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13,270
|
music_platform_2
|
bird:train.json:7929
|
Find the author, rating and review creation date of review for podcast title 'In The Thick'.
|
SELECT T2.author_id, T2.rating, T2.created_at FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T1.title = 'In The Thick' GROUP BY T2.author_id, T2.rating, T2.created_at
|
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"'",
"."
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{
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"value": "created_at"
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{
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"value": "podcast_id"
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{
"id": 5,
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"value": "title"
}
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"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
13,271
|
gas_company
|
spider:train_spider.json:2020
|
What are the headquarters that have both a company in the banking and 'oil and gas' industries?
|
SELECT headquarters FROM company WHERE main_industry = 'Banking' INTERSECT SELECT headquarters FROM company WHERE main_industry = 'Oil and gas'
|
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{
"id": 2,
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{
"id": 1,
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"value": "Oil and gas"
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{
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"type": "table",
"value": "company"
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{
"id": 3,
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"value": "Banking"
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"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O"
] |
13,272
|
works_cycles
|
bird:train.json:7166
|
What is the number of State Province of France that doesn't have a State Province Code?
|
SELECT T1.CountryRegionCode FROM StateProvince AS T1 INNER JOIN CountryRegion AS T2 ON T1.CountryRegionCode = T2.CountryRegionCode WHERE T2.Name = 'France' AND T1.IsOnlyStateProvinceFlag = 1
|
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"France",
"that",
"does",
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"have",
"a",
"State",
"Province",
"Code",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "isonlystateprovinceflag"
},
{
"id": 0,
"type": "column",
"value": "countryregioncode"
},
{
"id": 1,
"type": "table",
"value": "stateprovince"
},
{
"id": 2,
"type": "table",
"value": "countryregion"
},
{
"id": 4,
"type": "value",
"value": "France"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
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"token_idxs": []
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"token_idxs": []
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}
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"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
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"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
13,273
|
school_finance
|
spider:train_spider.json:1907
|
Find the names of schools that have more than one donator with donation amount above 8.5.
|
SELECT T2.School_name FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T1.amount > 8.5 GROUP BY T1.school_id HAVING count(*) > 1
|
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"."
] |
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{
"id": 1,
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"value": "school_name"
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{
"id": 0,
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"value": "school_id"
},
{
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"type": "table",
"value": "endowment"
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{
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"type": "table",
"value": "school"
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{
"id": 4,
"type": "column",
"value": "amount"
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{
"id": 5,
"type": "value",
"value": "8.5"
},
{
"id": 6,
"type": "value",
"value": "1"
}
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{
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"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
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"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,274
|
airline
|
bird:train.json:5867
|
What is the name of the airline that flew the most flights to Chicago Midway International?
|
SELECT T3.Description FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.DEST INNER JOIN `Air Carriers` AS T3 ON T2.OP_CARRIER_AIRLINE_ID = T3.Code WHERE T1.Description = 'Chicago, IL: Chicago Midway International' AND T2.DEST = 'MDW' GROUP BY T3.Description ORDER BY COUNT(T3.Description) DESC LIMIT 1
|
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"to",
"Chicago",
"Midway",
"International",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Chicago, IL: Chicago Midway International"
},
{
"id": 4,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 1,
"type": "table",
"value": "Air Carriers"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "airports"
},
{
"id": 3,
"type": "table",
"value": "airlines"
},
{
"id": 5,
"type": "column",
"value": "code"
},
{
"id": 7,
"type": "column",
"value": "dest"
},
{
"id": 8,
"type": "value",
"value": "MDW"
}
] |
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"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-VALUE",
"B-VALUE",
"O"
] |
13,275
|
legislator
|
bird:train.json:4761
|
What type of political party Sherrod Brown has in 2005?
|
SELECT T1.party FROM `current-terms` AS T1 INNER JOIN current AS T2 ON T2.bioguide_id = T1.bioguide WHERE T2.first_name = 'Sherrod' AND T2.last_name = 'Brown' AND T1.start LIKE '%2005%'
|
[
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"political",
"party",
"Sherrod",
"Brown",
"has",
"in",
"2005",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "current-terms"
},
{
"id": 3,
"type": "column",
"value": "bioguide_id"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "column",
"value": "bioguide"
},
{
"id": 2,
"type": "table",
"value": "current"
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{
"id": 6,
"type": "value",
"value": "Sherrod"
},
{
"id": 10,
"type": "value",
"value": "%2005%"
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{
"id": 0,
"type": "column",
"value": "party"
},
{
"id": 8,
"type": "value",
"value": "Brown"
},
{
"id": 9,
"type": "column",
"value": "start"
}
] |
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"token_idxs": []
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{
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"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
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[
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"O",
"B-COLUMN",
"B-VALUE",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
13,276
|
cs_semester
|
bird:train.json:882
|
State the name of research postgraduate student among Professor Zhihua Zhou's research assistants.
|
SELECT T3.f_name, T3.l_name FROM prof AS T1 INNER JOIN RA AS T2 ON T1.prof_id = T2.prof_id INNER JOIN student AS T3 ON T2.student_id = T3.student_id WHERE T1.first_name = 'Zhihua' AND T3.type = 'RPG' AND T1.last_name = 'Zhou'
|
[
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"student",
"among",
"Professor",
"Zhihua",
"Zhou",
"'s",
"research",
"assistants",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "student_id"
},
{
"id": 6,
"type": "column",
"value": "first_name"
},
{
"id": 10,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 12,
"type": "column",
"value": "prof_id"
},
{
"id": 0,
"type": "column",
"value": "f_name"
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{
"id": 1,
"type": "column",
"value": "l_name"
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{
"id": 7,
"type": "value",
"value": "Zhihua"
},
{
"id": 3,
"type": "table",
"value": "prof"
},
{
"id": 8,
"type": "column",
"value": "type"
},
{
"id": 11,
"type": "value",
"value": "Zhou"
},
{
"id": 9,
"type": "value",
"value": "RPG"
},
{
"id": 4,
"type": "table",
"value": "ra"
}
] |
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{
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"token_idxs": []
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{
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}
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[
"O",
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"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
13,277
|
sakila_1
|
spider:train_spider.json:2931
|
Give the districts which have two or more addresses.
|
SELECT district FROM address GROUP BY district HAVING count(*) >= 2
|
[
"Give",
"the",
"districts",
"which",
"have",
"two",
"or",
"more",
"addresses",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "district"
},
{
"id": 0,
"type": "table",
"value": "address"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,278
|
cre_Doc_and_collections
|
bird:test.json:707
|
List all owner of documents that is related to documents owned by Braeden.
|
SELECT DISTINCT OWNER FROM Document_Subset_Members AS T1 JOIN Document_Objects AS T2 ON T1.Related_Document_Object_ID = T2.Document_Object_ID WHERE T2.Owner = 'Braeden';
|
[
"List",
"all",
"owner",
"of",
"documents",
"that",
"is",
"related",
"to",
"documents",
"owned",
"by",
"Braeden",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "related_document_object_id"
},
{
"id": 1,
"type": "table",
"value": "document_subset_members"
},
{
"id": 5,
"type": "column",
"value": "document_object_id"
},
{
"id": 2,
"type": "table",
"value": "document_objects"
},
{
"id": 3,
"type": "value",
"value": "Braeden"
},
{
"id": 0,
"type": "column",
"value": "owner"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
7,
8
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,279
|
movies_4
|
bird:train.json:557
|
Name the horror movies with positive ratings greater than 7.
|
SELECT T1.title FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T3.genre_name = 'Horror' AND T1.vote_average > 7
|
[
"Name",
"the",
"horror",
"movies",
"with",
"positive",
"ratings",
"greater",
"than",
"7",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "movie_genres"
},
{
"id": 7,
"type": "column",
"value": "vote_average"
},
{
"id": 5,
"type": "column",
"value": "genre_name"
},
{
"id": 4,
"type": "column",
"value": "genre_id"
},
{
"id": 9,
"type": "column",
"value": "movie_id"
},
{
"id": 6,
"type": "value",
"value": "Horror"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "genre"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 8,
"type": "value",
"value": "7"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
9
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,280
|
soccer_2016
|
bird:train.json:1960
|
What are the names of the venues in Abu Dhabi?
|
SELECT T1.Venue_Name FROM Venue AS T1 INNER JOIN City AS T2 ON T1.City_Id = T2.City_Id WHERE T2.City_Name = 'Abu Dhabi'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"venues",
"in",
"Abu",
"Dhabi",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "venue_name"
},
{
"id": 3,
"type": "column",
"value": "city_name"
},
{
"id": 4,
"type": "value",
"value": "Abu Dhabi"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 1,
"type": "table",
"value": "venue"
},
{
"id": 2,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O"
] |
13,281
|
csu_1
|
spider:train_spider.json:2369
|
How many degrees were conferred at San Jose State University in 2000?
|
SELECT degrees FROM campuses AS T1 JOIN degrees AS T2 ON t1.id = t2.campus WHERE t1.campus = "San Jose State University" AND t2.year = 2000
|
[
"How",
"many",
"degrees",
"were",
"conferred",
"at",
"San",
"Jose",
"State",
"University",
"in",
"2000",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "San Jose State University"
},
{
"id": 1,
"type": "table",
"value": "campuses"
},
{
"id": 0,
"type": "column",
"value": "degrees"
},
{
"id": 2,
"type": "table",
"value": "degrees"
},
{
"id": 4,
"type": "column",
"value": "campus"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "2000"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"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": [
6,
7,
8,
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,282
|
talkingdata
|
bird:train.json:1207
|
On what date were the most events logged on devices for 40-year-old male users?
|
SELECT T.timestamp FROM ( SELECT T2.timestamp, COUNT(T2.event_id) AS num FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id WHERE T1.gender = 'M' AND T1.age = 40 GROUP BY T2.timestamp ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"On",
"what",
"date",
"were",
"the",
"most",
"events",
"logged",
"on",
"devices",
"for",
"40",
"-",
"year",
"-",
"old",
"male",
"users",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "events_relevant"
},
{
"id": 2,
"type": "table",
"value": "gender_age"
},
{
"id": 0,
"type": "column",
"value": "timestamp"
},
{
"id": 5,
"type": "column",
"value": "device_id"
},
{
"id": 4,
"type": "column",
"value": "event_id"
},
{
"id": 6,
"type": "column",
"value": "gender"
},
{
"id": 1,
"type": "column",
"value": "num"
},
{
"id": 8,
"type": "column",
"value": "age"
},
{
"id": 9,
"type": "value",
"value": "40"
},
{
"id": 7,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,284
|
cre_Theme_park
|
spider:train_spider.json:5897
|
Show the average price range of hotels that have 5 star ratings and allow pets.
|
SELECT avg(price_range) FROM HOTELS WHERE star_rating_code = "5" AND pets_allowed_yn = 1
|
[
"Show",
"the",
"average",
"price",
"range",
"of",
"hotels",
"that",
"have",
"5",
"star",
"ratings",
"and",
"allow",
"pets",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "star_rating_code"
},
{
"id": 4,
"type": "column",
"value": "pets_allowed_yn"
},
{
"id": 1,
"type": "column",
"value": "price_range"
},
{
"id": 0,
"type": "table",
"value": "hotels"
},
{
"id": 3,
"type": "column",
"value": "5"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
13,285
|
match_season
|
spider:train_spider.json:1059
|
What are the different positions for match season?
|
SELECT DISTINCT POSITION FROM match_season
|
[
"What",
"are",
"the",
"different",
"positions",
"for",
"match",
"season",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "match_season"
},
{
"id": 1,
"type": "column",
"value": "position"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
13,286
|
european_football_2
|
bird:dev.json:1057
|
Calculate the average home team goal in the 2010/2011 season in the country of Poland.
|
SELECT CAST(SUM(t2.home_team_goal) AS REAL) / COUNT(t2.id) FROM Country AS t1 INNER JOIN Match AS t2 ON t1.id = t2.country_id WHERE t1.name = 'Poland' AND t2.season = '2010/2011'
|
[
"Calculate",
"the",
"average",
"home",
"team",
"goal",
"in",
"the",
"2010/2011",
"season",
"in",
"the",
"country",
"of",
"Poland",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "home_team_goal"
},
{
"id": 3,
"type": "column",
"value": "country_id"
},
{
"id": 7,
"type": "value",
"value": "2010/2011"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "value",
"value": "Poland"
},
{
"id": 6,
"type": "column",
"value": "season"
},
{
"id": 1,
"type": "table",
"value": "match"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
13,287
|
authors
|
bird:train.json:3630
|
Gives the home page of the conference where the paper "Increasing the Concurrency in Estelle" is presented.
|
SELECT DISTINCT T2.HomePage FROM Paper AS T1 INNER JOIN Conference AS T2 ON T1.ConferenceId = T2.Id WHERE T1.Title = 'Increasing the Concurrency in Estelle'
|
[
"Gives",
"the",
"home",
"page",
"of",
"the",
"conference",
"where",
"the",
"paper",
"\"",
"Increasing",
"the",
"Concurrency",
"in",
"Estelle",
"\"",
"is",
"presented",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Increasing the Concurrency in Estelle"
},
{
"id": 5,
"type": "column",
"value": "conferenceid"
},
{
"id": 2,
"type": "table",
"value": "conference"
},
{
"id": 0,
"type": "column",
"value": "homepage"
},
{
"id": 1,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12,
13,
14,
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
13,288
|
restaurant
|
bird:train.json:1708
|
What is the percentage of restaurants that serve American food in Dublin city?
|
SELECT CAST(SUM(IIF(food_type = 'american food', 1, 0)) AS REAL) * 100 / COUNT(id_restaurant) FROM generalinfo WHERE city = 'dublin'
|
[
"What",
"is",
"the",
"percentage",
"of",
"restaurants",
"that",
"serve",
"American",
"food",
"in",
"Dublin",
"city",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "id_restaurant"
},
{
"id": 8,
"type": "value",
"value": "american food"
},
{
"id": 0,
"type": "table",
"value": "generalinfo"
},
{
"id": 7,
"type": "column",
"value": "food_type"
},
{
"id": 2,
"type": "value",
"value": "dublin"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
13,289
|
talkingdata
|
bird:train.json:1140
|
What is the age of the youngest female device user?
|
SELECT MIN(age) FROM gender_age WHERE gender = 'F'
|
[
"What",
"is",
"the",
"age",
"of",
"the",
"youngest",
"female",
"device",
"user",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "gender_age"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 3,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,290
|
food_inspection_2
|
bird:train.json:6207
|
What is the full name of the employee that inspected establishments with license 1334073?
|
SELECT DISTINCT T1.first_name, T1.last_name FROM employee AS T1 INNER JOIN inspection AS T2 ON T1.employee_id = T2.employee_id WHERE T2.license_no = 1334073
|
[
"What",
"is",
"the",
"full",
"name",
"of",
"the",
"employee",
"that",
"inspected",
"establishments",
"with",
"license",
"1334073",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "employee_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "table",
"value": "inspection"
},
{
"id": 4,
"type": "column",
"value": "license_no"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "employee"
},
{
"id": 5,
"type": "value",
"value": "1334073"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,291
|
book_1
|
bird:test.json:535
|
Show all book isbns and the numbers of orders for each.
|
SELECT isbn , count(*) FROM Books_Order GROUP BY isbn
|
[
"Show",
"all",
"book",
"isbns",
"and",
"the",
"numbers",
"of",
"orders",
"for",
"each",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "books_order"
},
{
"id": 1,
"type": "column",
"value": "isbn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7,
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
13,292
|
activity_1
|
spider:train_spider.json:6767
|
How many activities do we have?
|
SELECT count(*) FROM Activity
|
[
"How",
"many",
"activities",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "activity"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
13,293
|
regional_sales
|
bird:train.json:2660
|
Find the percentage of products that were shipped from Burbank in 2018?
|
SELECT CAST(SUM(CASE WHEN T3.`City Name` = 'Burbank' THEN T2.`Order Quantity` ELSE 0 END) AS REAL) * 100 / SUM(T2.`Order Quantity`) 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 T2.OrderDate LIKE '%/%/18'
|
[
"Find",
"the",
"percentage",
"of",
"products",
"that",
"were",
"shipped",
"from",
"Burbank",
"in",
"2018",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "Store Locations"
},
{
"id": 8,
"type": "column",
"value": "Order Quantity"
},
{
"id": 4,
"type": "table",
"value": "Sales Orders"
},
{
"id": 9,
"type": "column",
"value": "_productid"
},
{
"id": 1,
"type": "column",
"value": "orderdate"
},
{
"id": 10,
"type": "column",
"value": "productid"
},
{
"id": 12,
"type": "column",
"value": "City Name"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 6,
"type": "column",
"value": "_storeid"
},
{
"id": 5,
"type": "column",
"value": "storeid"
},
{
"id": 13,
"type": "value",
"value": "Burbank"
},
{
"id": 2,
"type": "value",
"value": "%/%/18"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 11,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": [
9
]
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O"
] |
13,294
|
insurance_policies
|
spider:train_spider.json:3890
|
Which Payments were processed with Visa? List the payment Id, the date and the amount.
|
SELECT Payment_ID , Date_Payment_Made , Amount_Payment FROM Payments WHERE Payment_Method_Code = 'Visa'
|
[
"Which",
"Payments",
"were",
"processed",
"with",
"Visa",
"?",
"List",
"the",
"payment",
"I",
"d",
",",
"the",
"date",
"and",
"the",
"amount",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "payment_method_code"
},
{
"id": 2,
"type": "column",
"value": "date_payment_made"
},
{
"id": 3,
"type": "column",
"value": "amount_payment"
},
{
"id": 1,
"type": "column",
"value": "payment_id"
},
{
"id": 0,
"type": "table",
"value": "payments"
},
{
"id": 5,
"type": "value",
"value": "Visa"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
10,
11
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12,
13
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
13,295
|
law_episode
|
bird:train.json:1307
|
In what year did the episodes titled DWB get an award?
|
SELECT DISTINCT T1.year FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id WHERE T2.title = 'DWB' AND T1.result = 'Winner'
|
[
"In",
"what",
"year",
"did",
"the",
"episodes",
"titled",
"DWB",
"get",
"an",
"award",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "episode_id"
},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 6,
"type": "column",
"value": "result"
},
{
"id": 7,
"type": "value",
"value": "Winner"
},
{
"id": 1,
"type": "table",
"value": "award"
},
{
"id": 4,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "DWB"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
13,296
|
music_2
|
spider:train_spider.json:5250
|
How many songs have a shared vocal?
|
SELECT count(DISTINCT title) FROM vocals AS T1 JOIN songs AS T2 ON T1.songid = T2.songid WHERE TYPE = "shared"
|
[
"How",
"many",
"songs",
"have",
"a",
"shared",
"vocal",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "vocals"
},
{
"id": 3,
"type": "column",
"value": "shared"
},
{
"id": 5,
"type": "column",
"value": "songid"
},
{
"id": 1,
"type": "table",
"value": "songs"
},
{
"id": 4,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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-TABLE",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
13,297
|
college_2
|
spider:train_spider.json:1490
|
Find the names of all instructors whose salary is greater than the salary of all instructors in the Biology department.
|
SELECT name FROM instructor WHERE salary > (SELECT max(salary) FROM instructor WHERE dept_name = 'Biology')
|
[
"Find",
"the",
"names",
"of",
"all",
"instructors",
"whose",
"salary",
"is",
"greater",
"than",
"the",
"salary",
"of",
"all",
"instructors",
"in",
"the",
"Biology",
"department",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "instructor"
},
{
"id": 3,
"type": "column",
"value": "dept_name"
},
{
"id": 4,
"type": "value",
"value": "Biology"
},
{
"id": 2,
"type": "column",
"value": "salary"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
13,298
|
retails
|
bird:train.json:6905
|
Which country has the least number of suppliers?
|
SELECT T2.n_name FROM supplier AS T1 INNER JOIN nation AS T2 ON T1.s_nationkey = T2.n_nationkey GROUP BY T1.s_nationkey ORDER BY COUNT(T1.s_name) LIMIT 1
|
[
"Which",
"country",
"has",
"the",
"least",
"number",
"of",
"suppliers",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "s_nationkey"
},
{
"id": 4,
"type": "column",
"value": "n_nationkey"
},
{
"id": 2,
"type": "table",
"value": "supplier"
},
{
"id": 1,
"type": "column",
"value": "n_name"
},
{
"id": 3,
"type": "table",
"value": "nation"
},
{
"id": 5,
"type": "column",
"value": "s_name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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"
] |
13,299
|
medicine_enzyme_interaction
|
spider:train_spider.json:965
|
What are the distinct name, location and products of the enzymes which has any 'inhibitor' interaction?
|
SELECT DISTINCT T1.name , T1.location , T1.product FROM enzyme AS T1 JOIN medicine_enzyme_interaction AS T2 ON T2.enzyme_id = T1.id WHERE T2.interaction_type = 'inhibitor'
|
[
"What",
"are",
"the",
"distinct",
"name",
",",
"location",
"and",
"products",
"of",
"the",
"enzymes",
"which",
"has",
"any",
"'",
"inhibitor",
"'",
"interaction",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "medicine_enzyme_interaction"
},
{
"id": 5,
"type": "column",
"value": "interaction_type"
},
{
"id": 6,
"type": "value",
"value": "inhibitor"
},
{
"id": 7,
"type": "column",
"value": "enzyme_id"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 2,
"type": "column",
"value": "product"
},
{
"id": 3,
"type": "table",
"value": "enzyme"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": [
16
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O"
] |
13,300
|
behavior_monitoring
|
spider:train_spider.json:3110
|
What are the code and description of the most frequent behavior incident type?
|
SELECT T1.incident_type_code , T2.incident_type_description FROM Behavior_Incident AS T1 JOIN Ref_Incident_Type AS T2 ON T1.incident_type_code = T2.incident_type_code GROUP BY T1.incident_type_code ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"are",
"the",
"code",
"and",
"description",
"of",
"the",
"most",
"frequent",
"behavior",
"incident",
"type",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "incident_type_description"
},
{
"id": 0,
"type": "column",
"value": "incident_type_code"
},
{
"id": 2,
"type": "table",
"value": "behavior_incident"
},
{
"id": 3,
"type": "table",
"value": "ref_incident_type"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"O"
] |
13,301
|
california_schools
|
bird:dev.json:1
|
Please list the lowest three eligible free rates for students aged 5-17 in continuation schools.
|
SELECT `Free Meal Count (Ages 5-17)` / `Enrollment (Ages 5-17)` FROM frpm WHERE `Educational Option Type` = 'Continuation School' AND `Free Meal Count (Ages 5-17)` / `Enrollment (Ages 5-17)` IS NOT NULL ORDER BY `Free Meal Count (Ages 5-17)` / `Enrollment (Ages 5-17)` ASC LIMIT 3
|
[
"Please",
"list",
"the",
"lowest",
"three",
"eligible",
"free",
"rates",
"for",
"students",
"aged",
"5",
"-",
"17",
"in",
"continuation",
"schools",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "Free Meal Count (Ages 5-17)"
},
{
"id": 3,
"type": "column",
"value": "Educational Option Type"
},
{
"id": 2,
"type": "column",
"value": "Enrollment (Ages 5-17)"
},
{
"id": 4,
"type": "value",
"value": "Continuation School"
},
{
"id": 0,
"type": "table",
"value": "frpm"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10,
11,
12,
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
15,
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,302
|
world_development_indicators
|
bird:train.json:2151
|
Mention the series code of countries using Hong Kong dollar as their currency unit.
|
SELECT T2.SeriesCode FROM Country AS T1 INNER JOIN CountryNotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T1.CurrencyUnit = 'Hong Kong dollar'
|
[
"Mention",
"the",
"series",
"code",
"of",
"countries",
"using",
"Hong",
"Kong",
"dollar",
"as",
"their",
"currency",
"unit",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Hong Kong dollar"
},
{
"id": 2,
"type": "table",
"value": "countrynotes"
},
{
"id": 3,
"type": "column",
"value": "currencyunit"
},
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 0,
"type": "column",
"value": "seriescode"
},
{
"id": 1,
"type": "table",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,303
|
customers_and_orders
|
bird:test.json:302
|
Count the number of customers who have not made an order.
|
SELECT count(*) FROM Customers WHERE customer_id NOT IN ( SELECT customer_id FROM Customer_orders)
|
[
"Count",
"the",
"number",
"of",
"customers",
"who",
"have",
"not",
"made",
"an",
"order",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O"
] |
13,304
|
perpetrator
|
spider:train_spider.json:2321
|
How many distinct locations of perpetrators are there?
|
SELECT count(DISTINCT LOCATION) FROM perpetrator
|
[
"How",
"many",
"distinct",
"locations",
"of",
"perpetrators",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "perpetrator"
},
{
"id": 1,
"type": "column",
"value": "location"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
13,305
|
olympics
|
bird:train.json:5004
|
What is the id of Rio de Janeiro?
|
SELECT id FROM city WHERE city_name = 'Rio de Janeiro'
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"Rio",
"de",
"Janeiro",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Rio de Janeiro"
},
{
"id": 2,
"type": "column",
"value": "city_name"
},
{
"id": 0,
"type": "table",
"value": "city"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,306
|
soccer_2
|
spider:train_spider.json:5034
|
Find the names of states that have some college students playing in the mid position but not in the goalie position.
|
SELECT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.pPos = 'mid' EXCEPT SELECT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.pPos = 'goalie'
|
[
"Find",
"the",
"names",
"of",
"states",
"that",
"have",
"some",
"college",
"students",
"playing",
"in",
"the",
"mid",
"position",
"but",
"not",
"in",
"the",
"goalie",
"position",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "college"
},
{
"id": 2,
"type": "table",
"value": "tryout"
},
{
"id": 5,
"type": "value",
"value": "goalie"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "column",
"value": "cname"
},
{
"id": 3,
"type": "column",
"value": "ppos"
},
{
"id": 4,
"type": "value",
"value": "mid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
19
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
13,307
|
car_retails
|
bird:train.json:1627
|
Please list all the customers that have Steve Patterson as their sales representitive.
|
SELECT t1.customerName FROM customers AS t1 INNER JOIN employees AS t2 ON t1.salesRepEmployeeNumber = t2.employeeNumber WHERE t2.firstName = 'Steve' AND t2.lastName = 'Patterson'
|
[
"Please",
"list",
"all",
"the",
"customers",
"that",
"have",
"Steve",
"Patterson",
"as",
"their",
"sales",
"representitive",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "salesrepemployeenumber"
},
{
"id": 4,
"type": "column",
"value": "employeenumber"
},
{
"id": 0,
"type": "column",
"value": "customername"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "employees"
},
{
"id": 5,
"type": "column",
"value": "firstname"
},
{
"id": 8,
"type": "value",
"value": "Patterson"
},
{
"id": 7,
"type": "column",
"value": "lastname"
},
{
"id": 6,
"type": "value",
"value": "Steve"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
13,308
|
toxicology
|
bird:dev.json:286
|
Among all chemical compounds identified in the database, what percent of compounds form a triple-bond.
|
SELECT CAST(COUNT(CASE WHEN T.bond_type = '#' THEN T.bond_id ELSE NULL END) AS REAL) * 100 / COUNT(T.bond_id) FROM bond AS T
|
[
"Among",
"all",
"chemical",
"compounds",
"identified",
"in",
"the",
"database",
",",
"what",
"percent",
"of",
"compounds",
"form",
"a",
"triple",
"-",
"bond",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "bond_type"
},
{
"id": 2,
"type": "column",
"value": "bond_id"
},
{
"id": 0,
"type": "table",
"value": "bond"
},
{
"id": 1,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "#"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,309
|
retail_complains
|
bird:train.json:358
|
Complaint about Credit Card mostly came from clients of which age group?
|
SELECT SUM(CASE WHEN T1.age > 13 AND T1.age <= 19 THEN 1 ELSE 0 END), SUM(CASE WHEN T1.age > 19 AND T1.age <= 65 THEN 1 ELSE 0 END) AS adult , SUM(CASE WHEN T1.age > 65 THEN 1 ELSE 0 END) AS elder FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.Product = 'Credit card'
|
[
"Complaint",
"about",
"Credit",
"Card",
"mostly",
"came",
"from",
"clients",
"of",
"which",
"age",
"group",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Credit card"
},
{
"id": 4,
"type": "column",
"value": "client_id"
},
{
"id": 2,
"type": "column",
"value": "product"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "table",
"value": "events"
},
{
"id": 7,
"type": "column",
"value": "age"
},
{
"id": 8,
"type": "value",
"value": "65"
},
{
"id": 9,
"type": "value",
"value": "13"
},
{
"id": 10,
"type": "value",
"value": "19"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2,
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,310
|
movie_platform
|
bird:train.json:138
|
Name all the list titles created by user 4208563.
|
SELECT list_title FROM lists WHERE user_id LIKE 4208563
|
[
"Name",
"all",
"the",
"list",
"titles",
"created",
"by",
"user",
"4208563",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "list_title"
},
{
"id": 2,
"type": "column",
"value": "user_id"
},
{
"id": 3,
"type": "value",
"value": "4208563"
},
{
"id": 0,
"type": "table",
"value": "lists"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,311
|
mondial_geo
|
bird:train.json:8491
|
What is the name of the most recently founded organization in Saudi Arabia?
|
SELECT T1.Name FROM organization AS T1 INNER JOIN country AS T2 ON T1.Country = T2.Code WHERE T2.Name = 'Saudi Arabia' ORDER BY T1.Established DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"most",
"recently",
"founded",
"organization",
"in",
"Saudi",
"Arabia",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "organization"
},
{
"id": 3,
"type": "value",
"value": "Saudi Arabia"
},
{
"id": 4,
"type": "column",
"value": "established"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,312
|
customer_complaints
|
spider:train_spider.json:5804
|
How many distinct complaint type codes are there in the database?
|
SELECT count(DISTINCT complaint_type_code) FROM complaints
|
[
"How",
"many",
"distinct",
"complaint",
"type",
"codes",
"are",
"there",
"in",
"the",
"database",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "complaint_type_code"
},
{
"id": 0,
"type": "table",
"value": "complaints"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
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-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,313
|
book_2
|
spider:train_spider.json:219
|
What are the distinct publishers of publications with price higher than 5000000?
|
SELECT DISTINCT Publisher FROM publication WHERE Price > 5000000
|
[
"What",
"are",
"the",
"distinct",
"publishers",
"of",
"publications",
"with",
"price",
"higher",
"than",
"5000000",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "publication"
},
{
"id": 1,
"type": "column",
"value": "publisher"
},
{
"id": 3,
"type": "value",
"value": "5000000"
},
{
"id": 2,
"type": "column",
"value": "price"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"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,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,314
|
retail_complains
|
bird:train.json:340
|
Compute the average time in minute for each age group
|
SELECT CAST(SUM(CASE WHEN T1.age > 13 AND T1.age <= 19 THEN 60 * strftime('%H', ser_time) + strftime('%M', ser_time) + strftime('%S', ser_time) / 60 ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age > 13 AND T1.age <= 19 THEN 1 ELSE 0 END) AS teenagerAverageMins, CAST(SUM(CASE WHEN T1.age > 19 AND T1.age <= 65 THEN 60 * strftime('%H', ser_time) + strftime('%M', ser_time) + strftime('%S', ser_time) / 60 ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age > 19 AND T1.age <= 65 THEN 1 ELSE 0 END) AS adultAverageMins , CAST(SUM(CASE WHEN T1.age > 65 THEN 60 * strftime('%H', ser_time) + strftime('%M', ser_time) + strftime('%S', ser_time) / 60 ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age > 65 THEN 1 ELSE 0 END) AS elderAverageMins FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client`
|
[
"Compute",
"the",
"average",
"time",
"in",
"minute",
"for",
"each",
"age",
"group"
] |
[
{
"id": 1,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 3,
"type": "column",
"value": "rand client"
},
{
"id": 2,
"type": "column",
"value": "client_id"
},
{
"id": 12,
"type": "column",
"value": "ser_time"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 6,
"type": "column",
"value": "age"
},
{
"id": 7,
"type": "value",
"value": "65"
},
{
"id": 8,
"type": "value",
"value": "13"
},
{
"id": 9,
"type": "value",
"value": "19"
},
{
"id": 10,
"type": "value",
"value": "60"
},
{
"id": 11,
"type": "value",
"value": "%M"
},
{
"id": 13,
"type": "value",
"value": "%S"
},
{
"id": 14,
"type": "value",
"value": "%H"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
3
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O"
] |
13,315
|
legislator
|
bird:train.json:4857
|
List all the junior senators in 1997.
|
SELECT T1.first_name, T1.last_name FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.start LIKE '1997%' AND T2.state_rank = 'junior'
|
[
"List",
"all",
"the",
"junior",
"senators",
"in",
"1997",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "current-terms"
},
{
"id": 4,
"type": "column",
"value": "bioguide_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 8,
"type": "column",
"value": "state_rank"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "bioguide"
},
{
"id": 2,
"type": "table",
"value": "current"
},
{
"id": 9,
"type": "value",
"value": "junior"
},
{
"id": 6,
"type": "column",
"value": "start"
},
{
"id": 7,
"type": "value",
"value": "1997%"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"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": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
3
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
13,316
|
financial
|
bird:dev.json:141
|
Which districts have transactions greater than USS$10,000 in 1997?
|
SELECT T1.district_id FROM account AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN trans AS T3 ON T1.account_id = T3.account_id WHERE STRFTIME('%Y', T3.date) = '1997' GROUP BY T1.district_id HAVING SUM(T3.amount) > 10000
|
[
"Which",
"districts",
"have",
"transactions",
"greater",
"than",
"USS$10,000",
"in",
"1997",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "district_id"
},
{
"id": 6,
"type": "column",
"value": "account_id"
},
{
"id": 5,
"type": "table",
"value": "district"
},
{
"id": 4,
"type": "table",
"value": "account"
},
{
"id": 9,
"type": "column",
"value": "amount"
},
{
"id": 1,
"type": "table",
"value": "trans"
},
{
"id": 3,
"type": "value",
"value": "10000"
},
{
"id": 2,
"type": "value",
"value": "1997"
},
{
"id": 8,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
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8
]
},
{
"entity_id": 3,
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6
]
},
{
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},
{
"entity_id": 5,
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1
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
13,317
|
icfp_1
|
spider:train_spider.json:2903
|
Which institution has the most papers? Find the name of the institution.
|
SELECT t1.name FROM inst AS t1 JOIN authorship AS t2 ON t1.instid = t2.instid JOIN papers AS t3 ON t2.paperid = t3.paperid GROUP BY t1.name ORDER BY count(*) DESC LIMIT 1
|
[
"Which",
"institution",
"has",
"the",
"most",
"papers",
"?",
"Find",
"the",
"name",
"of",
"the",
"institution",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "authorship"
},
{
"id": 4,
"type": "column",
"value": "paperid"
},
{
"id": 1,
"type": "table",
"value": "papers"
},
{
"id": 5,
"type": "column",
"value": "instid"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "inst"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,318
|
flight_company
|
spider:train_spider.json:6368
|
List the id, country, city and name of the airports ordered alphabetically by the name.
|
SELECT id , country , city , name FROM airport ORDER BY name
|
[
"List",
"the",
"i",
"d",
",",
"country",
",",
"city",
"and",
"name",
"of",
"the",
"airports",
"ordered",
"alphabetically",
"by",
"the",
"name",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "airport"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
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{
"entity_id": 2,
"token_idxs": [
5
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},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,319
|
thrombosis_prediction
|
bird:dev.json:1154
|
State the sex and birthday of patient ID '163109'. When was the examination taken and what symptom does the patient had.
|
SELECT T1.SEX, T1.Birthday, T2.`Examination Date`, T2.Symptoms FROM Patient AS T1 INNER JOIN Examination AS T2 ON T1.ID = T2.ID WHERE T1.ID = 163109
|
[
"State",
"the",
"sex",
"and",
"birthday",
"of",
"patient",
"ID",
"'",
"163109",
"'",
".",
"When",
"was",
"the",
"examination",
"taken",
"and",
"what",
"symptom",
"does",
"the",
"patient",
"had",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "Examination Date"
},
{
"id": 5,
"type": "table",
"value": "examination"
},
{
"id": 1,
"type": "column",
"value": "birthday"
},
{
"id": 3,
"type": "column",
"value": "symptoms"
},
{
"id": 4,
"type": "table",
"value": "patient"
},
{
"id": 7,
"type": "value",
"value": "163109"
},
{
"id": 0,
"type": "column",
"value": "sex"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": [
22
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
13,320
|
menu
|
bird:train.json:5498
|
Provide the page IDs and name of the menu which had the highest page count.
|
SELECT T1.page_number, T2.name FROM MenuPage AS T1 INNER JOIN Menu AS T2 ON T2.id = T1.menu_id ORDER BY T2.page_count DESC LIMIT 1
|
[
"Provide",
"the",
"page",
"IDs",
"and",
"name",
"of",
"the",
"menu",
"which",
"had",
"the",
"highest",
"page",
"count",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "page_number"
},
{
"id": 4,
"type": "column",
"value": "page_count"
},
{
"id": 2,
"type": "table",
"value": "menupage"
},
{
"id": 6,
"type": "column",
"value": "menu_id"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "table",
"value": "menu"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"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-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
13,321
|
software_company
|
bird:train.json:8556
|
What percentage of elderly customers who are never married in the place with geographic ID 24?
|
SELECT CAST(SUM(CASE WHEN T1.MARITAL_STATUS = 'never married' THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.GEOID = 24
|
[
"What",
"percentage",
"of",
"elderly",
"customers",
"who",
"are",
"never",
"married",
"in",
"the",
"place",
"with",
"geographic",
"ID",
"24",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "marital_status"
},
{
"id": 8,
"type": "value",
"value": "never married"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "table",
"value": "demog"
},
{
"id": 2,
"type": "column",
"value": "geoid"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "1.0"
},
{
"id": 3,
"type": "value",
"value": "24"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
7,
8
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,322
|
debit_card_specializing
|
bird:dev.json:1485
|
How much more was customer 7 consuming in April 2013 than customer 5?
|
SELECT SUM(IIF(CustomerID = 7, Consumption, 0)) - SUM(IIF(CustomerID = 5, Consumption, 0)) FROM yearmonth WHERE Date = '201304'
|
[
"How",
"much",
"more",
"was",
"customer",
"7",
"consuming",
"in",
"April",
"2013",
"than",
"customer",
"5",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "consumption"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "yearmonth"
},
{
"id": 2,
"type": "value",
"value": "201304"
},
{
"id": 1,
"type": "column",
"value": "date"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "7"
},
{
"id": 7,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"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-VALUE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,323
|
soccer_2016
|
bird:train.json:1932
|
What is the total number of runs scored by the batsmen during the 2nd inning of the match ID 335988?
|
SELECT SUM(Runs_Scored) FROM Batsman_Scored WHERE Match_Id = 335988 AND Innings_No = 2
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"runs",
"scored",
"by",
"the",
"batsmen",
"during",
"the",
"2nd",
"inning",
"of",
"the",
"match",
"ID",
"335988",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "batsman_scored"
},
{
"id": 1,
"type": "column",
"value": "runs_scored"
},
{
"id": 4,
"type": "column",
"value": "innings_no"
},
{
"id": 2,
"type": "column",
"value": "match_id"
},
{
"id": 3,
"type": "value",
"value": "335988"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
17,
18
]
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
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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",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
13,324
|
superstore
|
bird:train.json:2352
|
What is the total quantity of "Telescoping Adjustable Floor Lamp" ordered from central superstores?
|
SELECT SUM(T1.Quantity) FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.`Product Name` = 'Telescoping Adjustable Floor Lamp'
|
[
"What",
"is",
"the",
"total",
"quantity",
"of",
"\"",
"Telescoping",
"Adjustable",
"Floor",
"Lamp",
"\"",
"ordered",
"from",
"central",
"superstores",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Telescoping Adjustable Floor Lamp"
},
{
"id": 0,
"type": "table",
"value": "central_superstore"
},
{
"id": 2,
"type": "column",
"value": "Product Name"
},
{
"id": 5,
"type": "column",
"value": "Product ID"
},
{
"id": 4,
"type": "column",
"value": "quantity"
},
{
"id": 1,
"type": "table",
"value": "product"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14,
15
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
13,325
|
school_player
|
spider:train_spider.json:4886
|
Please show different denominations and the corresponding number of schools.
|
SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination
|
[
"Please",
"show",
"different",
"denominations",
"and",
"the",
"corresponding",
"number",
"of",
"schools",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "denomination"
},
{
"id": 0,
"type": "table",
"value": "school"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,326
|
donor
|
bird:train.json:3236
|
How many number of donations did the project 'A Rug For Reaching Readers' get?
|
SELECT SUM(T2.donation_total) FROM essays AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.title LIKE 'A Rug For Reaching Readers'
|
[
"How",
"many",
"number",
"of",
"donations",
"did",
"the",
"project",
"'",
"A",
"Rug",
"For",
"Reaching",
"Readers",
"'",
"get",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "A Rug For Reaching Readers"
},
{
"id": 4,
"type": "column",
"value": "donation_total"
},
{
"id": 1,
"type": "table",
"value": "donations"
},
{
"id": 5,
"type": "column",
"value": "projectid"
},
{
"id": 0,
"type": "table",
"value": "essays"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11,
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
13,327
|
college_2
|
spider:train_spider.json:1393
|
How many rooms in each building have a capacity of over 50?
|
SELECT count(*) , building FROM classroom WHERE capacity > 50 GROUP BY building
|
[
"How",
"many",
"rooms",
"in",
"each",
"building",
"have",
"a",
"capacity",
"of",
"over",
"50",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "classroom"
},
{
"id": 1,
"type": "column",
"value": "building"
},
{
"id": 2,
"type": "column",
"value": "capacity"
},
{
"id": 3,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
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11
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
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{
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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,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,328
|
california_schools
|
bird:dev.json:65
|
What is the ratio in percentage of Santa Clara County schools that are locally funded compared to all other types of charter school funding?
|
SELECT CAST(SUM(CASE WHEN FundingType = 'Locally funded' THEN 1 ELSE 0 END) AS REAL) * 100 / SUM(CASE WHEN FundingType != 'Locally funded' THEN 1 ELSE 0 END) FROM schools WHERE County = 'Santa Clara' AND Charter = 1
|
[
"What",
"is",
"the",
"ratio",
"in",
"percentage",
"of",
"Santa",
"Clara",
"County",
"schools",
"that",
"are",
"locally",
"funded",
"compared",
"to",
"all",
"other",
"types",
"of",
"charter",
"school",
"funding",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Locally funded"
},
{
"id": 2,
"type": "value",
"value": "Santa Clara"
},
{
"id": 7,
"type": "column",
"value": "fundingtype"
},
{
"id": 0,
"type": "table",
"value": "schools"
},
{
"id": 3,
"type": "column",
"value": "charter"
},
{
"id": 1,
"type": "column",
"value": "county"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
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9
]
},
{
"entity_id": 2,
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7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
21
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
23
]
},
{
"entity_id": 8,
"token_idxs": [
13,
14
]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
13,329
|
government_shift
|
bird:test.json:365
|
Find the details of the customer who has used services the most times.
|
SELECT t1.customer_details FROM customers AS t1 JOIN customers_and_services AS t2 ON t1.customer_id = t2.customer_id GROUP BY t1.customer_details ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"details",
"of",
"the",
"customer",
"who",
"has",
"used",
"services",
"the",
"most",
"times",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "customers_and_services"
},
{
"id": 0,
"type": "column",
"value": "customer_details"
},
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O"
] |
13,330
|
public_review_platform
|
bird:train.json:3807
|
How many compliments received from medium users that Phoenix city achieved?
|
SELECT COUNT(T1.number_of_compliments) FROM Users_Compliments AS T1 INNER JOIN Reviews AS T2 ON T1.user_id = T2.user_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T3.city LIKE 'Phoenix' AND T1.number_of_compliments LIKE 'Medium'
|
[
"How",
"many",
"compliments",
"received",
"from",
"medium",
"users",
"that",
"Phoenix",
"city",
"achieved",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "number_of_compliments"
},
{
"id": 2,
"type": "table",
"value": "users_compliments"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 3,
"type": "table",
"value": "reviews"
},
{
"id": 6,
"type": "value",
"value": "Phoenix"
},
{
"id": 8,
"type": "column",
"value": "user_id"
},
{
"id": 7,
"type": "value",
"value": "Medium"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"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": [
9
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": [
6
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O"
] |
13,331
|
soccer_2016
|
bird:train.json:1936
|
Where was the ID 336005 match held? Please give me the venue and the city.
|
SELECT T2.Venue_Name, T3.City_Name FROM `Match` AS T1 INNER JOIN Venue AS T2 ON T1.Venue_Id = T2.Venue_Id INNER JOIN City AS T3 ON T2.City_Id = T3.City_Id WHERE T1.Match_Id = '336005'
|
[
"Where",
"was",
"the",
"ID",
"336005",
"match",
"held",
"?",
"Please",
"give",
"me",
"the",
"venue",
"and",
"the",
"city",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "venue_name"
},
{
"id": 1,
"type": "column",
"value": "city_name"
},
{
"id": 3,
"type": "column",
"value": "match_id"
},
{
"id": 8,
"type": "column",
"value": "venue_id"
},
{
"id": 7,
"type": "column",
"value": "city_id"
},
{
"id": 4,
"type": "value",
"value": "336005"
},
{
"id": 5,
"type": "table",
"value": "Match"
},
{
"id": 6,
"type": "table",
"value": "venue"
},
{
"id": 2,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
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},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O"
] |
13,332
|
shipping
|
bird:train.json:5619
|
Identify the total weight of shipments transported to San Mateo, California, in 2016.
|
SELECT SUM(T1.weight) FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T2.city_name = 'San Mateo' AND STRFTIME('%Y', T1.ship_date) = '2016'
|
[
"Identify",
"the",
"total",
"weight",
"of",
"shipments",
"transported",
"to",
"San",
"Mateo",
",",
"California",
",",
"in",
"2016",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "city_name"
},
{
"id": 5,
"type": "value",
"value": "San Mateo"
},
{
"id": 8,
"type": "column",
"value": "ship_date"
},
{
"id": 0,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "column",
"value": "city_id"
},
{
"id": 2,
"type": "column",
"value": "weight"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 6,
"type": "value",
"value": "2016"
},
{
"id": 7,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
8,
9
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,333
|
ship_mission
|
spider:train_spider.json:4011
|
For each type, how many ships are there?
|
SELECT TYPE , COUNT(*) FROM ship GROUP BY TYPE
|
[
"For",
"each",
"type",
",",
"how",
"many",
"ships",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "ship"
},
{
"id": 1,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
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2
]
},
{
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
13,334
|
driving_school
|
spider:train_spider.json:6681
|
What are the first and last names of all customers with between 1000 and 3000 dollars outstanding?
|
SELECT first_name , last_name FROM Customers WHERE amount_outstanding BETWEEN 1000 AND 3000;
|
[
"What",
"are",
"the",
"first",
"and",
"last",
"names",
"of",
"all",
"customers",
"with",
"between",
"1000",
"and",
"3000",
"dollars",
"outstanding",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "amount_outstanding"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "value",
"value": "1000"
},
{
"id": 5,
"type": "value",
"value": "3000"
}
] |
[
{
"entity_id": 0,
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9
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3
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5,
6
]
},
{
"entity_id": 3,
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16
]
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12
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
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{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O"
] |
13,335
|
food_inspection_2
|
bird:train.json:6139
|
How many sanitarian employees in Chicago are from the zip code 60617?
|
SELECT COUNT(employee_id) FROM employee WHERE zip = '60617'
|
[
"How",
"many",
"sanitarian",
"employees",
"in",
"Chicago",
"are",
"from",
"the",
"zip",
"code",
"60617",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "employee_id"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "value",
"value": "60617"
},
{
"id": 1,
"type": "column",
"value": "zip"
}
] |
[
{
"entity_id": 0,
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3
]
},
{
"entity_id": 1,
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9
]
},
{
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11
]
},
{
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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},
{
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},
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},
{
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},
{
"entity_id": 13,
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,336
|
social_media
|
bird:train.json:785
|
Please list the texts of all the tweets posted from Buenos Aires with a positive sentiment.
|
SELECT T1.text FROM twitter AS T1 INNER JOIN location AS T2 ON T2.LocationID = T1.LocationID WHERE T1.Sentiment > 0 AND T2.City = 'Buenos Aires'
|
[
"Please",
"list",
"the",
"texts",
"of",
"all",
"the",
"tweets",
"posted",
"from",
"Buenos",
"Aires",
"with",
"a",
"positive",
"sentiment",
"."
] |
[
{
"id": 7,
"type": "value",
"value": "Buenos Aires"
},
{
"id": 3,
"type": "column",
"value": "locationid"
},
{
"id": 4,
"type": "column",
"value": "sentiment"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 1,
"type": "table",
"value": "twitter"
},
{
"id": 0,
"type": "column",
"value": "text"
},
{
"id": 6,
"type": "column",
"value": "city"
},
{
"id": 5,
"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": []
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
10,
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,337
|
university
|
bird:train.json:8036
|
What is the percentage of Harvard university's international students in 2011?
|
SELECT T1.pct_international_students FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T1.year = 2011 AND T2.university_name = 'Harvard University'
|
[
"What",
"is",
"the",
"percentage",
"of",
"Harvard",
"university",
"'s",
"international",
"students",
"in",
"2011",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "pct_international_students"
},
{
"id": 8,
"type": "value",
"value": "Harvard University"
},
{
"id": 1,
"type": "table",
"value": "university_year"
},
{
"id": 7,
"type": "column",
"value": "university_name"
},
{
"id": 3,
"type": "column",
"value": "university_id"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 5,
"type": "column",
"value": "year"
},
{
"id": 6,
"type": "value",
"value": "2011"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8,
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
5
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,338
|
mondial_geo
|
bird:train.json:8315
|
Among the countries that use Bosnian as their language, how many of them don't have a positive population growth rate?
|
SELECT COUNT(DISTINCT T1.Name) FROM country AS T1 INNER JOIN language AS T2 ON T1.Code = T2.Country INNER JOIN population AS T3 ON T3.Country = T2.Country WHERE T2.Name = 'Bosnian' AND T3.Population_Growth < 0
|
[
"Among",
"the",
"countries",
"that",
"use",
"Bosnian",
"as",
"their",
"language",
",",
"how",
"many",
"of",
"them",
"do",
"n't",
"have",
"a",
"positive",
"population",
"growth",
"rate",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "population_growth"
},
{
"id": 0,
"type": "table",
"value": "population"
},
{
"id": 3,
"type": "table",
"value": "language"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "country"
},
{
"id": 5,
"type": "value",
"value": "Bosnian"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "code"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
20
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O"
] |
13,339
|
car_racing
|
bird:test.json:1626
|
Which make does the most drivers have?
|
SELECT Make FROM driver GROUP BY Make ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Which",
"make",
"does",
"the",
"most",
"drivers",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 1,
"type": "column",
"value": "make"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
13,340
|
world_development_indicators
|
bird:train.json:2169
|
Write down the description and series code of Benin in year 2005.
|
SELECT T2.Description, T2.Seriescode FROM Country AS T1 INNER JOIN FootNotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T1.TableName = 'Benin' AND T2.Year = 'YR2005'
|
[
"Write",
"down",
"the",
"description",
"and",
"series",
"code",
"of",
"Benin",
"in",
"year",
"2005",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 4,
"type": "column",
"value": "countrycode"
},
{
"id": 1,
"type": "column",
"value": "seriescode"
},
{
"id": 3,
"type": "table",
"value": "footnotes"
},
{
"id": 5,
"type": "column",
"value": "tablename"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 8,
"type": "value",
"value": "YR2005"
},
{
"id": 6,
"type": "value",
"value": "Benin"
},
{
"id": 7,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": [
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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,341
|
e_government
|
spider:train_spider.json:6332
|
How many cities are there in state "Colorado"?
|
SELECT count(*) FROM addresses WHERE state_province_county = "Colorado"
|
[
"How",
"many",
"cities",
"are",
"there",
"in",
"state",
"\"",
"Colorado",
"\"",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "state_province_county"
},
{
"id": 0,
"type": "table",
"value": "addresses"
},
{
"id": 2,
"type": "column",
"value": "Colorado"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,342
|
college_1
|
spider:train_spider.json:3176
|
How many professors teach a class with the code ACCT-211?
|
SELECT count(DISTINCT PROF_NUM) FROM CLASS WHERE CRS_CODE = "ACCT-211"
|
[
"How",
"many",
"professors",
"teach",
"a",
"class",
"with",
"the",
"code",
"ACCT-211",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "crs_code"
},
{
"id": 2,
"type": "column",
"value": "ACCT-211"
},
{
"id": 3,
"type": "column",
"value": "prof_num"
},
{
"id": 0,
"type": "table",
"value": "class"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
13,343
|
chinook_1
|
spider:train_spider.json:864
|
What are the phone numbers for each employee?
|
SELECT Phone FROM EMPLOYEE
|
[
"What",
"are",
"the",
"phone",
"numbers",
"for",
"each",
"employee",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "column",
"value": "phone"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,344
|
tracking_software_problems
|
spider:train_spider.json:5384
|
What are the id of problems reported by the staff named Dameon Frami or Jolie Weber?
|
SELECT product_id FROM problems AS T1 JOIN staff AS T2 ON T1.reported_by_staff_id = T2.staff_id WHERE T2.staff_first_name = "Dameon" AND T2.staff_last_name = "Frami" UNION SELECT product_id FROM problems AS T1 JOIN staff AS T2 ON T1.reported_by_staff_id = T2.staff_id WHERE T2.staff_first_name = "Jolie" AND T2.staff_last_name = "Weber"
|
[
"What",
"are",
"the",
"i",
"d",
"of",
"problems",
"reported",
"by",
"the",
"staff",
"named",
"Dameon",
"Frami",
"or",
"Jolie",
"Weber",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "reported_by_staff_id"
},
{
"id": 5,
"type": "column",
"value": "staff_first_name"
},
{
"id": 7,
"type": "column",
"value": "staff_last_name"
},
{
"id": 0,
"type": "column",
"value": "product_id"
},
{
"id": 1,
"type": "table",
"value": "problems"
},
{
"id": 4,
"type": "column",
"value": "staff_id"
},
{
"id": 6,
"type": "column",
"value": "Dameon"
},
{
"id": 2,
"type": "table",
"value": "staff"
},
{
"id": 8,
"type": "column",
"value": "Frami"
},
{
"id": 9,
"type": "column",
"value": "Jolie"
},
{
"id": 10,
"type": "column",
"value": "Weber"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": [
15
]
},
{
"entity_id": 10,
"token_idxs": [
16
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
13,345
|
retail_world
|
bird:train.json:6591
|
How many product names does the supplier Exotic Liquids have?
|
SELECT COUNT(T1.ProductName) FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Exotic Liquids'
|
[
"How",
"many",
"product",
"names",
"does",
"the",
"supplier",
"Exotic",
"Liquids",
"have",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Exotic Liquids"
},
{
"id": 2,
"type": "column",
"value": "companyname"
},
{
"id": 4,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "column",
"value": "supplierid"
},
{
"id": 1,
"type": "table",
"value": "suppliers"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
13,346
|
student_loan
|
bird:train.json:4458
|
Calculate the ratio between unemployed students and disabled students.
|
SELECT CAST(( SELECT COUNT(name) FROM unemployed ) AS REAL ) / ( SELECT COUNT(name) FROM disabled )
|
[
"Calculate",
"the",
"ratio",
"between",
"unemployed",
"students",
"and",
"disabled",
"students",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "unemployed"
},
{
"id": 0,
"type": "table",
"value": "disabled"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
13,347
|
sports_competition
|
spider:train_spider.json:3363
|
List the position of players with average number of points scored by players of that position bigger than 20.
|
SELECT POSITION FROM player GROUP BY name HAVING avg(Points) >= 20
|
[
"List",
"the",
"position",
"of",
"players",
"with",
"average",
"number",
"of",
"points",
"scored",
"by",
"players",
"of",
"that",
"position",
"bigger",
"than",
"20",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "position"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 4,
"type": "column",
"value": "points"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,348
|
image_and_language
|
bird:train.json:7597
|
List all bounding box widths and heights of object sample ID 2.
|
SELECT W, H FROM IMG_OBJ WHERE OBJ_SAMPLE_ID = 2
|
[
"List",
"all",
"bounding",
"box",
"widths",
"and",
"heights",
"of",
"object",
"sample",
"ID",
"2",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "obj_sample_id"
},
{
"id": 0,
"type": "table",
"value": "img_obj"
},
{
"id": 1,
"type": "column",
"value": "w"
},
{
"id": 2,
"type": "column",
"value": "h"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
13,349
|
movie_3
|
bird:train.json:9370
|
Name the cast members of the movie 'African Egg'.
|
SELECT T2.first_name, T2.last_name FROM film_actor AS T1 INNER JOIN actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T1.film_id = T3.film_id WHERE T3.title = 'AFRICAN EGG'
|
[
"Name",
"the",
"cast",
"members",
"of",
"the",
"movie",
"'",
"African",
"Egg",
"'",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "AFRICAN EGG"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 5,
"type": "table",
"value": "film_actor"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 8,
"type": "column",
"value": "actor_id"
},
{
"id": 7,
"type": "column",
"value": "film_id"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "table",
"value": "actor"
},
{
"id": 2,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
13,350
|
disney
|
bird:train.json:4652
|
What are the names of the characters voiced by Frank Welker?
|
SELECT character FROM `voice-actors` WHERE 'voice-actor' = 'Frank Welker'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"characters",
"voiced",
"by",
"Frank",
"Welker",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "voice-actors"
},
{
"id": 3,
"type": "value",
"value": "Frank Welker"
},
{
"id": 2,
"type": "value",
"value": "voice-actor"
},
{
"id": 1,
"type": "column",
"value": "character"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,351
|
movies_4
|
bird:train.json:442
|
Who is the person associated with the crew id 1325273?
|
SELECT person_name FROM person WHERE person_id = 1325273
|
[
"Who",
"is",
"the",
"person",
"associated",
"with",
"the",
"crew",
"i",
"d",
"1325273",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "person_name"
},
{
"id": 2,
"type": "column",
"value": "person_id"
},
{
"id": 3,
"type": "value",
"value": "1325273"
},
{
"id": 0,
"type": "table",
"value": "person"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,352
|
financial
|
bird:dev.json:163
|
Which district has the most accounts with loan contracts finished with no problems?
|
SELECT T1.A2 FROM District AS T1 INNER JOIN Account AS T2 ON T1.District_id = T2.District_id INNER JOIN Loan AS T3 ON T2.Account_id = T3.Account_id WHERE T3.status = 'A' GROUP BY T1.District_id ORDER BY COUNT(T2.Account_id) DESC LIMIT 1
|
[
"Which",
"district",
"has",
"the",
"most",
"accounts",
"with",
"loan",
"contracts",
"finished",
"with",
"no",
"problems",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "district_id"
},
{
"id": 7,
"type": "column",
"value": "account_id"
},
{
"id": 5,
"type": "table",
"value": "district"
},
{
"id": 6,
"type": "table",
"value": "account"
},
{
"id": 3,
"type": "column",
"value": "status"
},
{
"id": 2,
"type": "table",
"value": "loan"
},
{
"id": 1,
"type": "column",
"value": "a2"
},
{
"id": 4,
"type": "value",
"value": "A"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
1
]
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,354
|
driving_school
|
spider:train_spider.json:6693
|
How many customers have no payment histories?
|
SELECT count(*) FROM Customers WHERE customer_id NOT IN ( SELECT customer_id FROM Customer_Payments );
|
[
"How",
"many",
"customers",
"have",
"no",
"payment",
"histories",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "customer_payments"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O"
] |
13,355
|
toxicology
|
bird:dev.json:221
|
What are the atoms that are bonded in the molecule TR001 with the bond ID of TR001_2_6?
|
SELECT SUBSTR(T.bond_id, 1, 7) AS atom_id1 , T.molecule_id || SUBSTR(T.bond_id, 8, 2) AS atom_id2 FROM bond AS T WHERE T.molecule_id = 'TR001' AND T.bond_id = 'TR001_2_6'
|
[
"What",
"are",
"the",
"atoms",
"that",
"are",
"bonded",
"in",
"the",
"molecule",
"TR001",
"with",
"the",
"bond",
"ID",
"of",
"TR001_2_6",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "molecule_id"
},
{
"id": 6,
"type": "value",
"value": "TR001_2_6"
},
{
"id": 1,
"type": "column",
"value": "bond_id"
},
{
"id": 5,
"type": "value",
"value": "TR001"
},
{
"id": 0,
"type": "table",
"value": "bond"
},
{
"id": 2,
"type": "value",
"value": "1"
},
{
"id": 3,
"type": "value",
"value": "7"
},
{
"id": 7,
"type": "value",
"value": "8"
},
{
"id": 8,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
16
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,356
|
language_corpus
|
bird:train.json:5744
|
How many Catalan-language Wikipedia pages are there overall?
|
SELECT pages FROM langs WHERE lang = 'ca'
|
[
"How",
"many",
"Catalan",
"-",
"language",
"Wikipedia",
"pages",
"are",
"there",
"overall",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "langs"
},
{
"id": 1,
"type": "column",
"value": "pages"
},
{
"id": 2,
"type": "column",
"value": "lang"
},
{
"id": 3,
"type": "value",
"value": "ca"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,357
|
department_store
|
spider:train_spider.json:4785
|
Find the names of products that were bought by at least two distinct customers.
|
SELECT DISTINCT T3.product_name FROM customer_orders AS T1 JOIN order_items AS T2 ON T1.order_id = T2.order_id JOIN products AS T3 ON T2.product_id = T3.product_id GROUP BY T3.product_id HAVING COUNT (DISTINCT T1.customer_id) >= 2
|
[
"Find",
"the",
"names",
"of",
"products",
"that",
"were",
"bought",
"by",
"at",
"least",
"two",
"distinct",
"customers",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 5,
"type": "table",
"value": "order_items"
},
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "column",
"value": "product_id"
},
{
"id": 2,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "column",
"value": "order_id"
},
{
"id": 3,
"type": "value",
"value": "2"
}
] |
[
{
"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": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,358
|
school_player
|
spider:train_spider.json:4883
|
What is the denomination of the school the most players belong to?
|
SELECT T2.Denomination FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID ORDER BY COUNT(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"denomination",
"of",
"the",
"school",
"the",
"most",
"players",
"belong",
"to",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "denomination"
},
{
"id": 0,
"type": "column",
"value": "school_id"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 3,
"type": "table",
"value": "school"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
13,359
|
university_basketball
|
spider:train_spider.json:989
|
What is the primary conference of the school that has the lowest acc percent score in the competition?
|
SELECT t1.Primary_conference FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id ORDER BY t2.acc_percent LIMIT 1
|
[
"What",
"is",
"the",
"primary",
"conference",
"of",
"the",
"school",
"that",
"has",
"the",
"lowest",
"acc",
"percent",
"score",
"in",
"the",
"competition",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "primary_conference"
},
{
"id": 2,
"type": "table",
"value": "basketball_match"
},
{
"id": 3,
"type": "column",
"value": "acc_percent"
},
{
"id": 1,
"type": "table",
"value": "university"
},
{
"id": 4,
"type": "column",
"value": "school_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
13,360
|
cs_semester
|
bird:train.json:929
|
Give the student's last name that gave the highest student satisfaction for the course "Intro to Database 2".
|
SELECT T1.l_name FROM student AS T1 INNER JOIN registration AS T2 ON T1.student_id = T2.student_id INNER JOIN course AS T3 ON T2.course_id = T3.course_id WHERE T3.name = 'Intro to Database 2' ORDER BY T2.sat DESC LIMIT 1
|
[
"Give",
"the",
"student",
"'s",
"last",
"name",
"that",
"gave",
"the",
"highest",
"student",
"satisfaction",
"for",
"the",
"course",
"\"",
"Intro",
"to",
"Database",
"2",
"\"",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Intro to Database 2"
},
{
"id": 6,
"type": "table",
"value": "registration"
},
{
"id": 8,
"type": "column",
"value": "student_id"
},
{
"id": 7,
"type": "column",
"value": "course_id"
},
{
"id": 5,
"type": "table",
"value": "student"
},
{
"id": 0,
"type": "column",
"value": "l_name"
},
{
"id": 1,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "sat"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
16,
17,
18,
19
]
},
{
"entity_id": 4,
"token_idxs": [
3,
4
]
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
13,361
|
car_road_race
|
bird:test.json:1328
|
List all names of drivers in descending alphabetical order.
|
SELECT Driver_Name FROM driver ORDER BY Driver_Name DESC
|
[
"List",
"all",
"names",
"of",
"drivers",
"in",
"descending",
"alphabetical",
"order",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "driver_name"
},
{
"id": 0,
"type": "table",
"value": "driver"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,362
|
chicago_crime
|
bird:train.json:8767
|
Among the incidents in January, 2018, how many of them were stated "against Property" in the FBI classification?
|
SELECT SUM(CASE WHEN SUBSTR(T2.date, 5, 4) = '2018' THEN 1 ELSE 0 END) FROM FBI_Code AS T1 INNER JOIN Crime AS T2 ON T1.fbi_code_no = T2.fbi_code_no WHERE T1.crime_against = 'Property' AND SUBSTR(T2.date, 1, 1) = '1'
|
[
"Among",
"the",
"incidents",
"in",
"January",
",",
"2018",
",",
"how",
"many",
"of",
"them",
"were",
"stated",
"\"",
"against",
"Property",
"\"",
"in",
"the",
"FBI",
"classification",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "crime_against"
},
{
"id": 2,
"type": "column",
"value": "fbi_code_no"
},
{
"id": 0,
"type": "table",
"value": "fbi_code"
},
{
"id": 4,
"type": "value",
"value": "Property"
},
{
"id": 1,
"type": "table",
"value": "crime"
},
{
"id": 7,
"type": "column",
"value": "date"
},
{
"id": 8,
"type": "value",
"value": "2018"
},
{
"id": 5,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "5"
},
{
"id": 10,
"type": "value",
"value": "4"
}
] |
[
{
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},
{
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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15
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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13
]
},
{
"entity_id": 8,
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6
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,363
|
bike_1
|
spider:train_spider.json:158
|
For each zip code, how many times has the maximum wind speed reached 25 mph?
|
SELECT zip_code , count(*) FROM weather WHERE max_wind_Speed_mph >= 25 GROUP BY zip_code
|
[
"For",
"each",
"zip",
"code",
",",
"how",
"many",
"times",
"has",
"the",
"maximum",
"wind",
"speed",
"reached",
"25",
"mph",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "max_wind_speed_mph"
},
{
"id": 1,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 3,
"type": "value",
"value": "25"
}
] |
[
{
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9
]
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{
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10,
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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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
13,364
|
e_learning
|
spider:train_spider.json:3768
|
How many courses are there in total?
|
SELECT count(*) FROM COURSES
|
[
"How",
"many",
"courses",
"are",
"there",
"in",
"total",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "courses"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
13,365
|
race_track
|
spider:train_spider.json:776
|
Return the names of tracks that have no had any races.
|
SELECT name FROM track WHERE track_id NOT IN (SELECT track_id FROM race)
|
[
"Return",
"the",
"names",
"of",
"tracks",
"that",
"have",
"no",
"had",
"any",
"races",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "track_id"
},
{
"id": 0,
"type": "table",
"value": "track"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "table",
"value": "race"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,366
|
restaurant_1
|
spider:train_spider.json:2828
|
List all students' first names and last names who majored in 600.
|
SELECT Fname , Lname FROM Student WHERE Major = 600;
|
[
"List",
"all",
"students",
"'",
"first",
"names",
"and",
"last",
"names",
"who",
"majored",
"in",
"600",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "fname"
},
{
"id": 2,
"type": "column",
"value": "lname"
},
{
"id": 3,
"type": "column",
"value": "major"
},
{
"id": 4,
"type": "value",
"value": "600"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,367
|
art_1
|
bird:test.json:1253
|
What is the unique id of every painter who had a medium oil painting displayed at gallery 240?
|
SELECT DISTINCT painterID FROM paintings WHERE medium = "oil" AND LOCATION = "Gallery 240"
|
[
"What",
"is",
"the",
"unique",
"i",
"d",
"of",
"every",
"painter",
"who",
"had",
"a",
"medium",
"oil",
"painting",
"displayed",
"at",
"gallery",
"240",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "Gallery 240"
},
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 1,
"type": "column",
"value": "painterid"
},
{
"id": 4,
"type": "column",
"value": "location"
},
{
"id": 2,
"type": "column",
"value": "medium"
},
{
"id": 3,
"type": "column",
"value": "oil"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
17,
18
]
},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 10,
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},
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,368
|
soccer_2016
|
bird:train.json:2011
|
What is the venue name of Bandladore?
|
SELECT T1.Venue_Name FROM Venue AS T1 INNER JOIN City AS T2 ON T1.City_ID = T2.City_ID WHERE T2.City_Name = 'Bangalore'
|
[
"What",
"is",
"the",
"venue",
"name",
"of",
"Bandladore",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "venue_name"
},
{
"id": 3,
"type": "column",
"value": "city_name"
},
{
"id": 4,
"type": "value",
"value": "Bangalore"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 1,
"type": "table",
"value": "venue"
},
{
"id": 2,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,370
|
image_and_language
|
bird:train.json:7611
|
What is the average width and height of the objects in image ID 47? List their object classes as well.
|
SELECT T2.OBJ_CLASS, AVG(T1.W), AVG(T1.H) FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T1.IMG_ID = 47 GROUP BY T2.OBJ_CLASS
|
[
"What",
"is",
"the",
"average",
"width",
"and",
"height",
"of",
"the",
"objects",
"in",
"image",
"ID",
"47",
"?",
"List",
"their",
"object",
"classes",
"as",
"well",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "obj_class_id"
},
{
"id": 2,
"type": "table",
"value": "obj_classes"
},
{
"id": 0,
"type": "column",
"value": "obj_class"
},
{
"id": 1,
"type": "table",
"value": "img_obj"
},
{
"id": 3,
"type": "column",
"value": "img_id"
},
{
"id": 4,
"type": "value",
"value": "47"
},
{
"id": 5,
"type": "column",
"value": "w"
},
{
"id": 6,
"type": "column",
"value": "h"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17,
18
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O"
] |
13,371
|
device
|
spider:train_spider.json:5066
|
List the name of the shop with the latest open year.
|
SELECT Shop_Name FROM shop ORDER BY Open_Year DESC LIMIT 1
|
[
"List",
"the",
"name",
"of",
"the",
"shop",
"with",
"the",
"latest",
"open",
"year",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "shop_name"
},
{
"id": 2,
"type": "column",
"value": "open_year"
},
{
"id": 0,
"type": "table",
"value": "shop"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9,
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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,372
|
activity_1
|
spider:train_spider.json:6740
|
In which buildings are there at least ten professors?
|
SELECT building FROM Faculty WHERE rank = "Professor" GROUP BY building HAVING count(*) >= 10
|
[
"In",
"which",
"buildings",
"are",
"there",
"at",
"least",
"ten",
"professors",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Professor"
},
{
"id": 1,
"type": "column",
"value": "building"
},
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 2,
"type": "column",
"value": "rank"
},
{
"id": 4,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
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