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216
|
university
|
bird:train.json:8076
|
Among the universities in Australia, how many of them have more than 15000 students in 2011?
|
SELECT COUNT(*) FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id INNER JOIN country AS T3 ON T3.id = T1.country_id WHERE T3.country_name = 'Australia' AND T2.year = 2011 AND T2.num_students > 15000
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"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
217
|
law_episode
|
bird:train.json:1333
|
List out all the credit names for episode 9.
|
SELECT T3.name FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T1.episode = 9
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"type": "column",
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"O",
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"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
218
|
local_govt_mdm
|
spider:train_spider.json:2647
|
What is the cmi cross reference id that is related to at least one council tax entry? List the cross reference id and source system code.
|
SELECT T1.cmi_cross_ref_id , T1.source_system_code FROM CMI_Cross_References AS T1 JOIN Council_Tax AS T2 ON T1.cmi_cross_ref_id = T2.cmi_cross_ref_id GROUP BY T1.cmi_cross_ref_id HAVING count(*) >= 1
|
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"."
] |
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{
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"type": "column",
"value": "cmi_cross_ref_id"
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{
"id": 3,
"type": "table",
"value": "council_tax"
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{
"id": 4,
"type": "value",
"value": "1"
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"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
219
|
entertainment_awards
|
spider:train_spider.json:4614
|
List the most common type of artworks.
|
SELECT TYPE FROM artwork GROUP BY TYPE ORDER BY COUNT(*) DESC LIMIT 1
|
[
"List",
"the",
"most",
"common",
"type",
"of",
"artworks",
"."
] |
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{
"id": 0,
"type": "table",
"value": "artwork"
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{
"id": 1,
"type": "column",
"value": "type"
}
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},
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
220
|
codebase_community
|
bird:dev.json:696
|
Count the number of posts with a tag specified as 'careers'.
|
SELECT COUNT(Id) FROM tags WHERE TagName = 'careers'
|
[
"Count",
"the",
"number",
"of",
"posts",
"with",
"a",
"tag",
"specified",
"as",
"'",
"careers",
"'",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "tagname"
},
{
"id": 2,
"type": "value",
"value": "careers"
},
{
"id": 0,
"type": "table",
"value": "tags"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
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"token_idxs": []
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{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
221
|
election
|
spider:train_spider.json:2776
|
Show the name of each party and the corresponding number of delegates from that party.
|
SELECT T2.Party , COUNT(*) FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party
|
[
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"the",
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"of",
"delegates",
"from",
"that",
"party",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "election"
},
{
"id": 3,
"type": "column",
"value": "party_id"
},
{
"id": 0,
"type": "column",
"value": "party"
},
{
"id": 2,
"type": "table",
"value": "party"
}
] |
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
222
|
soccer_2016
|
bird:train.json:1984
|
How many matches are there in 2008?
|
SELECT COUNT(Match_Id) FROM `Match` WHERE Match_Date LIKE '2008%'
|
[
"How",
"many",
"matches",
"are",
"there",
"in",
"2008",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "match_date"
},
{
"id": 3,
"type": "column",
"value": "match_id"
},
{
"id": 0,
"type": "table",
"value": "Match"
},
{
"id": 2,
"type": "value",
"value": "2008%"
}
] |
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{
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{
"entity_id": 19,
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}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
223
|
legislator
|
bird:train.json:4848
|
Which legislators are woman?
|
SELECT first_name, last_name FROM historical WHERE gender_bio = 'F'
|
[
"Which",
"legislators",
"are",
"woman",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "historical"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "column",
"value": "gender_bio"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "value",
"value": "F"
}
] |
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O"
] |
224
|
superstore
|
bird:train.json:2435
|
How many orders purchased by Aaron Bergman have been delivered with the slowest shipping speed?
|
SELECT COUNT(*) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T1.`Customer Name` = 'Aaron Bergman' AND T2.`Ship Mode` = 'Standard Class'
|
[
"How",
"many",
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"purchased",
"by",
"Aaron",
"Bergman",
"have",
"been",
"delivered",
"with",
"the",
"slowest",
"shipping",
"speed",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "central_superstore"
},
{
"id": 6,
"type": "value",
"value": "Standard Class"
},
{
"id": 3,
"type": "column",
"value": "Customer Name"
},
{
"id": 4,
"type": "value",
"value": "Aaron Bergman"
},
{
"id": 2,
"type": "column",
"value": "Customer ID"
},
{
"id": 5,
"type": "column",
"value": "Ship Mode"
},
{
"id": 0,
"type": "table",
"value": "people"
}
] |
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{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
225
|
financial
|
bird:dev.json:164
|
Who placed the order with the id 32423?
|
SELECT T3.client_id FROM `order` AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id INNER JOIN disp AS T4 ON T4.account_id = T2.account_id INNER JOIN client AS T3 ON T4.client_id = T3.client_id WHERE T1.order_id = 32423
|
[
"Who",
"placed",
"the",
"order",
"with",
"the",
"i",
"d",
"32423",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "account_id"
},
{
"id": 0,
"type": "column",
"value": "client_id"
},
{
"id": 2,
"type": "column",
"value": "order_id"
},
{
"id": 6,
"type": "table",
"value": "account"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 3,
"type": "value",
"value": "32423"
},
{
"id": 5,
"type": "table",
"value": "order"
},
{
"id": 4,
"type": "table",
"value": "disp"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
226
|
software_company
|
bird:train.json:8541
|
In widowed male customers ages from 40 to 60, how many of them has an income ranges from 3000 and above?
|
SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.age >= 40 AND T1.age <= 60 AND T1.MARITAL_STATUS = 'Widowed' AND T1.SEX = 'Male' AND T2.INCOME_K >= 2000 AND T2.INCOME_K <= 3000
|
[
"In",
"widowed",
"male",
"customers",
"ages",
"from",
"40",
"to",
"60",
",",
"how",
"many",
"of",
"them",
"has",
"an",
"income",
"ranges",
"from",
"3000",
"and",
"above",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "marital_status"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 11,
"type": "column",
"value": "income_k"
},
{
"id": 8,
"type": "value",
"value": "Widowed"
},
{
"id": 1,
"type": "table",
"value": "demog"
},
{
"id": 3,
"type": "column",
"value": "geoid"
},
{
"id": 10,
"type": "value",
"value": "Male"
},
{
"id": 12,
"type": "value",
"value": "2000"
},
{
"id": 13,
"type": "value",
"value": "3000"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 9,
"type": "column",
"value": "sex"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "40"
},
{
"id": 6,
"type": "value",
"value": "60"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
1
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
2
]
},
{
"entity_id": 11,
"token_idxs": [
16
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": [
19
]
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
227
|
network_2
|
spider:train_spider.json:4456
|
Find the names of females who are friends with Zach
|
SELECT T1.name FROM Person AS T1 JOIN PersonFriend AS T2 ON T1.name = T2.name WHERE T2.friend = 'Zach' AND T1.gender = 'female'
|
[
"Find",
"the",
"names",
"of",
"females",
"who",
"are",
"friends",
"with",
"Zach"
] |
[
{
"id": 2,
"type": "table",
"value": "personfriend"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "column",
"value": "friend"
},
{
"id": 5,
"type": "column",
"value": "gender"
},
{
"id": 6,
"type": "value",
"value": "female"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "Zach"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE"
] |
228
|
movie_2
|
bird:test.json:1836
|
What is the name of the film playing at the most number of theaters?
|
SELECT T1.title FROM movies AS T1 JOIN movietheaters AS T2 ON T1.code = T2.movie GROUP BY T1.title ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"film",
"playing",
"at",
"the",
"most",
"number",
"of",
"theaters",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "movietheaters"
},
{
"id": 1,
"type": "table",
"value": "movies"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "column",
"value": "movie"
},
{
"id": 3,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O"
] |
229
|
aan_1
|
bird:test.json:1007
|
Give the title of the paper which cites most number of papers?
|
SELECT T2.title FROM Citation AS T1 JOIN Paper AS T2 ON T2.paper_id = T1.paper_id GROUP BY T1.paper_id ORDER BY count(*) DESC LIMIT 1
|
[
"Give",
"the",
"title",
"of",
"the",
"paper",
"which",
"cites",
"most",
"number",
"of",
"papers",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "paper_id"
},
{
"id": 2,
"type": "table",
"value": "citation"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "paper"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
230
|
public_review_platform
|
bird:train.json:3920
|
What is the review length of user 60776 to business with business ID 1?
|
SELECT review_length FROM Reviews WHERE user_id = 60776 AND business_id = 1
|
[
"What",
"is",
"the",
"review",
"length",
"of",
"user",
"60776",
"to",
"business",
"with",
"business",
"ID",
"1",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "review_length"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "reviews"
},
{
"id": 2,
"type": "column",
"value": "user_id"
},
{
"id": 3,
"type": "value",
"value": "60776"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
231
|
college_1
|
spider:train_spider.json:3243
|
What is the first name of each student enrolled in class ACCT-211?
|
SELECT T3.stu_fname FROM CLASS AS T1 JOIN enroll AS T2 ON T1.class_code = T2.class_code JOIN student AS T3 ON T2.stu_num = T3.stu_num WHERE T1.crs_code = 'ACCT-211'
|
[
"What",
"is",
"the",
"first",
"name",
"of",
"each",
"student",
"enrolled",
"in",
"class",
"ACCT-211",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "class_code"
},
{
"id": 0,
"type": "column",
"value": "stu_fname"
},
{
"id": 2,
"type": "column",
"value": "crs_code"
},
{
"id": 3,
"type": "value",
"value": "ACCT-211"
},
{
"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"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
232
|
toxicology
|
bird:dev.json:289
|
Is molecule TR151 carcinogenic?
|
SELECT T.label FROM molecule AS T WHERE T.molecule_id = 'TR151'
|
[
"Is",
"molecule",
"TR151",
"carcinogenic",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "molecule_id"
},
{
"id": 0,
"type": "table",
"value": "molecule"
},
{
"id": 1,
"type": "column",
"value": "label"
},
{
"id": 3,
"type": "value",
"value": "TR151"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"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",
"B-TABLE",
"B-VALUE",
"O",
"O"
] |
233
|
video_game
|
bird:test.json:1935
|
What is the average units sold in millions of the games that are not developed by Nintendo?
|
SELECT avg(Units_sold_Millions) FROM game WHERE developers != 'Nintendo'
|
[
"What",
"is",
"the",
"average",
"units",
"sold",
"in",
"millions",
"of",
"the",
"games",
"that",
"are",
"not",
"developed",
"by",
"Nintendo",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "units_sold_millions"
},
{
"id": 1,
"type": "column",
"value": "developers"
},
{
"id": 2,
"type": "value",
"value": "Nintendo"
},
{
"id": 0,
"type": "table",
"value": "game"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
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14
]
},
{
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16
]
},
{
"entity_id": 3,
"token_idxs": [
4,
5,
6,
7
]
},
{
"entity_id": 4,
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},
{
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},
{
"entity_id": 6,
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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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"token_idxs": []
},
{
"entity_id": 15,
"token_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",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
234
|
disney
|
bird:train.json:4672
|
What is the highest grossing movie without a song?
|
SELECT T1.movie_title FROM movies_total_gross AS T1 INNER JOIN characters AS T2 ON T2.movie_title = T1.movie_title WHERE T2.song IS NULL ORDER BY CAST(REPLACE(trim(T1.total_gross, '$'), ',', '') AS REAL) DESC LIMIT 1
|
[
"What",
"is",
"the",
"highest",
"grossing",
"movie",
"without",
"a",
"song",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "movies_total_gross"
},
{
"id": 0,
"type": "column",
"value": "movie_title"
},
{
"id": 5,
"type": "column",
"value": "total_gross"
},
{
"id": 2,
"type": "table",
"value": "characters"
},
{
"id": 3,
"type": "column",
"value": "song"
},
{
"id": 4,
"type": "value",
"value": ","
},
{
"id": 6,
"type": "value",
"value": "$"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
235
|
retail_world
|
bird:train.json:6478
|
What is the full name of the Vice President of Sales. Give me the URL of his/her photo.
|
SELECT FirstName, LastName FROM Employees WHERE Title = 'Vice President, Sales'
|
[
"What",
"is",
"the",
"full",
"name",
"of",
"the",
"Vice",
"President",
"of",
"Sales",
".",
"Give",
"me",
"the",
"URL",
"of",
"his",
"/",
"her",
"photo",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Vice President, Sales"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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7,
8,
9,
10
]
},
{
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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",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
236
|
movie_3
|
bird:train.json:9150
|
What is the description of the film Artist Coldblooded?
|
SELECT description FROM film WHERE title = 'ARTIST COLDBLOODED'
|
[
"What",
"is",
"the",
"description",
"of",
"the",
"film",
"Artist",
"Coldblooded",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "ARTIST COLDBLOODED"
},
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O"
] |
237
|
professional_basketball
|
bird:train.json:2813
|
Which player, born in Winter Haven, played 12 minutes per season during the 1980s in the All-Stars?
|
SELECT DISTINCT T1.firstName, T1.middleName, T1.lastName FROM players AS T1 INNER JOIN player_allstar AS T2 ON T1.playerID = T2.playerID WHERE T1.birthCity = 'Winter Haven' AND T2.season_id BETWEEN 1980 AND 1989 AND T2.minutes = 12
|
[
"Which",
"player",
",",
"born",
"in",
"Winter",
"Haven",
",",
"played",
"12",
"minutes",
"per",
"season",
"during",
"the",
"1980s",
"in",
"the",
"All",
"-",
"Stars",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "player_allstar"
},
{
"id": 7,
"type": "value",
"value": "Winter Haven"
},
{
"id": 1,
"type": "column",
"value": "middlename"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 6,
"type": "column",
"value": "birthcity"
},
{
"id": 8,
"type": "column",
"value": "season_id"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "table",
"value": "players"
},
{
"id": 11,
"type": "column",
"value": "minutes"
},
{
"id": 9,
"type": "value",
"value": "1980"
},
{
"id": 10,
"type": "value",
"value": "1989"
},
{
"id": 12,
"type": "value",
"value": "12"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": [
1
]
},
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19,
20
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},
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8
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},
{
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5,
6
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},
{
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12
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{
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15
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},
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10
]
},
{
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"token_idxs": [
9
]
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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",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O"
] |
238
|
hockey
|
bird:train.json:7665
|
Among the coaches who have gotten in the Hall of Fame, how many of them have a weight of over 195?
|
SELECT COUNT(DISTINCT T1.coachID) FROM Master AS T1 INNER JOIN HOF AS T2 ON T1.hofID = T2.hofID WHERE T1.weight > 195
|
[
"Among",
"the",
"coaches",
"who",
"have",
"gotten",
"in",
"the",
"Hall",
"of",
"Fame",
",",
"how",
"many",
"of",
"them",
"have",
"a",
"weight",
"of",
"over",
"195",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "coachid"
},
{
"id": 0,
"type": "table",
"value": "master"
},
{
"id": 2,
"type": "column",
"value": "weight"
},
{
"id": 5,
"type": "column",
"value": "hofid"
},
{
"id": 1,
"type": "table",
"value": "hof"
},
{
"id": 3,
"type": "value",
"value": "195"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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9
]
},
{
"entity_id": 2,
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18
]
},
{
"entity_id": 3,
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21
]
},
{
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2
]
},
{
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},
{
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},
{
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},
{
"entity_id": 8,
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},
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"entity_id": 9,
"token_idxs": []
},
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},
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"token_idxs": []
},
{
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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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
239
|
movies_4
|
bird:train.json:536
|
What is the average ratio between female and male actors in a movie?
|
SELECT CAST(COUNT(CASE WHEN T2.gender = 'Female' THEN T1.person_id ELSE NULL END) AS REAL) / COUNT(CASE WHEN T2.gender = 'Male' THEN T1.person_id ELSE NULL END) FROM movie_cast AS T1 INNER JOIN gender AS T2 ON T1.gender_id = T2.gender_id
|
[
"What",
"is",
"the",
"average",
"ratio",
"between",
"female",
"and",
"male",
"actors",
"in",
"a",
"movie",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "movie_cast"
},
{
"id": 2,
"type": "column",
"value": "gender_id"
},
{
"id": 3,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "gender"
},
{
"id": 4,
"type": "column",
"value": "gender"
},
{
"id": 6,
"type": "value",
"value": "Female"
},
{
"id": 5,
"type": "value",
"value": "Male"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
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},
{
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},
{
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8
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},
{
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6
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{
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},
{
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},
{
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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-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
240
|
driving_school
|
spider:train_spider.json:6650
|
How many staff live in state Georgia?
|
SELECT count(*) FROM Addresses WHERE state_province_county = "Georgia";
|
[
"How",
"many",
"staff",
"live",
"in",
"state",
"Georgia",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "state_province_county"
},
{
"id": 0,
"type": "table",
"value": "addresses"
},
{
"id": 2,
"type": "column",
"value": "Georgia"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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6
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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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},
{
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},
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},
{
"entity_id": 12,
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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"
] |
242
|
public_review_platform
|
bird:train.json:4116
|
How many businesses in the city of Scottsdale open on Sunday at 12PM?
|
SELECT COUNT(DISTINCT T2.business_id) FROM Business AS T1 INNER JOIN Business_hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T1.city = 'Scottsdale' AND T3.day_of_week = 'Sunday' AND T2.opening_time = '12PM'
|
[
"How",
"many",
"businesses",
"in",
"the",
"city",
"of",
"Scottsdale",
"open",
"on",
"Sunday",
"at",
"12PM",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "business_hours"
},
{
"id": 9,
"type": "column",
"value": "opening_time"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 7,
"type": "column",
"value": "day_of_week"
},
{
"id": 6,
"type": "value",
"value": "Scottsdale"
},
{
"id": 2,
"type": "table",
"value": "business"
},
{
"id": 4,
"type": "column",
"value": "day_id"
},
{
"id": 8,
"type": "value",
"value": "Sunday"
},
{
"id": 0,
"type": "table",
"value": "days"
},
{
"id": 5,
"type": "column",
"value": "city"
},
{
"id": 10,
"type": "value",
"value": "12PM"
}
] |
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{
"entity_id": 0,
"token_idxs": [
10
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
243
|
food_inspection_2
|
bird:train.json:6241
|
How many grocery stores paid $250 fine upon their inspection?
|
SELECT COUNT(DISTINCT T1.license_no) FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN violation AS T3 ON T2.inspection_id = T3.inspection_id WHERE T1.facility_type = 'Grocery Store' AND T3.fine = 250
|
[
"How",
"many",
"grocery",
"stores",
"paid",
"$",
"250",
"fine",
"upon",
"their",
"inspection",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "establishment"
},
{
"id": 4,
"type": "column",
"value": "inspection_id"
},
{
"id": 5,
"type": "column",
"value": "facility_type"
},
{
"id": 6,
"type": "value",
"value": "Grocery Store"
},
{
"id": 1,
"type": "column",
"value": "license_no"
},
{
"id": 3,
"type": "table",
"value": "inspection"
},
{
"id": 0,
"type": "table",
"value": "violation"
},
{
"id": 7,
"type": "column",
"value": "fine"
},
{
"id": 8,
"type": "value",
"value": "250"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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10
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"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
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"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
244
|
car_racing
|
bird:test.json:1632
|
Find the countries in which there are both drivers with make "Dodge" and drivers with make "Chevrolet".
|
SELECT t2.country FROM driver AS t1 JOIN country AS t2 ON t1.country = t2.country_id WHERE t1.Make = "Dodge" INTERSECT SELECT t2.country FROM driver AS t1 JOIN country AS t2 ON t1.country = t2.country_id WHERE t1.Make = "Chevrolet"
|
[
"Find",
"the",
"countries",
"in",
"which",
"there",
"are",
"both",
"drivers",
"with",
"make",
"\"",
"Dodge",
"\"",
"and",
"drivers",
"with",
"make",
"\"",
"Chevrolet",
"\"",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "country_id"
},
{
"id": 5,
"type": "column",
"value": "Chevrolet"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "driver"
},
{
"id": 4,
"type": "column",
"value": "Dodge"
},
{
"id": 3,
"type": "column",
"value": "make"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
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"token_idxs": [
12
]
},
{
"entity_id": 5,
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19
]
},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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},
{
"entity_id": 10,
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},
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"entity_id": 11,
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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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
245
|
candidate_poll
|
spider:train_spider.json:2429
|
What are the names of all female candidates in alphabetical order (sex is F)?
|
SELECT t1.name FROM people AS t1 JOIN candidate AS t2 ON t1.people_id = t2.people_id WHERE t1.sex = 'F' ORDER BY t1.name
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"female",
"candidates",
"in",
"alphabetical",
"order",
"(",
"sex",
"is",
"F",
")",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "candidate"
},
{
"id": 5,
"type": "column",
"value": "people_id"
},
{
"id": 1,
"type": "table",
"value": "people"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "sex"
},
{
"id": 4,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
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3
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},
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},
{
"entity_id": 2,
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7
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
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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",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
246
|
codebase_community
|
bird:dev.json:580
|
Name 10 users with the badge name 'Necromancer.'
|
SELECT T1.DisplayName FROM users AS T1 INNER JOIN badges AS T2 ON T1.Id = T2.UserId WHERE T2.Name = 'Necromancer' LIMIT 10
|
[
"Name",
"10",
"users",
"with",
"the",
"badge",
"name",
"'",
"Necromancer",
".",
"'"
] |
[
{
"id": 0,
"type": "column",
"value": "displayname"
},
{
"id": 4,
"type": "value",
"value": "Necromancer"
},
{
"id": 2,
"type": "table",
"value": "badges"
},
{
"id": 6,
"type": "column",
"value": "userid"
},
{
"id": 1,
"type": "table",
"value": "users"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
0
]
},
{
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8
]
},
{
"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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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_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-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
247
|
codebase_comments
|
bird:train.json:617
|
Give the number of watchers that the repository of the solution No. 338082 have.
|
SELECT T1.Watchers FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T2.Id = 338082
|
[
"Give",
"the",
"number",
"of",
"watchers",
"that",
"the",
"repository",
"of",
"the",
"solution",
"No",
".",
"338082",
"have",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "watchers"
},
{
"id": 2,
"type": "table",
"value": "solution"
},
{
"id": 4,
"type": "value",
"value": "338082"
},
{
"id": 5,
"type": "column",
"value": "repoid"
},
{
"id": 1,
"type": "table",
"value": "repo"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
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},
{
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10
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},
{
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{
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13
]
},
{
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7
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},
{
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
248
|
law_episode
|
bird:train.json:1310
|
What role was Julia Roberts nominated for?
|
SELECT T2.role FROM Person AS T1 INNER JOIN Award AS T2 ON T1.person_id = T2.person_id WHERE T2.Result = 'Nominee' AND T1.name = 'Julia Roberts'
|
[
"What",
"role",
"was",
"Julia",
"Roberts",
"nominated",
"for",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Julia Roberts"
},
{
"id": 3,
"type": "column",
"value": "person_id"
},
{
"id": 5,
"type": "value",
"value": "Nominee"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 4,
"type": "column",
"value": "result"
},
{
"id": 2,
"type": "table",
"value": "award"
},
{
"id": 0,
"type": "column",
"value": "role"
},
{
"id": 6,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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3,
4
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"B-VALUE",
"O",
"O"
] |
249
|
music_2
|
spider:train_spider.json:5197
|
What is the last name of the musician who was in the most songs?
|
SELECT T2.lastname FROM Performance AS T1 JOIN Band AS T2 ON T1.bandmate = T2.id JOIN Songs AS T3 ON T3.SongId = T1.SongId GROUP BY lastname ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"last",
"name",
"of",
"the",
"musician",
"who",
"was",
"in",
"the",
"most",
"songs",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "performance"
},
{
"id": 0,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "column",
"value": "bandmate"
},
{
"id": 4,
"type": "column",
"value": "songid"
},
{
"id": 1,
"type": "table",
"value": "songs"
},
{
"id": 3,
"type": "table",
"value": "band"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
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{
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
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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": 16,
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
250
|
inn_1
|
spider:train_spider.json:2590
|
List the names and decor of rooms that have a king bed. Sort the list by their price.
|
SELECT roomName , decor FROM Rooms WHERE bedtype = 'King' ORDER BY basePrice;
|
[
"List",
"the",
"names",
"and",
"decor",
"of",
"rooms",
"that",
"have",
"a",
"king",
"bed",
".",
"Sort",
"the",
"list",
"by",
"their",
"price",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "baseprice"
},
{
"id": 1,
"type": "column",
"value": "roomname"
},
{
"id": 3,
"type": "column",
"value": "bedtype"
},
{
"id": 0,
"type": "table",
"value": "rooms"
},
{
"id": 2,
"type": "column",
"value": "decor"
},
{
"id": 4,
"type": "value",
"value": "King"
}
] |
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"token_idxs": [
6
]
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2
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4
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10
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"entity_id": 16,
"token_idxs": []
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
251
|
donor
|
bird:train.json:3251
|
Which school county in the state of New York has a high number of low poverty levels?
|
SELECT school_county FROM projects WHERE poverty_level = 'low poverty' AND school_state = 'NY' GROUP BY school_state ORDER BY COUNT(poverty_level) DESC LIMIT 1
|
[
"Which",
"school",
"county",
"in",
"the",
"state",
"of",
"New",
"York",
"has",
"a",
"high",
"number",
"of",
"low",
"poverty",
"levels",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "school_county"
},
{
"id": 3,
"type": "column",
"value": "poverty_level"
},
{
"id": 1,
"type": "column",
"value": "school_state"
},
{
"id": 4,
"type": "value",
"value": "low poverty"
},
{
"id": 0,
"type": "table",
"value": "projects"
},
{
"id": 5,
"type": "value",
"value": "NY"
}
] |
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"entity_id": 15,
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{
"entity_id": 16,
"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
252
|
authors
|
bird:train.json:3547
|
Describe the paper title, published year, conference's short name and included author names in the paper ID of 15.
|
SELECT DISTINCT T1.Title, T1.Year, T3.ShortName, T2.Name FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId INNER JOIN Conference AS T3 ON T1.ConferenceId = T3.Id WHERE T1.Id = 15
|
[
"Describe",
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"title",
",",
"published",
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",",
"conference",
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"short",
"name",
"and",
"included",
"author",
"names",
"in",
"the",
"paper",
"ID",
"of",
"15",
"."
] |
[
{
"id": 9,
"type": "column",
"value": "conferenceid"
},
{
"id": 8,
"type": "table",
"value": "paperauthor"
},
{
"id": 4,
"type": "table",
"value": "conference"
},
{
"id": 2,
"type": "column",
"value": "shortname"
},
{
"id": 10,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 7,
"type": "table",
"value": "paper"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "15"
}
] |
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3
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{
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6
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{
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10
]
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{
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11
]
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{
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"token_idxs": []
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"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
253
|
beer_factory
|
bird:train.json:5352
|
How many transactions were made at Sac State Union?
|
SELECT COUNT(T1.TransactionID) FROM `transaction` AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID WHERE T2.LocationName = 'Sac State Union'
|
[
"How",
"many",
"transactions",
"were",
"made",
"at",
"Sac",
"State",
"Union",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Sac State Union"
},
{
"id": 4,
"type": "column",
"value": "transactionid"
},
{
"id": 2,
"type": "column",
"value": "locationname"
},
{
"id": 0,
"type": "table",
"value": "transaction"
},
{
"id": 5,
"type": "column",
"value": "locationid"
},
{
"id": 1,
"type": "table",
"value": "location"
}
] |
[
{
"entity_id": 0,
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},
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8
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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,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
254
|
swimming
|
spider:train_spider.json:5629
|
Find the names of stadiums that the most swimmers have been to.
|
SELECT t3.name FROM record AS t1 JOIN event AS t2 ON t1.event_id = t2.id JOIN stadium AS t3 ON t3.id = t2.stadium_id GROUP BY t2.stadium_id ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"names",
"of",
"stadiums",
"that",
"the",
"most",
"swimmers",
"have",
"been",
"to",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "stadium_id"
},
{
"id": 6,
"type": "column",
"value": "event_id"
},
{
"id": 2,
"type": "table",
"value": "stadium"
},
{
"id": 3,
"type": "table",
"value": "record"
},
{
"id": 4,
"type": "table",
"value": "event"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
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{
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"token_idxs": []
},
{
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2
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},
{
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4
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},
{
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{
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11
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},
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0
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
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"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
255
|
machine_repair
|
spider:train_spider.json:2235
|
List the names of technicians in ascending order of age.
|
SELECT Name FROM technician ORDER BY Age ASC
|
[
"List",
"the",
"names",
"of",
"technicians",
"in",
"ascending",
"order",
"of",
"age",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "technician"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
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{
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4
]
},
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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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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
256
|
college_3
|
spider:train_spider.json:4668
|
What are the last names of faculty in building Barton, sorted by last name?
|
SELECT Lname FROM FACULTY WHERE Building = "Barton" ORDER BY Lname
|
[
"What",
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"the",
"last",
"names",
"of",
"faculty",
"in",
"building",
"Barton",
",",
"sorted",
"by",
"last",
"name",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "building"
},
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 3,
"type": "column",
"value": "Barton"
},
{
"id": 1,
"type": "column",
"value": "lname"
}
] |
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{
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{
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{
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
257
|
software_company
|
bird:train.json:8583
|
Describe the average income per month and yearly income of the geographic ID in which customer of ID "209556" and "290135".
|
SELECT T2.INCOME_K, T2.INHABITANTS_K * T2.INCOME_K * 12 FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.ID = 209556 OR T1.ID = 290135
|
[
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"of",
"ID",
"\"",
"209556",
"\"",
"and",
"\"",
"290135",
"\"",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "inhabitants_k"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "column",
"value": "income_k"
},
{
"id": 6,
"type": "value",
"value": "209556"
},
{
"id": 7,
"type": "value",
"value": "290135"
},
{
"id": 2,
"type": "table",
"value": "demog"
},
{
"id": 4,
"type": "column",
"value": "geoid"
},
{
"id": 3,
"type": "value",
"value": "12"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
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"O",
"O",
"O",
"O",
"O",
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"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
258
|
card_games
|
bird:dev.json:503
|
What was the expansion type for the set which card "Samite Pilgrim" in it?
|
SELECT type FROM sets WHERE code IN ( SELECT setCode FROM cards WHERE name = 'Samite Pilgrim' )
|
[
"What",
"was",
"the",
"expansion",
"type",
"for",
"the",
"set",
"which",
"card",
"\"",
"Samite",
"Pilgrim",
"\"",
"in",
"it",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Samite Pilgrim"
},
{
"id": 4,
"type": "column",
"value": "setcode"
},
{
"id": 3,
"type": "table",
"value": "cards"
},
{
"id": 0,
"type": "table",
"value": "sets"
},
{
"id": 1,
"type": "column",
"value": "type"
},
{
"id": 2,
"type": "column",
"value": "code"
},
{
"id": 5,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
259
|
world
|
bird:train.json:7897
|
How many languages are there in the country where Tocantins district belongs?
|
SELECT COUNT(DISTINCT T2.Language) FROM City AS T1 INNER JOIN CountryLanguage AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.District = 'Tocantins'
|
[
"How",
"many",
"languages",
"are",
"there",
"in",
"the",
"country",
"where",
"Tocantins",
"district",
"belongs",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "countrylanguage"
},
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 3,
"type": "value",
"value": "Tocantins"
},
{
"id": 2,
"type": "column",
"value": "district"
},
{
"id": 4,
"type": "column",
"value": "language"
},
{
"id": 0,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
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9
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
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"token_idxs": []
},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
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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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O"
] |
260
|
chicago_crime
|
bird:train.json:8760
|
Which alderman represents the ward with the most number of crimes in January, 2018? Please give his or her full name.
|
SELECT T1.ward_no, T1.alderman_first_name, T1.alderman_last_name, T1.alderman_name_suffix FROM Ward AS T1 INNER JOIN Crime AS T2 ON T1.ward_no = T2.ward_no WHERE SUBSTR(T2.date, 1, 1) = '1' AND SUBSTR(T2.date, 5, 4) = '2018' GROUP BY T1.ward_no ORDER BY COUNT(T1.ward_no) DESC LIMIT 1
|
[
"Which",
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"represents",
"the",
"ward",
"with",
"the",
"most",
"number",
"of",
"crimes",
"in",
"January",
",",
"2018",
"?",
"Please",
"give",
"his",
"or",
"her",
"full",
"name",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "alderman_name_suffix"
},
{
"id": 1,
"type": "column",
"value": "alderman_first_name"
},
{
"id": 2,
"type": "column",
"value": "alderman_last_name"
},
{
"id": 0,
"type": "column",
"value": "ward_no"
},
{
"id": 5,
"type": "table",
"value": "crime"
},
{
"id": 4,
"type": "table",
"value": "ward"
},
{
"id": 7,
"type": "value",
"value": "2018"
},
{
"id": 8,
"type": "column",
"value": "date"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "5"
},
{
"id": 10,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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},
{
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1
]
},
{
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{
"entity_id": 4,
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4
]
},
{
"entity_id": 5,
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10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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14
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{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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{
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{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
261
|
superhero
|
bird:dev.json:793
|
Among the superheroes with the race of god/eternal, how many of them are male
|
SELECT COUNT(*) FROM superhero AS T1 INNER JOIN race AS T2 ON T1.race_id = T2.id INNER JOIN gender AS T3 ON T3.id = T1.gender_id WHERE T1.race_id = 21 AND T1.gender_id = 1
|
[
"Among",
"the",
"superheroes",
"with",
"the",
"race",
"of",
"god",
"/",
"eternal",
",",
"how",
"many",
"of",
"them",
"are",
"male"
] |
[
{
"id": 1,
"type": "table",
"value": "superhero"
},
{
"id": 4,
"type": "column",
"value": "gender_id"
},
{
"id": 5,
"type": "column",
"value": "race_id"
},
{
"id": 0,
"type": "table",
"value": "gender"
},
{
"id": 2,
"type": "table",
"value": "race"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "21"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
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"token_idxs": [
5
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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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{
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{
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{
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
262
|
retail_world
|
bird:train.json:6444
|
What is the homepage link for the company that supplies the product "Thringer Rostbratwurst"?
|
SELECT T2.HomePage FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.ProductName = 'Thringer Rostbratwurst'
|
[
"What",
"is",
"the",
"homepage",
"link",
"for",
"the",
"company",
"that",
"supplies",
"the",
"product",
"\"",
"Thringer",
"Rostbratwurst",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Thringer Rostbratwurst"
},
{
"id": 3,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 0,
"type": "column",
"value": "homepage"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13,
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
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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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
263
|
talkingdata
|
bird:train.json:1121
|
Which group does age 24 belong to?
|
SELECT `group` FROM gender_age WHERE age = '24'
|
[
"Which",
"group",
"does",
"age",
"24",
"belong",
"to",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "gender_age"
},
{
"id": 1,
"type": "column",
"value": "group"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "24"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
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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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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O"
] |
264
|
regional_sales
|
bird:train.json:2656
|
Among the products sold in Maricopa County, which was the least sold?
|
SELECT T1.`Product Name` FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Store Locations` AS T3 ON T3.StoreID = T2._StoreID WHERE T3.County = 'Maricopa County' ORDER BY T2.`Order Quantity` ASC LIMIT 1
|
[
"Among",
"the",
"products",
"sold",
"in",
"Maricopa",
"County",
",",
"which",
"was",
"the",
"least",
"sold",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "Store Locations"
},
{
"id": 3,
"type": "value",
"value": "Maricopa County"
},
{
"id": 4,
"type": "column",
"value": "Order Quantity"
},
{
"id": 0,
"type": "column",
"value": "Product Name"
},
{
"id": 6,
"type": "table",
"value": "Sales Orders"
},
{
"id": 9,
"type": "column",
"value": "_productid"
},
{
"id": 10,
"type": "column",
"value": "productid"
},
{
"id": 5,
"type": "table",
"value": "products"
},
{
"id": 8,
"type": "column",
"value": "_storeid"
},
{
"id": 7,
"type": "column",
"value": "storeid"
},
{
"id": 2,
"type": "column",
"value": "county"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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6
]
},
{
"entity_id": 3,
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5
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},
{
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},
{
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2
]
},
{
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},
{
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},
{
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{
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},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
265
|
video_games
|
bird:train.json:3478
|
What are the genres of games published by the publisher with an ID of 464?
|
SELECT DISTINCT T2.genre_name FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id INNER JOIN game_publisher AS T3 ON T1.id = T3.game_id WHERE T3.publisher_id = 464
|
[
"What",
"are",
"the",
"genres",
"of",
"games",
"published",
"by",
"the",
"publisher",
"with",
"an",
"ID",
"of",
"464",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "game_publisher"
},
{
"id": 2,
"type": "column",
"value": "publisher_id"
},
{
"id": 0,
"type": "column",
"value": "genre_name"
},
{
"id": 8,
"type": "column",
"value": "genre_id"
},
{
"id": 7,
"type": "column",
"value": "game_id"
},
{
"id": 5,
"type": "table",
"value": "genre"
},
{
"id": 4,
"type": "table",
"value": "game"
},
{
"id": 3,
"type": "value",
"value": "464"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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4
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{
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6
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9
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},
{
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14
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},
{
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5
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},
{
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3
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},
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},
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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-TABLE",
"B-COLUMN",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
266
|
hockey
|
bird:train.json:7664
|
Please list the awards won by coaches who taught the NHL League and have already died.
|
SELECT DISTINCT T2.award FROM Master AS T1 INNER JOIN AwardsCoaches AS T2 ON T1.coachID = T2.coachID WHERE T1.deathYear IS NOT NULL AND T2.lgID = 'NHL'
|
[
"Please",
"list",
"the",
"awards",
"won",
"by",
"coaches",
"who",
"taught",
"the",
"NHL",
"League",
"and",
"have",
"already",
"died",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "awardscoaches"
},
{
"id": 4,
"type": "column",
"value": "deathyear"
},
{
"id": 3,
"type": "column",
"value": "coachid"
},
{
"id": 1,
"type": "table",
"value": "master"
},
{
"id": 0,
"type": "column",
"value": "award"
},
{
"id": 5,
"type": "column",
"value": "lgid"
},
{
"id": 6,
"type": "value",
"value": "NHL"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
267
|
customers_and_invoices
|
spider:train_spider.json:1622
|
What are teh names of the different products, as well as the number of customers who have ordered each product.
|
SELECT T2.product_name , count(*) FROM Order_items AS T1 JOIN Products AS T2 ON T1.product_id = T2.product_id JOIN Orders AS T3 ON T3.order_id = T1.order_id GROUP BY T2.product_name
|
[
"What",
"are",
"teh",
"names",
"of",
"the",
"different",
"products",
",",
"as",
"well",
"as",
"the",
"number",
"of",
"customers",
"who",
"have",
"ordered",
"each",
"product",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "product_name"
},
{
"id": 2,
"type": "table",
"value": "order_items"
},
{
"id": 5,
"type": "column",
"value": "product_id"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 4,
"type": "column",
"value": "order_id"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
18
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O"
] |
268
|
workshop_paper
|
spider:train_spider.json:5824
|
What is the author of the submission with the highest score?
|
SELECT Author FROM submission ORDER BY Scores DESC LIMIT 1
|
[
"What",
"is",
"the",
"author",
"of",
"the",
"submission",
"with",
"the",
"highest",
"score",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "submission"
},
{
"id": 1,
"type": "column",
"value": "author"
},
{
"id": 2,
"type": "column",
"value": "scores"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
269
|
works_cycles
|
bird:train.json:7071
|
Please give the personal information of the married employee who has the highest pay rate.
|
SELECT T2.Demographics FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN EmployeePayHistory AS T3 ON T2.BusinessEntityID = T3.BusinessEntityID WHERE T1.MaritalStatus = 'M' ORDER BY T3.Rate DESC LIMIT 1
|
[
"Please",
"give",
"the",
"personal",
"information",
"of",
"the",
"married",
"employee",
"who",
"has",
"the",
"highest",
"pay",
"rate",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "employeepayhistory"
},
{
"id": 7,
"type": "column",
"value": "businessentityid"
},
{
"id": 2,
"type": "column",
"value": "maritalstatus"
},
{
"id": 0,
"type": "column",
"value": "demographics"
},
{
"id": 5,
"type": "table",
"value": "employee"
},
{
"id": 6,
"type": "table",
"value": "person"
},
{
"id": 4,
"type": "column",
"value": "rate"
},
{
"id": 3,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
270
|
thrombosis_prediction
|
bird:dev.json:1311
|
How many patients with severe thrombosis have a normal prothrombin time?
|
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID INNER JOIN Examination AS T3 ON T1.ID = T3.ID WHERE T2.PT < 14 AND T3.Thrombosis < 3 AND T3.Thrombosis > 0
|
[
"How",
"many",
"patients",
"with",
"severe",
"thrombosis",
"have",
"a",
"normal",
"prothrombin",
"time",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "examination"
},
{
"id": 3,
"type": "table",
"value": "laboratory"
},
{
"id": 6,
"type": "column",
"value": "thrombosis"
},
{
"id": 2,
"type": "table",
"value": "patient"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "column",
"value": "pt"
},
{
"id": 5,
"type": "value",
"value": "14"
},
{
"id": 7,
"type": "value",
"value": "3"
},
{
"id": 8,
"type": "value",
"value": "0"
}
] |
[
{
"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": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
271
|
advertising_agencies
|
bird:test.json:2134
|
What is the staff id of the staff who attended the least meetings but attended some meeting?
|
SELECT staff_id , count(*) FROM Staff_in_meetings GROUP BY staff_id ORDER BY count(*) ASC LIMIT 1;
|
[
"What",
"is",
"the",
"staff",
"i",
"d",
"of",
"the",
"staff",
"who",
"attended",
"the",
"least",
"meetings",
"but",
"attended",
"some",
"meeting",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "staff_in_meetings"
},
{
"id": 1,
"type": "column",
"value": "staff_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12,
13
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
272
|
authors
|
bird:train.json:3526
|
What is the short name and full name of conference uses the homepage "http://www.informatik.uni-trier.de/~ley/db/conf/ices/index.html"?
|
SELECT ShortName, FullName FROM Conference WHERE HomePage = 'http://www.informatik.uni-trier.de/~ley/db/conf/ices/index.html'
|
[
"What",
"is",
"the",
"short",
"name",
"and",
"full",
"name",
"of",
"conference",
"uses",
"the",
"homepage",
"\"",
"http://www.informatik.uni-trier.de/~ley/db/conf/ices/index.html",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "http://www.informatik.uni-trier.de/~ley/db/conf/ices/index.html"
},
{
"id": 0,
"type": "table",
"value": "conference"
},
{
"id": 1,
"type": "column",
"value": "shortname"
},
{
"id": 2,
"type": "column",
"value": "fullname"
},
{
"id": 3,
"type": "column",
"value": "homepage"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
273
|
tracking_orders
|
spider:train_spider.json:6929
|
What is the id of the order which has the most items?
|
SELECT T1.order_id FROM orders AS T1 JOIN order_items AS T2 ON T1.order_id = T2.order_id GROUP BY T1.order_id ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"the",
"order",
"which",
"has",
"the",
"most",
"items",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "order_items"
},
{
"id": 0,
"type": "column",
"value": "order_id"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
274
|
soccer_2016
|
bird:train.json:1835
|
When did Chennai Super Kings play its first match?
|
SELECT Match_Date FROM `Match` WHERE team_1 = ( SELECT Team_Id FROM Team WHERE Team_Name = 'Chennai Super Kings' ) OR Team_2 = ( SELECT Team_Id FROM Team WHERE Team_Name = 'Chennai Super Kings' ) ORDER BY Match_Date ASC LIMIT 1
|
[
"When",
"did",
"Chennai",
"Super",
"Kings",
"play",
"its",
"first",
"match",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Chennai Super Kings"
},
{
"id": 1,
"type": "column",
"value": "match_date"
},
{
"id": 6,
"type": "column",
"value": "team_name"
},
{
"id": 5,
"type": "column",
"value": "team_id"
},
{
"id": 2,
"type": "column",
"value": "team_1"
},
{
"id": 3,
"type": "column",
"value": "team_2"
},
{
"id": 0,
"type": "table",
"value": "Match"
},
{
"id": 4,
"type": "table",
"value": "team"
}
] |
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{
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},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
275
|
college_2
|
spider:train_spider.json:1357
|
Count the number of rooms in Lamberton with capacity lower than 50.
|
SELECT count(*) FROM classroom WHERE building = 'Lamberton' AND capacity < 50
|
[
"Count",
"the",
"number",
"of",
"rooms",
"in",
"Lamberton",
"with",
"capacity",
"lower",
"than",
"50",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "classroom"
},
{
"id": 2,
"type": "value",
"value": "Lamberton"
},
{
"id": 1,
"type": "column",
"value": "building"
},
{
"id": 3,
"type": "column",
"value": "capacity"
},
{
"id": 4,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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]
},
{
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8
]
},
{
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},
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
276
|
baseball_1
|
spider:train_spider.json:3646
|
Show me the number of parks the state of NY has.
|
SELECT count(*) FROM park WHERE state = 'NY';
|
[
"Show",
"me",
"the",
"number",
"of",
"parks",
"the",
"state",
"of",
"NY",
"has",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "table",
"value": "park"
},
{
"id": 2,
"type": "value",
"value": "NY"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
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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",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
277
|
toxicology
|
bird:dev.json:322
|
What is the element of toxicology for the atom with the ID of TR000_1?
|
SELECT T.element FROM atom AS T WHERE T.atom_id = 'TR000_1'
|
[
"What",
"is",
"the",
"element",
"of",
"toxicology",
"for",
"the",
"atom",
"with",
"the",
"ID",
"of",
"TR000_1",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "element"
},
{
"id": 2,
"type": "column",
"value": "atom_id"
},
{
"id": 3,
"type": "value",
"value": "TR000_1"
},
{
"id": 0,
"type": "table",
"value": "atom"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
278
|
talkingdata
|
bird:train.json:1042
|
How many female users over the age of 50 are there?
|
SELECT COUNT(gender) FROM gender_age WHERE age > 50 AND gender = 'F'
|
[
"How",
"many",
"female",
"users",
"over",
"the",
"age",
"of",
"50",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "gender_age"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "50"
},
{
"id": 4,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"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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"token_idxs": []
},
{
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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",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O"
] |
279
|
company_office
|
spider:train_spider.json:4582
|
Which headquarter locations are used by more than 2 companies?
|
SELECT Headquarters FROM Companies GROUP BY Headquarters HAVING COUNT(*) > 2
|
[
"Which",
"headquarter",
"locations",
"are",
"used",
"by",
"more",
"than",
"2",
"companies",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "headquarters"
},
{
"id": 0,
"type": "table",
"value": "companies"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
280
|
store_product
|
spider:train_spider.json:4936
|
Find the most prominent max page size among all the products.
|
SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"most",
"prominent",
"max",
"page",
"size",
"among",
"all",
"the",
"products",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "max_page_size"
},
{
"id": 0,
"type": "table",
"value": "product"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"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",
"O",
"O",
"B-TABLE",
"O"
] |
281
|
computer_student
|
bird:train.json:982
|
Which are the courses with the most number of professors? State the course ID and the level of the course.
|
SELECT T1.course_id, T1.courseLevel FROM course AS T1 INNER JOIN taughtBy AS T2 ON T1.course_id = T2.course_id GROUP BY T1.course_id, T1.courseLevel ORDER BY COUNT(T1.course_id) DESC LIMIT 1
|
[
"Which",
"are",
"the",
"courses",
"with",
"the",
"most",
"number",
"of",
"professors",
"?",
"State",
"the",
"course",
"ID",
"and",
"the",
"level",
"of",
"the",
"course",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "courselevel"
},
{
"id": 0,
"type": "column",
"value": "course_id"
},
{
"id": 3,
"type": "table",
"value": "taughtby"
},
{
"id": 2,
"type": "table",
"value": "course"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13,
14
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
20
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
282
|
program_share
|
spider:train_spider.json:3730
|
List all channel names ordered by their rating in percent from big to small.
|
SELECT name FROM channel ORDER BY rating_in_percent DESC
|
[
"List",
"all",
"channel",
"names",
"ordered",
"by",
"their",
"rating",
"in",
"percent",
"from",
"big",
"to",
"small",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "rating_in_percent"
},
{
"id": 0,
"type": "table",
"value": "channel"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
283
|
formula_1
|
spider:train_spider.json:2219
|
What is the average fastest lap speed in race named 'Monaco Grand Prix' in 2008 ?
|
SELECT avg(T2.fastestlapspeed) FROM races AS T1 JOIN results AS T2 ON T1.raceid = T2.raceid WHERE T1.year = 2008 AND T1.name = "Monaco Grand Prix"
|
[
"What",
"is",
"the",
"average",
"fastest",
"lap",
"speed",
"in",
"race",
"named",
"'",
"Monaco",
"Grand",
"Prix",
"'",
"in",
"2008",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "Monaco Grand Prix"
},
{
"id": 2,
"type": "column",
"value": "fastestlapspeed"
},
{
"id": 1,
"type": "table",
"value": "results"
},
{
"id": 3,
"type": "column",
"value": "raceid"
},
{
"id": 0,
"type": "table",
"value": "races"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "2008"
},
{
"id": 6,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
11,
12,
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
284
|
student_club
|
bird:dev.json:1453
|
List the name of events with less than average parking cost.
|
SELECT T1.event_name FROM event AS T1 INNER JOIN budget AS T2 ON T1.event_id = T2.link_to_event INNER JOIN expense AS T3 ON T2.budget_id = T3.link_to_budget WHERE T2.category = 'Parking' AND T3.cost < (SELECT AVG(cost) FROM expense)
|
[
"List",
"the",
"name",
"of",
"events",
"with",
"less",
"than",
"average",
"parking",
"cost",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "link_to_budget"
},
{
"id": 10,
"type": "column",
"value": "link_to_event"
},
{
"id": 0,
"type": "column",
"value": "event_name"
},
{
"id": 4,
"type": "column",
"value": "budget_id"
},
{
"id": 6,
"type": "column",
"value": "category"
},
{
"id": 9,
"type": "column",
"value": "event_id"
},
{
"id": 1,
"type": "table",
"value": "expense"
},
{
"id": 7,
"type": "value",
"value": "Parking"
},
{
"id": 3,
"type": "table",
"value": "budget"
},
{
"id": 2,
"type": "table",
"value": "event"
},
{
"id": 8,
"type": "column",
"value": "cost"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
285
|
hockey
|
bird:train.json:7792
|
For the goalie whose last name is "Young", how many teams did he play in?
|
SELECT COUNT(DISTINCT T1.tmID) FROM Goalies AS T1 INNER JOIN Master AS T2 ON T1.playerID = T2.playerID WHERE T2.lastName = 'Young'
|
[
"For",
"the",
"goalie",
"whose",
"last",
"name",
"is",
"\"",
"Young",
"\"",
",",
"how",
"many",
"teams",
"did",
"he",
"play",
"in",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "goalies"
},
{
"id": 1,
"type": "table",
"value": "master"
},
{
"id": 3,
"type": "value",
"value": "Young"
},
{
"id": 4,
"type": "column",
"value": "tmid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
13,
14
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
286
|
university_rank
|
bird:test.json:1775
|
Which conference has the least number of total enrollment?
|
SELECT home_conference FROM University GROUP BY home_conference ORDER BY sum(enrollment) LIMIT 1
|
[
"Which",
"conference",
"has",
"the",
"least",
"number",
"of",
"total",
"enrollment",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "home_conference"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 2,
"type": "column",
"value": "enrollment"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
287
|
art_1
|
bird:test.json:1305
|
Which artists have the most paintings in oil?
|
SELECT T1.lname , T1.fname FROM artists AS T1 JOIN paintings AS T2 ON T1.artistID = T2.painterID WHERE T2.medium = "oil" GROUP BY T2.painterID ORDER BY count(*) DESC LIMIT 3
|
[
"Which",
"artists",
"have",
"the",
"most",
"paintings",
"in",
"oil",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "painterid"
},
{
"id": 4,
"type": "table",
"value": "paintings"
},
{
"id": 7,
"type": "column",
"value": "artistid"
},
{
"id": 3,
"type": "table",
"value": "artists"
},
{
"id": 5,
"type": "column",
"value": "medium"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 2,
"type": "column",
"value": "fname"
},
{
"id": 6,
"type": "column",
"value": "oil"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O"
] |
288
|
retail_complains
|
bird:train.json:377
|
What is the oldest age of male clients?
|
SELECT MAX(age) FROM client WHERE sex = 'Male'
|
[
"What",
"is",
"the",
"oldest",
"age",
"of",
"male",
"clients",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 2,
"type": "value",
"value": "Male"
},
{
"id": 1,
"type": "column",
"value": "sex"
},
{
"id": 3,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
289
|
retail_complains
|
bird:train.json:357
|
Which product received the most complaints from elder clients?
|
SELECT T2.Product FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.age > 65 ORDER BY T1.client_id DESC LIMIT 1
|
[
"Which",
"product",
"received",
"the",
"most",
"complaints",
"from",
"elder",
"clients",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "client_id"
},
{
"id": 0,
"type": "column",
"value": "product"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 2,
"type": "table",
"value": "events"
},
{
"id": 3,
"type": "column",
"value": "age"
},
{
"id": 4,
"type": "value",
"value": "65"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"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": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
290
|
planet_1
|
bird:test.json:1889
|
List all Planets' names and coordinates in alphabetical order of name.
|
SELECT Name , Coordinates FROM Planet ORDER BY Name
|
[
"List",
"all",
"Planets",
"'",
"names",
"and",
"coordinates",
"in",
"alphabetical",
"order",
"of",
"name",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "coordinates"
},
{
"id": 0,
"type": "table",
"value": "planet"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
291
|
car_racing
|
bird:test.json:1623
|
List each make with the number of drivers with that make.
|
SELECT Make , COUNT(*) FROM driver GROUP BY Make
|
[
"List",
"each",
"make",
"with",
"the",
"number",
"of",
"drivers",
"with",
"that",
"make",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 1,
"type": "column",
"value": "make"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
292
|
movie_1
|
spider:train_spider.json:2473
|
What is the reviewer name, film title, movie rating, and rating date for every movie ordered by reviewer name, movie title, then finally rating?
|
SELECT T3.name , T2.title , T1.stars , T1.ratingDate FROM Rating AS T1 JOIN Movie AS T2 ON T1.mID = T2.mID JOIN Reviewer AS T3 ON T1.rID = T3.rID ORDER BY T3.name , T2.title , T1.stars
|
[
"What",
"is",
"the",
"reviewer",
"name",
",",
"film",
"title",
",",
"movie",
"rating",
",",
"and",
"rating",
"date",
" ",
"for",
"every",
"movie",
"ordered",
"by",
"reviewer",
"name",
",",
"movie",
"title",
",",
"then",
"finally",
"rating",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "ratingdate"
},
{
"id": 4,
"type": "table",
"value": "reviewer"
},
{
"id": 5,
"type": "table",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "stars"
},
{
"id": 6,
"type": "table",
"value": "movie"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "rid"
},
{
"id": 8,
"type": "column",
"value": "mid"
}
] |
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[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
293
|
e_learning
|
spider:train_spider.json:3843
|
Which students not enrolled in any course? Find their personal names.
|
SELECT personal_name FROM Students EXCEPT SELECT T1.personal_name FROM Students AS T1 JOIN Student_Course_Enrolment AS T2 ON T1.student_id = T2.student_id
|
[
"Which",
"students",
"not",
"enrolled",
"in",
"any",
"course",
"?",
"Find",
"their",
"personal",
"names",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "student_course_enrolment"
},
{
"id": 1,
"type": "column",
"value": "personal_name"
},
{
"id": 3,
"type": "column",
"value": "student_id"
},
{
"id": 0,
"type": "table",
"value": "students"
}
] |
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3,
4
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}
] |
[
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
294
|
image_and_language
|
bird:train.json:7539
|
On image no. 20, identify the attribute ID that is composed of the highest number of objects.
|
SELECT ATT_CLASS_ID FROM IMG_OBJ_ATT WHERE IMG_ID = 20 GROUP BY ATT_CLASS_ID ORDER BY COUNT(ATT_CLASS_ID) DESC LIMIT 1
|
[
"On",
"image",
"no",
".",
"20",
",",
"identify",
"the",
"attribute",
"ID",
"that",
"is",
"composed",
"of",
"the",
"highest",
"number",
"of",
"objects",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "att_class_id"
},
{
"id": 0,
"type": "table",
"value": "img_obj_att"
},
{
"id": 2,
"type": "column",
"value": "img_id"
},
{
"id": 3,
"type": "value",
"value": "20"
}
] |
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},
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
295
|
tracking_share_transactions
|
spider:train_spider.json:5880
|
Show the ids of the investors who have at least two transactions.
|
SELECT T2.investor_id FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id GROUP BY T2.investor_id HAVING COUNT(*) >= 2
|
[
"Show",
"the",
"ids",
"of",
"the",
"investors",
"who",
"have",
"at",
"least",
"two",
"transactions",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "transactions"
},
{
"id": 0,
"type": "column",
"value": "investor_id"
},
{
"id": 1,
"type": "table",
"value": "investors"
},
{
"id": 3,
"type": "value",
"value": "2"
}
] |
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
296
|
student_loan
|
bird:train.json:4371
|
Among the students that have been absent from school for more than 5 months, how many of them are male?
|
SELECT COUNT(T1.name) FROM longest_absense_from_school AS T1 INNER JOIN male AS T2 ON T1.`name` = T2.`name` WHERE T1.`month` >= 5
|
[
"Among",
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"students",
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"school",
"for",
"more",
"than",
"5",
"months",
",",
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"of",
"them",
"are",
"male",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 2,
"type": "column",
"value": "month"
},
{
"id": 1,
"type": "table",
"value": "male"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "5"
}
] |
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"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
297
|
formula_1
|
bird:dev.json:1002
|
As of the present, what is the full name of the youngest racer? Indicate her nationality and the name of the race to which he/she first joined.
|
SELECT T1.forename, T1.surname, T1.nationality, T3.name FROM drivers AS T1 INNER JOIN driverStandings AS T2 on T1.driverId = T2.driverId INNER JOIN races AS T3 on T2.raceId = T3.raceId ORDER BY JULIANDAY(T1.dob) DESC LIMIT 1
|
[
"As",
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"the",
"present",
",",
"what",
"is",
"the",
"full",
"name",
"of",
"the",
"youngest",
"racer",
"?",
"Indicate",
"her",
"nationality",
"and",
"the",
"name",
"of",
"the",
"race",
"to",
"which",
"he",
"/",
"she",
"first",
"joined",
"."
] |
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{
"id": 6,
"type": "table",
"value": "driverstandings"
},
{
"id": 2,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "column",
"value": "forename"
},
{
"id": 9,
"type": "column",
"value": "driverid"
},
{
"id": 1,
"type": "column",
"value": "surname"
},
{
"id": 5,
"type": "table",
"value": "drivers"
},
{
"id": 7,
"type": "column",
"value": "raceid"
},
{
"id": 4,
"type": "table",
"value": "races"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "dob"
}
] |
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
298
|
world_development_indicators
|
bird:train.json:2234
|
What's the long name of the country that got 3000000 on the indicator Arms exports in 1960?
|
SELECT T1.LongName FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.IndicatorName = 'Arms exports (SIPRI trend indicator values)' AND T2.Year = 1960 AND T2.Value = 3000000
|
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"got",
"3000000",
"on",
"the",
"indicator",
"Arms",
"exports",
"in",
"1960",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Arms exports (SIPRI trend indicator values)"
},
{
"id": 4,
"type": "column",
"value": "indicatorname"
},
{
"id": 3,
"type": "column",
"value": "countrycode"
},
{
"id": 2,
"type": "table",
"value": "indicators"
},
{
"id": 0,
"type": "column",
"value": "longname"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 9,
"type": "value",
"value": "3000000"
},
{
"id": 8,
"type": "column",
"value": "value"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "1960"
}
] |
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[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
299
|
match_season
|
spider:train_spider.json:1054
|
Show the country name and capital of all countries.
|
SELECT Country_name , Capital FROM country
|
[
"Show",
"the",
"country",
"name",
"and",
"capital",
"of",
"all",
"countries",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "country_name"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "capital"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
300
|
retail_world
|
bird:train.json:6662
|
Among the employees who handled orders to Brazil, who has the highest salary and calculate the average salary of them.
|
SELECT T1.FirstName, T1.LastName, AVG(T1.Salary) FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID WHERE T2.ShipCountry = 'Brazil' GROUP BY T1.FirstName, T1.LastName ORDER BY SUM(T1.Salary) DESC LIMIT 1
|
[
"Among",
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"employees",
"who",
"handled",
"orders",
"to",
"Brazil",
",",
"who",
"has",
"the",
"highest",
"salary",
"and",
"calculate",
"the",
"average",
"salary",
"of",
"them",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "shipcountry"
},
{
"id": 7,
"type": "column",
"value": "employeeid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "table",
"value": "orders"
},
{
"id": 5,
"type": "value",
"value": "Brazil"
},
{
"id": 6,
"type": "column",
"value": "salary"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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2
]
},
{
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5
]
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{
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{
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7
]
},
{
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13
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{
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{
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{
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"token_idxs": []
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{
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
301
|
college_2
|
spider:train_spider.json:1392
|
Find the number of rooms with more than 50 capacity for each building.
|
SELECT count(*) , building FROM classroom WHERE capacity > 50 GROUP BY building
|
[
"Find",
"the",
"number",
"of",
"rooms",
"with",
"more",
"than",
"50",
"capacity",
"for",
"each",
"building",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "classroom"
},
{
"id": 1,
"type": "column",
"value": "building"
},
{
"id": 2,
"type": "column",
"value": "capacity"
},
{
"id": 3,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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12
]
},
{
"entity_id": 2,
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9
]
},
{
"entity_id": 3,
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8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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,
"token_idxs": []
},
{
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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",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
302
|
art_1
|
bird:test.json:1255
|
What are the distinct titles of every painting that has a greater height than some painting on canvas?
|
SELECT DISTINCT title FROM paintings WHERE height_mm > (SELECT min(height_mm) FROM paintings WHERE mediumOn = "canvas")
|
[
"What",
"are",
"the",
"distinct",
"titles",
"of",
"every",
"painting",
"that",
"has",
"a",
"greater",
"height",
"than",
"some",
"painting",
"on",
"canvas",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 2,
"type": "column",
"value": "height_mm"
},
{
"id": 3,
"type": "column",
"value": "mediumon"
},
{
"id": 4,
"type": "column",
"value": "canvas"
},
{
"id": 1,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
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4
]
},
{
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12
]
},
{
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},
{
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17
]
},
{
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O"
] |
303
|
menu
|
bird:train.json:5576
|
How much space does page 1 of the menu "Zentral Theater Terrace" cover?
|
SELECT T2.full_height * T2.full_width FROM Menu AS T1 INNER JOIN MenuPage AS T2 ON T1.id = T2.menu_id WHERE T1.name = 'Zentral Theater Terrace' AND T2.page_number = 1
|
[
"How",
"much",
"space",
"does",
"page",
"1",
"of",
"the",
"menu",
"\"",
"Zentral",
"Theater",
"Terrace",
"\"",
"cover",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Zentral Theater Terrace"
},
{
"id": 2,
"type": "column",
"value": "full_height"
},
{
"id": 8,
"type": "column",
"value": "page_number"
},
{
"id": 3,
"type": "column",
"value": "full_width"
},
{
"id": 1,
"type": "table",
"value": "menupage"
},
{
"id": 5,
"type": "column",
"value": "menu_id"
},
{
"id": 0,
"type": "table",
"value": "menu"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
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8
]
},
{
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4
]
},
{
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},
{
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
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10,
11,
12
]
},
{
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},
{
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5
]
},
{
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},
{
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},
{
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},
{
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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",
"O",
"B-TABLE",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
304
|
aan_1
|
bird:test.json:997
|
What is the venue and year with the most number of publications?
|
SELECT venue , YEAR FROM paper GROUP BY venue , YEAR ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"venue",
"and",
"year",
"with",
"the",
"most",
"number",
"of",
"publications",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paper"
},
{
"id": 1,
"type": "column",
"value": "venue"
},
{
"id": 2,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 12,
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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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
305
|
retail_world
|
bird:train.json:6472
|
What is the contact title for the person who supplied a product that is 10 boxes x 12 pieces.
|
SELECT T2.ContactTitle FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.QuantityPerUnit = '10 boxes x 12 pieces'
|
[
"What",
"is",
"the",
"contact",
"title",
"for",
"the",
"person",
"who",
"supplied",
"a",
"product",
"that",
"is",
"10",
"boxes",
"x",
"12",
"pieces",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "10 boxes x 12 pieces"
},
{
"id": 3,
"type": "column",
"value": "quantityperunit"
},
{
"id": 0,
"type": "column",
"value": "contacttitle"
},
{
"id": 5,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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11
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14,
15,
16,
17,
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
306
|
books
|
bird:train.json:5945
|
What is the full name of the customer who owns the "aalleburtonkc@yellowbook.com" e-mail address?
|
SELECT first_name, last_name FROM customer WHERE email = 'aalleburtonkc@yellowbook.com'
|
[
"What",
"is",
"the",
"full",
"name",
"of",
"the",
"customer",
"who",
"owns",
"the",
"\"",
"aalleburtonkc@yellowbook.com",
"\"",
"e",
"-",
"mail",
"address",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "aalleburtonkc@yellowbook.com"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 3,
"type": "column",
"value": "email"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
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14,
15,
16
]
},
{
"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,
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
307
|
thrombosis_prediction
|
bird:dev.json:1187
|
How many patients who were examined between 1987/7/6 and 1996/1/31 had a GPT level greater than 30 and an ALB level less than 4? List them by their ID.
|
SELECT DISTINCT ID FROM Laboratory WHERE Date BETWEEN '1987-07-06' AND '1996-01-31' AND GPT > 30 AND ALB < 4
|
[
"How",
"many",
"patients",
"who",
"were",
"examined",
"between",
"1987/7/6",
"and",
"1996/1/31",
"had",
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"and",
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"ALB",
"level",
"less",
"than",
"4",
"?",
"List",
"them",
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"their",
"ID",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "laboratory"
},
{
"id": 3,
"type": "value",
"value": "1987-07-06"
},
{
"id": 4,
"type": "value",
"value": "1996-01-31"
},
{
"id": 2,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "column",
"value": "gpt"
},
{
"id": 7,
"type": "column",
"value": "alb"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "30"
},
{
"id": 8,
"type": "value",
"value": "4"
}
] |
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"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
308
|
retail_world
|
bird:train.json:6599
|
Which of Cooperativa de Quesos 'Las Cabras' products have a unit price greater than 20?
|
SELECT T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName LIKE 'Cooperativa de Quesos%' AND T1.UnitPrice > 20
|
[
"Which",
"of",
"Cooperativa",
"de",
"Quesos",
"'",
"Las",
"Cabras",
"'",
"products",
"have",
"a",
"unit",
"price",
"greater",
"than",
"20",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Cooperativa de Quesos%"
},
{
"id": 0,
"type": "column",
"value": "productname"
},
{
"id": 4,
"type": "column",
"value": "companyname"
},
{
"id": 3,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 6,
"type": "column",
"value": "unitprice"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"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": [
2,
3,
4
]
},
{
"entity_id": 6,
"token_idxs": [
12,
13
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
309
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4165
|
How many document types are there?
|
SELECT count(*) FROM Ref_document_types
|
[
"How",
"many",
"document",
"types",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "ref_document_types"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
310
|
movie_3
|
bird:train.json:9213
|
Write down any five film names under the documentary category.
|
SELECT T1.title FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T2.category_id = T3.category_id WHERE T3.name = 'Documentary' LIMIT 5
|
[
"Write",
"down",
"any",
"five",
"film",
"names",
"under",
"the",
"documentary",
"category",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "film_category"
},
{
"id": 3,
"type": "value",
"value": "Documentary"
},
{
"id": 6,
"type": "column",
"value": "category_id"
},
{
"id": 1,
"type": "table",
"value": "category"
},
{
"id": 7,
"type": "column",
"value": "film_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
311
|
regional_sales
|
bird:train.json:2718
|
How many online orders were shipped during the month of June 2018?
|
SELECT SUM(IIF(ShipDate LIKE '6/%/18' AND `Sales Channel` = 'Online', 1, 0)) FROM `Sales Orders`
|
[
"How",
"many",
"online",
"orders",
"were",
"shipped",
"during",
"the",
"month",
"of",
"June",
"2018",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "Sales Channel"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 3,
"type": "column",
"value": "shipdate"
},
{
"id": 4,
"type": "value",
"value": "6/%/18"
},
{
"id": 6,
"type": "value",
"value": "Online"
},
{
"id": 1,
"type": "value",
"value": "1"
},
{
"id": 2,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
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-VALUE",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
312
|
customers_and_invoices
|
spider:train_spider.json:1597
|
Show all product colors.
|
SELECT DISTINCT product_color FROM Products
|
[
"Show",
"all",
"product",
"colors",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "product_color"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
313
|
law_episode
|
bird:train.json:1256
|
Please list the titles of all the episodes in which Park Dietz was credited.
|
SELECT T1.title FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T2.credited = 'true' AND T3.name = 'Park Dietz'
|
[
"Please",
"list",
"the",
"titles",
"of",
"all",
"the",
"episodes",
"in",
"which",
"Park",
"Dietz",
"was",
"credited",
"."
] |
[
{
"id": 8,
"type": "value",
"value": "Park Dietz"
},
{
"id": 9,
"type": "column",
"value": "episode_id"
},
{
"id": 4,
"type": "column",
"value": "person_id"
},
{
"id": 5,
"type": "column",
"value": "credited"
},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "table",
"value": "credit"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "value",
"value": "true"
},
{
"id": 7,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
10,
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
314
|
regional_sales
|
bird:train.json:2640
|
Please list the names of customers who have total orders of over 3 in 2018.
|
SELECT DISTINCT IIF(COUNT(T2.CustomerID) > 3, T2.`Customer Names`, NULL) FROM `Sales Orders` AS T1 INNER JOIN Customers AS T2 ON T2.CustomerID = T1._CustomerID WHERE T1.OrderDate LIKE '%/%/18' GROUP BY T1._CustomerID HAVING COUNT(T2.CustomerID)
|
[
"Please",
"list",
"the",
"names",
"of",
"customers",
"who",
"have",
"total",
"orders",
"of",
"over",
"3",
"in",
"2018",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "Customer Names"
},
{
"id": 1,
"type": "table",
"value": "Sales Orders"
},
{
"id": 0,
"type": "column",
"value": "_customerid"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "column",
"value": "orderdate"
},
{
"id": 4,
"type": "value",
"value": "%/%/18"
},
{
"id": 7,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
315
|
simpson_episodes
|
bird:train.json:4318
|
Calculate the total votes of episodes that Adam Kuhlman had involved.
|
SELECT SUM(T1.votes) FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T2.person = 'Adam Kuhlman';
|
[
"Calculate",
"the",
"total",
"votes",
"of",
"episodes",
"that",
"Adam",
"Kuhlman",
"had",
"involved",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Adam Kuhlman"
},
{
"id": 5,
"type": "column",
"value": "episode_id"
},
{
"id": 0,
"type": "table",
"value": "episode"
},
{
"id": 1,
"type": "table",
"value": "credit"
},
{
"id": 2,
"type": "column",
"value": "person"
},
{
"id": 4,
"type": "column",
"value": "votes"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"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-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
316
|
regional_sales
|
bird:train.json:2652
|
How many orders made by Rochester Ltd?
|
SELECT SUM(CASE WHEN T1.`Customer Names` = 'Rochester Ltd' THEN 1 ELSE 0 END) FROM Customers AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._CustomerID = T1.CustomerID
|
[
"How",
"many",
"orders",
"made",
"by",
"Rochester",
"Ltd",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "Customer Names"
},
{
"id": 7,
"type": "value",
"value": "Rochester Ltd"
},
{
"id": 1,
"type": "table",
"value": "Sales Orders"
},
{
"id": 2,
"type": "column",
"value": "_customerid"
},
{
"id": 3,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1,
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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
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