularity = ( SELECT MAX(movie_popularity) FROM movies )
|
[
"How",
"many",
"critics",
"were",
"given",
"to",
"the",
"movie",
"that",
"got",
"the",
"most",
"movie",
"popularity",
"number",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "movie_popularity"
},
{
"id": 4,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "table",
"value": "ratings"
},
{
"id": 1,
"type": "table",
"value": "movies"
},
{
"id": 3,
"type": "column",
"value": "critic"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
10,280
|
music_2
|
spider:train_spider.json:5223
|
What is the type of vocals that the band member with the last name "Heilo" played the most?
|
SELECT TYPE FROM vocals AS T1 JOIN band AS T2 ON T1.bandmate = T2.id WHERE lastname = "Heilo" GROUP BY TYPE ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"type",
"of",
"vocals",
"that",
"the",
"band",
"member",
"with",
"the",
"last",
"name",
"\"",
"Heilo",
"\"",
"played",
"the",
"most",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "column",
"value": "bandmate"
},
{
"id": 1,
"type": "table",
"value": "vocals"
},
{
"id": 4,
"type": "column",
"value": "Heilo"
},
{
"id": 0,
"type": "column",
"value": "type"
},
{
"id": 2,
"type": "table",
"value": "band"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
3,257
|
planet_1
|
bird:test.json:1929
|
Find the number of employees who do not have clearance in Mars .
|
select count(*) from employee where employeeid not in ( select t2.employeeid from has_clearance as t1 join employee as t2 on t1.employee = t2.employeeid join planet as t3 on t1.planet = t3.planetid where t3.name = "mars" );
|
[
"Find",
"the",
"number",
"of",
"employees",
"who",
"do",
"not",
"have",
"clearance",
"in",
"Mars",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "has_clearance"
},
{
"id": 1,
"type": "column",
"value": "employeeid"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 7,
"type": "column",
"value": "planetid"
},
{
"id": 8,
"type": "column",
"value": "employee"
},
{
"id": 2,
"type": "table",
"value": "planet"
},
{
"id": 6,
"type": "column",
"value": "planet"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "mars"
}
] |
[
{
"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": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
8,
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",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O"
] |
14,153
|
soccer_2016
|
bird:train.json:1826
|
How many umpires are from South Africa?
|
SELECT SUM(CASE WHEN T1.Country_Name = 'South Africa' THEN 1 ELSE 0 END) FROM Country AS T1 INNER JOIN Umpire AS T2 ON T1.Country_ID = T2.Umpire_Country
|
[
"How",
"many",
"umpires",
"are",
"from",
"South",
"Africa",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "umpire_country"
},
{
"id": 6,
"type": "column",
"value": "country_name"
},
{
"id": 7,
"type": "value",
"value": "South Africa"
},
{
"id": 2,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "umpire"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"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": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5,
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
5,718
|
donor
|
bird:train.json:3244
|
For the donation of the project 'Awesome Audiobooks Make Avid Readers', what was the percentage of the tip in the total amount?
|
SELECT CAST(SUM(T2.donation_optional_support) AS REAL) * 100 / SUM(T2.donation_total) FROM essays AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.title LIKE 'Awesome Audiobooks Make Avid Readers'
|
[
"For",
"the",
"donation",
"of",
"the",
"project",
"'",
"Awesome",
"Audiobooks",
"Make",
"Avid",
"Readers",
"'",
",",
"what",
"was",
"the",
"percentage",
"of",
"the",
"tip",
"in",
"the",
"total",
"amount",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Awesome Audiobooks Make Avid Readers"
},
{
"id": 7,
"type": "column",
"value": "donation_optional_support"
},
{
"id": 6,
"type": "column",
"value": "donation_total"
},
{
"id": 1,
"type": "table",
"value": "donations"
},
{
"id": 4,
"type": "column",
"value": "projectid"
},
{
"id": 0,
"type": "table",
"value": "essays"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
3,910
|
flight_4
|
spider:train_spider.json:6831
|
Find the name, city, and country of the airport that has the highest latitude.
|
SELECT name , city , country FROM airports ORDER BY elevation DESC LIMIT 1
|
[
"Find",
"the",
"name",
",",
"city",
",",
"and",
"country",
"of",
"the",
"airport",
"that",
"has",
"the",
"highest",
"latitude",
"."
] |
[
{
"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": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,105
|
region_building
|
bird:test.json:326
|
List the names of regions in alphabetical order.
|
SELECT Name FROM region ORDER BY Name ASC
|
[
"List",
"the",
"names",
"of",
"regions",
"in",
"alphabetical",
"order",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "region"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
14,737
|
shooting
|
bird:train.json:2469
|
From the cases where the subject are male, list the case number and the location and subject status.
|
SELECT T1.case_number, T1.location, T1.subject_statuses FROM incidents AS T1 INNER JOIN subjects AS T2 ON T1.case_number = T2.case_number WHERE T2.gender = 'M'
|
[
"From",
"the",
"cases",
"where",
"the",
"subject",
"are",
"male",
",",
"list",
"the",
"case",
"number",
"and",
"the",
"location",
"and",
"subject",
"status",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "subject_statuses"
},
{
"id": 0,
"type": "column",
"value": "case_number"
},
{
"id": 3,
"type": "table",
"value": "incidents"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 4,
"type": "table",
"value": "subjects"
},
{
"id": 5,
"type": "column",
"value": "gender"
},
{
"id": 6,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11,
12
]
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
5,514
|
synthea
|
bird:train.json:1420
|
List the procedures received by Emmy Waelchi.
|
SELECT T2.DESCRIPTION FROM patients AS T1 INNER JOIN procedures AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Emmy' AND T1.last = 'Waelchi'
|
[
"List",
"the",
"procedures",
"received",
"by",
"Emmy",
"Waelchi",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "procedures"
},
{
"id": 1,
"type": "table",
"value": "patients"
},
{
"id": 3,
"type": "column",
"value": "patient"
},
{
"id": 7,
"type": "value",
"value": "Waelchi"
},
{
"id": 4,
"type": "column",
"value": "first"
},
{
"id": 5,
"type": "value",
"value": "Emmy"
},
{
"id": 6,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
0
]
},
{
"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": []
}
] |
[
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
53
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5162
|
What are the names of the workshop groups that have bookings with status code "stop"?
|
SELECT T2.Store_Name FROM Bookings AS T1 JOIN Drama_Workshop_Groups AS T2 ON T1.Workshop_Group_ID = T2.Workshop_Group_ID WHERE T1.Status_Code = "stop"
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"workshop",
"groups",
"that",
"have",
"bookings",
"with",
"status",
"code",
"\"",
"stop",
"\"",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "drama_workshop_groups"
},
{
"id": 5,
"type": "column",
"value": "workshop_group_id"
},
{
"id": 3,
"type": "column",
"value": "status_code"
},
{
"id": 0,
"type": "column",
"value": "store_name"
},
{
"id": 1,
"type": "table",
"value": "bookings"
},
{
"id": 4,
"type": "column",
"value": "stop"
}
] |
[
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16,
17
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{
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},
{
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}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE"
] |
9,016
|
retail_world
|
bird:train.json:6617
|
Which products by Plutzer Lebensmittelgromrkte AG were discontinued and what are their price?
|
SELECT T1.UnitPrice FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Plutzer Lebensmittelgromrkte AG' AND T1.Discontinued = 1
|
[
"Which",
"products",
"by",
"Plutzer",
"Lebensmittelgromrkte",
"AG",
"were",
"discontinued",
"and",
"what",
"are",
"their",
"price",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Plutzer Lebensmittelgromrkte AG"
},
{
"id": 6,
"type": "column",
"value": "discontinued"
},
{
"id": 4,
"type": "column",
"value": "companyname"
},
{
"id": 3,
"type": "column",
"value": "supplierid"
},
{
"id": 0,
"type": "column",
"value": "unitprice"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
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},
{
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},
{
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}
] |
[
"O",
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"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O"
] |
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