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4,451
|
ship_1
|
spider:train_spider.json:6238
|
Find the captain rank that has some captains in both Cutter and Armed schooner classes.
|
SELECT rank FROM captain WHERE CLASS = 'Cutter' INTERSECT SELECT rank FROM captain WHERE CLASS = 'Armed schooner'
|
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{
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"value": "rank"
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"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
12,382
|
soccer_3
|
bird:test.json:21
|
What are the names of players from the club managed by Sam Allardyce?
|
SELECT T2.Name FROM club AS T1 JOIN player AS T2 ON T1.Club_ID = T2.Club_ID WHERE T1.Manager = "Sam Allardyce"
|
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"type": "column",
"value": "club_id"
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"value": "player"
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"type": "column",
"value": "name"
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"value": "club"
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"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
8,179
|
codebase_community
|
bird:dev.json:688
|
Identify the number of posts that have been viewed over 35000 times but have received no comments from other users.
|
SELECT COUNT(Id) FROM posts WHERE ViewCount > 35000 AND CommentCount = 0
|
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"received",
"no",
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"users",
"."
] |
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"value": "commentcount"
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"value": "viewcount"
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"value": "35000"
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"value": "id"
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"value": "0"
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[
"O",
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"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
7,973
|
software_company
|
bird:train.json:8524
|
How many of the first 60,000 customers from the place with the highest average income per month have sent a true response to the incentive mailing sent by the marketing department?
|
SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T2.RESPONSE = 'true' ORDER BY T3.INCOME_K DESC LIMIT 1
|
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
9,246
|
apartment_rentals
|
spider:train_spider.json:1194
|
How many apartment bookings are there in total?
|
SELECT count(*) FROM Apartment_Bookings
|
[
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"?"
] |
[
{
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[
"O",
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"O",
"O",
"O",
"O",
"O"
] |
6,482
|
medicine_enzyme_interaction
|
spider:train_spider.json:975
|
find the number of medicines offered by each trade.
|
SELECT trade_name , count(*) FROM medicine GROUP BY trade_name
|
[
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"."
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[
{
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"type": "column",
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{
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"type": "table",
"value": "medicine"
}
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3,467
|
music_4
|
spider:train_spider.json:6160
|
Give the songs included in volumes that have more than 1 week on top.
|
SELECT Song FROM volume WHERE Weeks_on_Top > 1
|
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"."
] |
[
{
"id": 2,
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{
"id": 0,
"type": "table",
"value": "volume"
},
{
"id": 1,
"type": "column",
"value": "song"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
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"O",
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"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
3,150
|
assets_maintenance
|
spider:train_spider.json:3133
|
List all every engineer's first name, last name, details and coresponding skill description.
|
SELECT T1.first_name , T1.last_name , T1.other_details , T3.skill_description FROM Maintenance_Engineers AS T1 JOIN Engineer_Skills AS T2 ON T1.engineer_id = T2.engineer_id JOIN Skills AS T3 ON T2.skill_id = T3.skill_id
|
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"."
] |
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{
"id": 5,
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"type": "column",
"value": "skill_description"
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{
"id": 6,
"type": "table",
"value": "engineer_skills"
},
{
"id": 2,
"type": "column",
"value": "other_details"
},
{
"id": 8,
"type": "column",
"value": "engineer_id"
},
{
"id": 0,
"type": "column",
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{
"id": 1,
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"value": "last_name"
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{
"id": 7,
"type": "column",
"value": "skill_id"
},
{
"id": 4,
"type": "table",
"value": "skills"
}
] |
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"O",
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"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
10,794
|
simpson_episodes
|
bird:train.json:4306
|
How many people were not born in Connecticut, USA?
|
SELECT COUNT(name) FROM Person WHERE birth_region != 'Connecticut' AND birth_country != 'USA';
|
[
"How",
"many",
"people",
"were",
"not",
"born",
"in",
"Connecticut",
",",
"USA",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "birth_country"
},
{
"id": 2,
"type": "column",
"value": "birth_region"
},
{
"id": 3,
"type": "value",
"value": "Connecticut"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "value",
"value": "USA"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
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7
]
},
{
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},
{
"entity_id": 5,
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9
]
},
{
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},
{
"entity_id": 7,
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{
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},
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},
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},
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
5,539
|
baseball_1
|
spider:train_spider.json:3656
|
Find the average height of the players who belong to the college called 'Yale University'.
|
SELECT avg(T1.height) FROM player AS T1 JOIN player_college AS T2 ON T1.player_id = T2.player_id JOIN college AS T3 ON T3.college_id = T2.college_id WHERE T3.name_full = 'Yale University';
|
[
"Find",
"the",
"average",
"height",
"of",
"the",
"players",
"who",
"belong",
"to",
"the",
"college",
"called",
"'",
"Yale",
"University",
"'",
"."
] |
[
{
"id": 2,
"type": "value",
"value": "Yale University"
},
{
"id": 5,
"type": "table",
"value": "player_college"
},
{
"id": 6,
"type": "column",
"value": "college_id"
},
{
"id": 1,
"type": "column",
"value": "name_full"
},
{
"id": 7,
"type": "column",
"value": "player_id"
},
{
"id": 0,
"type": "table",
"value": "college"
},
{
"id": 3,
"type": "column",
"value": "height"
},
{
"id": 4,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
14,
15
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
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6
]
},
{
"entity_id": 5,
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},
{
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
3,673
|
works_cycles
|
bird:train.json:7326
|
List the person who owns a distinguish credt card.
|
SELECT T3.FirstName, T3.LastName FROM CreditCard AS T1 INNER JOIN PersonCreditCard AS T2 ON T1.CreditCardID = T2.CreditCardID INNER JOIN Person AS T3 ON T2.BusinessEntityID = T3.BusinessEntityID WHERE T1.CardType = 'Distinguish'
|
[
"List",
"the",
"person",
"who",
"owns",
"a",
"distinguish",
"credt",
"card",
"."
] |
[
{
"id": 6,
"type": "table",
"value": "personcreditcard"
},
{
"id": 7,
"type": "column",
"value": "businessentityid"
},
{
"id": 8,
"type": "column",
"value": "creditcardid"
},
{
"id": 4,
"type": "value",
"value": "Distinguish"
},
{
"id": 5,
"type": "table",
"value": "creditcard"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "column",
"value": "cardtype"
},
{
"id": 2,
"type": "table",
"value": "person"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"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": []
}
] |
[
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"B-COLUMN",
"O"
] |
14,387
|
pilot_1
|
bird:test.json:1171
|
List in alphabetic order the names of pilots whose age is greater than some pilots having plane Piper Cub.
|
SELECT pilot_name FROM pilotskills WHERE age > (SELECT min(age) FROM pilotskills WHERE plane_name = 'Piper Cub') ORDER BY pilot_name
|
[
"List",
"in",
"alphabetic",
"order",
"the",
"names",
"of",
"pilots",
"whose",
"age",
"is",
"greater",
"than",
"some",
"pilots",
"having",
"plane",
"Piper",
"Cub",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 1,
"type": "column",
"value": "pilot_name"
},
{
"id": 3,
"type": "column",
"value": "plane_name"
},
{
"id": 4,
"type": "value",
"value": "Piper Cub"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
5,
7
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
17,
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
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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",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O"
] |
2,780
|
california_schools
|
bird:dev.json:49
|
Which different county has the most number of closed schools? Please provide the name of each school as well as the closure date.
|
SELECT DISTINCT County, School, ClosedDate FROM schools WHERE County = ( SELECT County FROM schools WHERE StatusType = 'Closed' GROUP BY County ORDER BY COUNT(School) DESC LIMIT 1 ) AND StatusType = 'Closed' AND school IS NOT NULL
|
[
"Which",
"different",
"county",
"has",
"the",
"most",
"number",
"of",
"closed",
"schools",
"?",
"Please",
"provide",
"the",
"name",
"of",
"each",
"school",
"as",
"well",
"as",
"the",
"closure",
"date",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "closeddate"
},
{
"id": 4,
"type": "column",
"value": "statustype"
},
{
"id": 0,
"type": "table",
"value": "schools"
},
{
"id": 1,
"type": "column",
"value": "county"
},
{
"id": 2,
"type": "column",
"value": "school"
},
{
"id": 5,
"type": "value",
"value": "Closed"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
17
]
},
{
"entity_id": 3,
"token_idxs": [
22,
23
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,909
|
university
|
bird:train.json:8004
|
Between 2011 to 2016, in which countries can you find the universities where at least 50% of its students are international students?
|
SELECT DISTINCT T3.country_name FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id INNER JOIN country AS T3 ON T3.id = T1.country_id WHERE T2.pct_international_students > 50 AND T2.year BETWEEN 2011 AND 2016
|
[
"Between",
"2011",
"to",
"2016",
",",
"in",
"which",
"countries",
"can",
"you",
"find",
"the",
"universities",
"where",
"at",
"least",
"50",
"%",
"of",
"its",
"students",
"are",
"international",
"students",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "pct_international_students"
},
{
"id": 3,
"type": "table",
"value": "university_year"
},
{
"id": 11,
"type": "column",
"value": "university_id"
},
{
"id": 0,
"type": "column",
"value": "country_name"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 9,
"type": "value",
"value": "2011"
},
{
"id": 10,
"type": "value",
"value": "2016"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,146
|
video_game
|
bird:test.json:1943
|
How many players have rank of the year smaller than 3?
|
SELECT count(*) FROM player WHERE Rank_of_the_year <= 3
|
[
"How",
"many",
"players",
"have",
"rank",
"of",
"the",
"year",
"smaller",
"than",
"3",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "rank_of_the_year"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 2,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5,
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
1,193
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4181
|
How many locations are listed in the database?
|
SELECT count(*) FROM Ref_locations
|
[
"How",
"many",
"locations",
"are",
"listed",
"in",
"the",
"database",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "ref_locations"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,143
|
movie_3
|
bird:train.json:9392
|
What films did Burt Dukakis got star in?
|
SELECT T3.title 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 T2.first_name = 'BURT' AND T2.last_name = 'DUKAKIS'
|
[
"What",
"films",
"did",
"Burt",
"Dukakis",
"got",
"star",
"in",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "film_actor"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 9,
"type": "column",
"value": "actor_id"
},
{
"id": 4,
"type": "column",
"value": "film_id"
},
{
"id": 8,
"type": "value",
"value": "DUKAKIS"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "actor"
},
{
"id": 1,
"type": "table",
"value": "film"
},
{
"id": 6,
"type": "value",
"value": "BURT"
}
] |
[
{
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},
{
"entity_id": 1,
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1
]
},
{
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},
{
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},
{
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},
{
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},
{
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3
]
},
{
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},
{
"entity_id": 8,
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4
]
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{
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{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
8,900
|
university
|
bird:train.json:8032
|
Provide the ID of the university with the highest percentage of female students in 2012.
|
SELECT university_id FROM university_year WHERE year = 2012 ORDER BY pct_female_students DESC LIMIT 1
|
[
"Provide",
"the",
"ID",
"of",
"the",
"university",
"with",
"the",
"highest",
"percentage",
"of",
"female",
"students",
"in",
"2012",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "pct_female_students"
},
{
"id": 0,
"type": "table",
"value": "university_year"
},
{
"id": 1,
"type": "column",
"value": "university_id"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2012"
}
] |
[
{
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},
{
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2,
5
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{
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},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
9,
11,
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
7,612
|
movie_1
|
spider:train_spider.json:2469
|
What are the names of all movies that were created after the most recent Steven Spielberg film?
|
SELECT title FROM Movie WHERE YEAR > (SELECT max(YEAR) FROM Movie WHERE director = "Steven Spielberg")
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"movies",
"that",
"were",
"created",
"after",
"the",
"most",
"recent",
"Steven",
"Spielberg",
"film",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "Steven Spielberg"
},
{
"id": 3,
"type": "column",
"value": "director"
},
{
"id": 0,
"type": "table",
"value": "movie"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
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},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
3,492
|
talkingdata
|
bird:train.json:1111
|
Provide the total number of the male users that use OPPO as their phone brand.
|
SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T2.phone_brand = 'OPPO' AND T1.gender = 'M'
|
[
"Provide",
"the",
"total",
"number",
"of",
"the",
"male",
"users",
"that",
"use",
"OPPO",
"as",
"their",
"phone",
"brand",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 3,
"type": "column",
"value": "phone_brand"
},
{
"id": 0,
"type": "table",
"value": "gender_age"
},
{
"id": 2,
"type": "column",
"value": "device_id"
},
{
"id": 5,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "value",
"value": "OPPO"
},
{
"id": 6,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
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6
]
},
{
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},
{
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},
{
"entity_id": 4,
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9
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,161
|
donor
|
bird:train.json:3228
|
State the number of public magnet schools in New York Manhattan.
|
SELECT COUNT(schoolid) FROM projects WHERE school_county = 'New York (Manhattan)' AND school_magnet = 't'
|
[
"State",
"the",
"number",
"of",
"public",
"magnet",
"schools",
"in",
"New",
"York",
"Manhattan",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "New York (Manhattan)"
},
{
"id": 2,
"type": "column",
"value": "school_county"
},
{
"id": 4,
"type": "column",
"value": "school_magnet"
},
{
"id": 0,
"type": "table",
"value": "projects"
},
{
"id": 1,
"type": "column",
"value": "schoolid"
},
{
"id": 5,
"type": "value",
"value": "t"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,144
|
book_1
|
bird:test.json:577
|
What is the title of the book written by Plato has price lower than the average sale price of all books?
|
SELECT T1.title FROM Book AS T1 JOIN Author_book AS T2 ON T1.isbn = T2.isbn JOIN Author AS T3 ON T2.Author = T3.idAuthor WHERE T3.name = "Plato" AND T1.saleprice < (SELECT avg(saleprice) FROM Book)
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"book",
"written",
"by",
"Plato",
"has",
"price",
"lower",
"than",
"the",
"average",
"sale",
"price",
"of",
"all",
"books",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "author_book"
},
{
"id": 8,
"type": "column",
"value": "saleprice"
},
{
"id": 5,
"type": "column",
"value": "idauthor"
},
{
"id": 1,
"type": "table",
"value": "author"
},
{
"id": 4,
"type": "column",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 7,
"type": "column",
"value": "Plato"
},
{
"id": 2,
"type": "table",
"value": "book"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 9,
"type": "column",
"value": "isbn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
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15
]
},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
5,155
|
toxicology
|
bird:dev.json:252
|
What are the atoms that can bond with the atom that has the element lead?
|
SELECT T2.atom_id, T2.atom_id2 FROM atom AS T1 INNER JOIN connected AS T2 ON T1.atom_id = T2.atom_id WHERE T1.element = 'pb'
|
[
"What",
"are",
"the",
"atoms",
"that",
"can",
"bond",
"with",
"the",
"atom",
"that",
"has",
"the",
"element",
"lead",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "connected"
},
{
"id": 1,
"type": "column",
"value": "atom_id2"
},
{
"id": 0,
"type": "column",
"value": "atom_id"
},
{
"id": 4,
"type": "column",
"value": "element"
},
{
"id": 2,
"type": "table",
"value": "atom"
},
{
"id": 5,
"type": "value",
"value": "pb"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
11,490
|
shooting
|
bird:train.json:2462
|
What is the percentage of the cases involved more than 3 officers from year 2010 to 2015?
|
SELECT CAST(SUM(IIF(officer_count > 3, 1, 0)) AS REAL) * 100 / COUNT(case_number) FROM incidents WHERE STRFTIME('%Y', date) BETWEEN '2010' AND '2015'
|
[
"What",
"is",
"the",
"percentage",
"of",
"the",
"cases",
"involved",
"more",
"than",
"3",
"officers",
"from",
"year",
"2010",
"to",
"2015",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "officer_count"
},
{
"id": 6,
"type": "column",
"value": "case_number"
},
{
"id": 0,
"type": "table",
"value": "incidents"
},
{
"id": 1,
"type": "value",
"value": "2010"
},
{
"id": 2,
"type": "value",
"value": "2015"
},
{
"id": 4,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "%Y"
},
{
"id": 7,
"type": "value",
"value": "1"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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6
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": [
10
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
12,612
|
voter_2
|
spider:train_spider.json:5484
|
Find the first and last name of all the students of age 18 who have vice president votes.
|
SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_President_VOTE WHERE T1.age = 18
|
[
"Find",
"the",
"first",
"and",
"last",
"name",
"of",
"all",
"the",
"students",
"of",
"age",
"18",
"who",
"have",
"vice",
"president",
"votes",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "vice_president_vote"
},
{
"id": 3,
"type": "table",
"value": "voting_record"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 6,
"type": "column",
"value": "stuid"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "value",
"value": "18"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
15,
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O"
] |
11,274
|
game_1
|
spider:train_spider.json:5975
|
Show all video games and their types in the order of their names.
|
SELECT gname , gtype FROM Video_games ORDER BY gname
|
[
"Show",
"all",
"video",
"games",
"and",
"their",
"types",
"in",
"the",
"order",
"of",
"their",
"names",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "video_games"
},
{
"id": 1,
"type": "column",
"value": "gname"
},
{
"id": 2,
"type": "column",
"value": "gtype"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
9,173
|
address
|
bird:train.json:5159
|
Provide the average elevation of the cities with alias Amherst.
|
SELECT AVG(T2.elevation) FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.alias = 'Amherst'
|
[
"Provide",
"the",
"average",
"elevation",
"of",
"the",
"cities",
"with",
"alias",
"Amherst",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "elevation"
},
{
"id": 1,
"type": "table",
"value": "zip_data"
},
{
"id": 5,
"type": "column",
"value": "zip_code"
},
{
"id": 3,
"type": "value",
"value": "Amherst"
},
{
"id": 0,
"type": "table",
"value": "alias"
},
{
"id": 2,
"type": "column",
"value": "alias"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
711
|
document_management
|
spider:train_spider.json:4517
|
What are all the section titles of the document named "David CV"?
|
SELECT t2.section_title FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code WHERE t1.document_name = "David CV"
|
[
"What",
"are",
"all",
"the",
"section",
"titles",
"of",
"the",
"document",
"named",
"\"",
"David",
"CV",
"\"",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "document_sections"
},
{
"id": 0,
"type": "column",
"value": "section_title"
},
{
"id": 3,
"type": "column",
"value": "document_name"
},
{
"id": 5,
"type": "column",
"value": "document_code"
},
{
"id": 1,
"type": "table",
"value": "documents"
},
{
"id": 4,
"type": "column",
"value": "David CV"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
15,819
|
airline
|
bird:train.json:5895
|
What is the air carrier's description of the cancelled flights?
|
SELECT T1.Description FROM `Air Carriers` AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.OP_CARRIER_AIRLINE_ID WHERE T2.CANCELLED = 1 GROUP BY T1.Description
|
[
"What",
"is",
"the",
"air",
"carrier",
"'s",
"description",
"of",
"the",
"cancelled",
"flights",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 1,
"type": "table",
"value": "Air Carriers"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 3,
"type": "column",
"value": "cancelled"
},
{
"id": 2,
"type": "table",
"value": "airlines"
},
{
"id": 5,
"type": "column",
"value": "code"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,840
|
flight_company
|
spider:train_spider.json:6378
|
How many airports haven't the pilot 'Thompson' driven an aircraft?
|
SELECT count(*) FROM airport WHERE id NOT IN ( SELECT airport_id FROM flight WHERE pilot = 'Thompson' );
|
[
"How",
"many",
"airports",
"have",
"n't",
"the",
"pilot",
"'",
"Thompson",
"'",
"driven",
"an",
"aircraft",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "airport_id"
},
{
"id": 5,
"type": "value",
"value": "Thompson"
},
{
"id": 0,
"type": "table",
"value": "airport"
},
{
"id": 2,
"type": "table",
"value": "flight"
},
{
"id": 4,
"type": "column",
"value": "pilot"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"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": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
4,012
|
customers_and_orders
|
bird:test.json:272
|
What are the ids and names of all customers?
|
SELECT customer_id , customer_name FROM Customers
|
[
"What",
"are",
"the",
"ids",
"and",
"names",
"of",
"all",
"customers",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "customer_name"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
14,608
|
cre_Students_Information_Systems
|
bird:test.json:465
|
Which students have gone through any event? List the students' biographical data and event date.
|
SELECT T1.bio_data , T2.event_date FROM Students AS T1 JOIN Student_Events AS T2 ON T1.student_id = T2.student_id
|
[
"Which",
"students",
"have",
"gone",
"through",
"any",
"event",
"?",
"List",
"the",
"students",
"'",
"biographical",
"data",
"and",
"event",
"date",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "student_events"
},
{
"id": 1,
"type": "column",
"value": "event_date"
},
{
"id": 4,
"type": "column",
"value": "student_id"
},
{
"id": 0,
"type": "column",
"value": "bio_data"
},
{
"id": 2,
"type": "table",
"value": "students"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12,
13
]
},
{
"entity_id": 1,
"token_idxs": [
15,
16
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
11,489
|
california_schools
|
bird:dev.json:32
|
What is the eligible free or reduced price meal rate for the top 5 schools in grades 1-12 with the highest free or reduced price meal count of the schools with the ownership code 66?
|
SELECT CAST(T1.`FRPM Count (K-12)` AS REAL) / T1.`Enrollment (K-12)` FROM frpm AS T1 INNER JOIN schools AS T2 ON T1.CDSCode = T2.CDSCode WHERE T2.SOC = 66 ORDER BY T1.`FRPM Count (K-12)` DESC LIMIT 5
|
[
"What",
"is",
"the",
"eligible",
"free",
"or",
"reduced",
"price",
"meal",
"rate",
"for",
"the",
"top",
"5",
"schools",
"in",
"grades",
"1",
"-",
"12",
"with",
"the",
"highest",
"free",
"or",
"reduced",
"price",
"meal",
"count",
"of",
"the",
"schools",
"with",
"the",
"ownership",
"code",
"66",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "FRPM Count (K-12)"
},
{
"id": 5,
"type": "column",
"value": "Enrollment (K-12)"
},
{
"id": 1,
"type": "table",
"value": "schools"
},
{
"id": 6,
"type": "column",
"value": "cdscode"
},
{
"id": 0,
"type": "table",
"value": "frpm"
},
{
"id": 2,
"type": "column",
"value": "soc"
},
{
"id": 3,
"type": "value",
"value": "66"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
36
]
},
{
"entity_id": 4,
"token_idxs": [
27,
28
]
},
{
"entity_id": 5,
"token_idxs": [
17,
18,
19
]
},
{
"entity_id": 6,
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},
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},
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,579
|
soccer_2
|
spider:train_spider.json:5037
|
What is the count of states with college students playing in the mid position but not as goalies?
|
SELECT COUNT(*) FROM (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')
|
[
"What",
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"the",
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"states",
"with",
"college",
"students",
"playing",
"in",
"the",
"mid",
"position",
"but",
"not",
"as",
"goalies",
"?"
] |
[
{
"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"
}
] |
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{
"entity_id": 0,
"token_idxs": [
5
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]
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{
"entity_id": 18,
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}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
8,308
|
apartment_rentals
|
spider:train_spider.json:1229
|
Which apartments have bookings with status code "Confirmed"? Return their apartment numbers.
|
SELECT DISTINCT T2.apt_number FROM Apartment_Bookings AS T1 JOIN Apartments AS T2 ON T1.apt_id = T2.apt_id WHERE T1.booking_status_code = "Confirmed"
|
[
"Which",
"apartments",
"have",
"bookings",
"with",
"status",
"code",
"\"",
"Confirmed",
"\"",
"?",
"Return",
"their",
"apartment",
"numbers",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "booking_status_code"
},
{
"id": 1,
"type": "table",
"value": "apartment_bookings"
},
{
"id": 0,
"type": "column",
"value": "apt_number"
},
{
"id": 2,
"type": "table",
"value": "apartments"
},
{
"id": 4,
"type": "column",
"value": "Confirmed"
},
{
"id": 5,
"type": "column",
"value": "apt_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
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{
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3
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1
]
},
{
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5,
6
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{
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8
]
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{
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13
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
15,440
|
music_4
|
spider:train_spider.json:6192
|
What are the famous titles of artists who have not only had volumes that spent more than 2 weeks on top but also volumes that spent less than 2 weeks on top?
|
SELECT T1.Famous_Title FROM artist AS T1 JOIN volume AS T2 ON T1.Artist_ID = T2.Artist_ID WHERE T2.Weeks_on_Top > 2 INTERSECT SELECT T1.Famous_Title FROM artist AS T1 JOIN volume AS T2 ON T1.Artist_ID = T2.Artist_ID WHERE T2.Weeks_on_Top < 2
|
[
"What",
"are",
"the",
"famous",
"titles",
"of",
"artists",
"who",
"have",
"not",
"only",
"had",
"volumes",
"that",
"spent",
"more",
"than",
"2",
"weeks",
"on",
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"but",
"also",
"volumes",
"that",
"spent",
"less",
"than",
"2",
"weeks",
"on",
"top",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "famous_title"
},
{
"id": 3,
"type": "column",
"value": "weeks_on_top"
},
{
"id": 5,
"type": "column",
"value": "artist_id"
},
{
"id": 1,
"type": "table",
"value": "artist"
},
{
"id": 2,
"type": "table",
"value": "volume"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
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{
"entity_id": 0,
"token_idxs": []
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"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
15
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{
"entity_id": 3,
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7
]
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{
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{
"entity_id": 5,
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{
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,659
|
financial
|
bird:dev.json:159
|
List all the withdrawals in cash transactions that the client with the id 3356 makes.
|
SELECT T4.trans_id FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T3 ON T2.account_id = T3.account_id INNER JOIN trans AS T4 ON T3.account_id = T4.account_id WHERE T1.client_id = 3356 AND T4.operation = 'VYBER'
|
[
"List",
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"the",
"withdrawals",
"in",
"cash",
"transactions",
"that",
"the",
"client",
"with",
"the",
"i",
"d",
"3356",
"makes",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "account_id"
},
{
"id": 4,
"type": "column",
"value": "client_id"
},
{
"id": 6,
"type": "column",
"value": "operation"
},
{
"id": 0,
"type": "column",
"value": "trans_id"
},
{
"id": 2,
"type": "table",
"value": "account"
},
{
"id": 8,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "table",
"value": "trans"
},
{
"id": 7,
"type": "value",
"value": "VYBER"
},
{
"id": 5,
"type": "value",
"value": "3356"
},
{
"id": 9,
"type": "table",
"value": "disp"
}
] |
[
{
"entity_id": 0,
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6
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12,
13
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},
{
"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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9
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O"
] |
5,442
|
formula_1
|
spider:train_spider.json:2162
|
What are the forenames and surnames of all unique drivers who had a lap time of less than 93000 milliseconds?
|
SELECT DISTINCT T1.forename , T1.surname FROM drivers AS T1 JOIN laptimes AS T2 ON T1.driverid = T2.driverid WHERE T2.milliseconds < 93000
|
[
"What",
"are",
"the",
"forenames",
"and",
"surnames",
"of",
"all",
"unique",
"drivers",
"who",
"had",
"a",
"lap",
"time",
"of",
"less",
"than",
"93000",
"milliseconds",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "milliseconds"
},
{
"id": 0,
"type": "column",
"value": "forename"
},
{
"id": 3,
"type": "table",
"value": "laptimes"
},
{
"id": 6,
"type": "column",
"value": "driverid"
},
{
"id": 1,
"type": "column",
"value": "surname"
},
{
"id": 2,
"type": "table",
"value": "drivers"
},
{
"id": 5,
"type": "value",
"value": "93000"
}
] |
[
{
"entity_id": 0,
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3
]
},
{
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5
]
},
{
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9
]
},
{
"entity_id": 3,
"token_idxs": [
13,
14
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},
{
"entity_id": 4,
"token_idxs": [
19
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},
{
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18
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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": 16,
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},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
158
|
coinmarketcap
|
bird:train.json:6270
|
Which crytocurrency was traded in the highest value on 2016/1/8?
|
SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.date = '2016-01-08' AND T2.volume_24h = ( SELECT MAX(volume_24h) FROM historical WHERE date = '2016-01-08' )
|
[
"Which",
"crytocurrency",
"was",
"traded",
"in",
"the",
"highest",
"value",
"on",
"2016/1/8",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 6,
"type": "value",
"value": "2016-01-08"
},
{
"id": 7,
"type": "column",
"value": "volume_24h"
},
{
"id": 4,
"type": "column",
"value": "coin_id"
},
{
"id": 1,
"type": "table",
"value": "coins"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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9
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},
{
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},
{
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},
{
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},
{
"entity_id": 10,
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
520
|
wine_1
|
spider:train_spider.json:6562
|
What are the names of wines, sorted by price ascending?
|
SELECT DISTINCT Name FROM WINE ORDER BY price
|
[
"What",
"are",
"the",
"names",
"of",
"wines",
",",
"sorted",
"by",
"price",
"ascending",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "table",
"value": "wine"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
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3
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},
{
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9
]
},
{
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},
{
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},
{
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},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
6,211
|
formula_1
|
bird:dev.json:913
|
In which country can I find the circuit with the highest altitude?
|
SELECT country FROM circuits ORDER BY alt DESC LIMIT 1
|
[
"In",
"which",
"country",
"can",
"I",
"find",
"the",
"circuit",
"with",
"the",
"highest",
"altitude",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "circuits"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "alt"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
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11
]
},
{
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
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},
{
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},
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,036
|
works_cycles
|
bird:train.json:7099
|
What type of transaction was made with the only yellow product, size 62 and with a minimum inventory stock of 500 units?
|
SELECT DISTINCT T2.TransactionType FROM Product AS T1 INNER JOIN TransactionHistory AS T2 ON T1.ProductID = T2.ProductID WHERE T1.Size = 62 AND T1.Color = 'Yellow' AND T1.SafetyStockLevel = 500
|
[
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"type",
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"transaction",
"was",
"made",
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"yellow",
"product",
",",
"size",
"62",
"and",
"with",
"a",
"minimum",
"inventory",
"stock",
"of",
"500",
"units",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "transactionhistory"
},
{
"id": 8,
"type": "column",
"value": "safetystocklevel"
},
{
"id": 0,
"type": "column",
"value": "transactiontype"
},
{
"id": 3,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "table",
"value": "product"
},
{
"id": 7,
"type": "value",
"value": "Yellow"
},
{
"id": 6,
"type": "column",
"value": "color"
},
{
"id": 4,
"type": "column",
"value": "size"
},
{
"id": 9,
"type": "value",
"value": "500"
},
{
"id": 5,
"type": "value",
"value": "62"
}
] |
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{
"entity_id": 0,
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1,
2,
3
]
},
{
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10
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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": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
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"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
11,526
|
manufactory_1
|
spider:train_spider.json:5295
|
What are the names of products produced by both Creative Labs and Sony?
|
SELECT T1.name FROM products AS T1 JOIN manufacturers AS T2 ON T1.Manufacturer = T2.code WHERE T2.name = 'Creative Labs' INTERSECT SELECT T1.name FROM products AS T1 JOIN manufacturers AS T2 ON T1.Manufacturer = T2.code WHERE T2.name = 'Sony'
|
[
"What",
"are",
"the",
"names",
"of",
"products",
"produced",
"by",
"both",
"Creative",
"Labs",
"and",
"Sony",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "manufacturers"
},
{
"id": 3,
"type": "value",
"value": "Creative Labs"
},
{
"id": 5,
"type": "column",
"value": "manufacturer"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "Sony"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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5
]
},
{
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{
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10
]
},
{
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12
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},
{
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{
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},
{
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{
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{
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},
{
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},
{
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
1,232
|
beer_factory
|
bird:train.json:5272
|
Which brand of root beer did Jayne Collins give the lowest rating?
|
SELECT T3.BrandName FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeerbrand AS T3 ON T2.BrandID = T3.BrandID WHERE T1.First = 'Jayne' AND T1.Last = 'Collins' AND T2.StarRating = 1
|
[
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"of",
"root",
"beer",
"did",
"Jayne",
"Collins",
"give",
"the",
"lowest",
"rating",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "rootbeerreview"
},
{
"id": 1,
"type": "table",
"value": "rootbeerbrand"
},
{
"id": 9,
"type": "column",
"value": "starrating"
},
{
"id": 11,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "column",
"value": "brandname"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "brandid"
},
{
"id": 8,
"type": "value",
"value": "Collins"
},
{
"id": 5,
"type": "column",
"value": "first"
},
{
"id": 6,
"type": "value",
"value": "Jayne"
},
{
"id": 7,
"type": "column",
"value": "last"
},
{
"id": 10,
"type": "value",
"value": "1"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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3,
4
]
},
{
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{
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{
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1
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{
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{
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},
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"entity_id": 14,
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
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"I-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
3,456
|
codebase_comments
|
bird:train.json:605
|
List the summary of the method "Castle.MonoRail.Framework.Test.StubViewComponentContext.RenderSection".
|
SELECT DISTINCT Summary FROM Method WHERE Name = 'Castle.MonoRail.Framework.Test.StubViewComponentContext.RenderSection'
|
[
"List",
"the",
"summary",
"of",
"the",
"method",
"\"",
"Castle",
".",
"MonoRail",
".",
"Framework",
".",
"Test",
".",
"StubViewComponentContext",
".",
"RenderSection",
"\"",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Castle.MonoRail.Framework.Test.StubViewComponentContext.RenderSection"
},
{
"id": 1,
"type": "column",
"value": "summary"
},
{
"id": 0,
"type": "table",
"value": "method"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
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5
]
},
{
"entity_id": 1,
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2
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{
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{
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9,
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16,
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{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
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"entity_id": 11,
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},
{
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},
{
"entity_id": 13,
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},
{
"entity_id": 14,
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},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
9,064
|
music_1
|
spider:train_spider.json:3587
|
What is the language that was used most often in songs with resolution above 500?
|
SELECT artist_name FROM song WHERE resolution > 500 GROUP BY languages ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"language",
"that",
"was",
"used",
"most",
"often",
"in",
"songs",
"with",
"resolution",
"above",
"500",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "artist_name"
},
{
"id": 3,
"type": "column",
"value": "resolution"
},
{
"id": 1,
"type": "column",
"value": "languages"
},
{
"id": 0,
"type": "table",
"value": "song"
},
{
"id": 4,
"type": "value",
"value": "500"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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13
]
},
{
"entity_id": 3,
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14
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
5
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
4,506
|
computer_student
|
bird:train.json:979
|
Find the ID of advisor of student ID 80 and state the level of courses taught by him/her.
|
SELECT T1.p_id_dummy, T2.courseLevel FROM advisedBy AS T1 INNER JOIN course AS T2 ON T1.p_id = T2.course_id INNER JOIN taughtBy AS T3 ON T2.course_id = T3.course_id WHERE T1.p_id = 80
|
[
"Find",
"the",
"ID",
"of",
"advisor",
"of",
"student",
"ID",
"80",
"and",
"state",
"the",
"level",
"of",
"courses",
"taught",
"by",
"him",
"/",
"her",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "courselevel"
},
{
"id": 0,
"type": "column",
"value": "p_id_dummy"
},
{
"id": 5,
"type": "table",
"value": "advisedby"
},
{
"id": 7,
"type": "column",
"value": "course_id"
},
{
"id": 2,
"type": "table",
"value": "taughtby"
},
{
"id": 6,
"type": "table",
"value": "course"
},
{
"id": 3,
"type": "column",
"value": "p_id"
},
{
"id": 4,
"type": "value",
"value": "80"
}
] |
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{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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12
]
},
{
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15,
16
]
},
{
"entity_id": 3,
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7
]
},
{
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8
]
},
{
"entity_id": 5,
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4
]
},
{
"entity_id": 6,
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14
]
},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"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",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O"
] |
13,948
|
voter_2
|
spider:train_spider.json:5444
|
Find the number of students in total.
|
SELECT count(*) FROM STUDENT
|
[
"Find",
"the",
"number",
"of",
"students",
"in",
"total",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "student"
}
] |
[
{
"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": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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"
] |
3,582
|
sales_in_weather
|
bird:train.json:8213
|
How many units are being sold for item 1 when the average temperature is 83?
|
SELECT SUM(units) FROM weather AS T1 INNER JOIN sales_in_weather AS T2 ON T1.`date` = T2.`date` INNER JOIN relation AS T3 ON T2.store_nbr = T3.store_nbr WHERE T2.item_nbr = 1 AND T1.tavg = 83
|
[
"How",
"many",
"units",
"are",
"being",
"sold",
"for",
"item",
"1",
"when",
"the",
"average",
"temperature",
"is",
"83",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "sales_in_weather"
},
{
"id": 4,
"type": "column",
"value": "store_nbr"
},
{
"id": 0,
"type": "table",
"value": "relation"
},
{
"id": 5,
"type": "column",
"value": "item_nbr"
},
{
"id": 2,
"type": "table",
"value": "weather"
},
{
"id": 1,
"type": "column",
"value": "units"
},
{
"id": 7,
"type": "column",
"value": "tavg"
},
{
"id": 9,
"type": "column",
"value": "date"
},
{
"id": 8,
"type": "value",
"value": "83"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": [
14
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
11,830
|
movie_platform
|
bird:train.json:142
|
Provide list titles created by user who are eligible for trial when he created the list.
|
SELECT DISTINCT T2.list_title FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T1.user_eligible_for_trial = 1
|
[
"Provide",
"list",
"titles",
"created",
"by",
"user",
"who",
"are",
"eligible",
"for",
"trial",
"when",
"he",
"created",
"the",
"list",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "user_eligible_for_trial"
},
{
"id": 1,
"type": "table",
"value": "lists_users"
},
{
"id": 0,
"type": "column",
"value": "list_title"
},
{
"id": 5,
"type": "column",
"value": "list_id"
},
{
"id": 2,
"type": "table",
"value": "lists"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
8,785
|
synthea
|
bird:train.json:1425
|
Who had to take Clopidogrel 75 MG Oral Tablet for over 10 years?
|
SELECT T1.first, T1.last FROM patients AS T1 INNER JOIN medications AS T2 ON T1.patient = T2.PATIENT WHERE T2.DESCRIPTION = 'Clopidogrel 75 MG Oral Tablet' AND strftime('%Y', T2.STOP) - strftime('%Y', T2.START) > 10
|
[
"Who",
"had",
"to",
"take",
"Clopidogrel",
"75",
"MG",
"Oral",
"Tablet",
"for",
"over",
"10",
"years",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Clopidogrel 75 MG Oral Tablet"
},
{
"id": 3,
"type": "table",
"value": "medications"
},
{
"id": 5,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "patients"
},
{
"id": 4,
"type": "column",
"value": "patient"
},
{
"id": 0,
"type": "column",
"value": "first"
},
{
"id": 10,
"type": "column",
"value": "start"
},
{
"id": 1,
"type": "column",
"value": "last"
},
{
"id": 9,
"type": "column",
"value": "stop"
},
{
"id": 7,
"type": "value",
"value": "10"
},
{
"id": 8,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4,
5,
6,
7
]
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": [
12
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
4,673
|
books
|
bird:train.json:6050
|
Who is the author of the book The Mystery in the Rocky Mountains?
|
SELECT T3.author_name FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T1.title = 'The Mystery in the Rocky Mountains'
|
[
"Who",
"is",
"the",
"author",
"of",
"the",
"book",
"The",
"Mystery",
"in",
"the",
"Rocky",
"Mountains",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "The Mystery in the Rocky Mountains"
},
{
"id": 0,
"type": "column",
"value": "author_name"
},
{
"id": 5,
"type": "table",
"value": "book_author"
},
{
"id": 6,
"type": "column",
"value": "author_id"
},
{
"id": 7,
"type": "column",
"value": "book_id"
},
{
"id": 1,
"type": "table",
"value": "author"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9,
10,
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,049
|
retail_world
|
bird:train.json:6612
|
How many orders were shipped via Federal Shipping?
|
SELECT COUNT(T1.OrderID) FROM Orders AS T1 INNER JOIN Shippers AS T2 ON T1.ShipVia = T2.ShipperID WHERE T2.CompanyName = 'Federal Shipping' AND T1.ShipVia = 3
|
[
"How",
"many",
"orders",
"were",
"shipped",
"via",
"Federal",
"Shipping",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Federal Shipping"
},
{
"id": 5,
"type": "column",
"value": "companyname"
},
{
"id": 4,
"type": "column",
"value": "shipperid"
},
{
"id": 1,
"type": "table",
"value": "shippers"
},
{
"id": 2,
"type": "column",
"value": "orderid"
},
{
"id": 3,
"type": "column",
"value": "shipvia"
},
{
"id": 0,
"type": "table",
"value": "orders"
},
{
"id": 7,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6,
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O"
] |
9,440
|
behavior_monitoring
|
spider:train_spider.json:3105
|
Find the ids and first names of the 3 teachers that have the most number of assessment notes?
|
SELECT T1.teacher_id , T2.first_name FROM Assessment_Notes AS T1 JOIN Teachers AS T2 ON T1.teacher_id = T2.teacher_id GROUP BY T1.teacher_id ORDER BY count(*) DESC LIMIT 3
|
[
"Find",
"the",
"ids",
"and",
"first",
"names",
"of",
"the",
"3",
"teachers",
"that",
"have",
"the",
"most",
"number",
"of",
"assessment",
"notes",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "assessment_notes"
},
{
"id": 0,
"type": "column",
"value": "teacher_id"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "table",
"value": "teachers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
16,
17
]
},
{
"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",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
14,103
|
customers_and_addresses
|
spider:train_spider.json:6111
|
What is the payment method of the customer that has purchased the least quantity of items?
|
SELECT t1.payment_method FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id JOIN order_items AS t3 ON t2.order_id = t3.order_id GROUP BY t1.customer_name ORDER BY sum(t3.order_quantity) LIMIT 1
|
[
"What",
"is",
"the",
"payment",
"method",
"of",
"the",
"customer",
"that",
"has",
"purchased",
"the",
"least",
"quantity",
"of",
"items",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "payment_method"
},
{
"id": 6,
"type": "column",
"value": "order_quantity"
},
{
"id": 0,
"type": "column",
"value": "customer_name"
},
{
"id": 2,
"type": "table",
"value": "order_items"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "column",
"value": "order_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O"
] |
14,161
|
student_loan
|
bird:train.json:4406
|
What is the total number of students in the school?
|
SELECT COUNT(name) FROM person
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"students",
"in",
"the",
"school",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"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": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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"
] |
7,962
|
student_club
|
bird:dev.json:1466
|
Write the full name of the club member with the position of 'Secretary' and list which college the club member belongs to.
|
SELECT T1.first_name, T1.last_name, college FROM member AS T1 INNER JOIN major AS T2 ON T2.major_id = T1.link_to_major WHERE T1.position = 'Secretary'
|
[
"Write",
"the",
"full",
"name",
"of",
"the",
"club",
"member",
"with",
"the",
"position",
"of",
"'",
"Secretary",
"'",
"and",
"list",
"which",
"college",
"the",
"club",
"member",
"belongs",
"to",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "link_to_major"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 6,
"type": "value",
"value": "Secretary"
},
{
"id": 5,
"type": "column",
"value": "position"
},
{
"id": 7,
"type": "column",
"value": "major_id"
},
{
"id": 2,
"type": "column",
"value": "college"
},
{
"id": 3,
"type": "table",
"value": "member"
},
{
"id": 4,
"type": "table",
"value": "major"
}
] |
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[
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"O",
"O",
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"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
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"O",
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"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
3,269
|
chicago_crime
|
bird:train.json:8685
|
Give the case number and coordinates of the places where child abduction is reported.
|
SELECT T1.case_number, T1.latitude, T1.longitude FROM Crime AS T1 INNER JOIN IUCR AS T2 ON T2.iucr_no = T1.iucr_no WHERE T2.secondary_description = 'CHILD ABDUCTION'
|
[
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"case",
"number",
"and",
"coordinates",
"of",
"the",
"places",
"where",
"child",
"abduction",
"is",
"reported",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "secondary_description"
},
{
"id": 6,
"type": "value",
"value": "CHILD ABDUCTION"
},
{
"id": 0,
"type": "column",
"value": "case_number"
},
{
"id": 2,
"type": "column",
"value": "longitude"
},
{
"id": 1,
"type": "column",
"value": "latitude"
},
{
"id": 7,
"type": "column",
"value": "iucr_no"
},
{
"id": 3,
"type": "table",
"value": "crime"
},
{
"id": 4,
"type": "table",
"value": "iucr"
}
] |
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[
"O",
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"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
8,099
|
chicago_crime
|
bird:train.json:8733
|
What is the percentage of severe cases that are related to sexual assault?
|
SELECT CAST(SUM(CASE WHEN primary_description = 'CRIM SEXUAL ASSAULT' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM IUCR WHERE index_code = 'I'
|
[
"What",
"is",
"the",
"percentage",
"of",
"severe",
"cases",
"that",
"are",
"related",
"to",
"sexual",
"assault",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "primary_description"
},
{
"id": 7,
"type": "value",
"value": "CRIM SEXUAL ASSAULT"
},
{
"id": 1,
"type": "column",
"value": "index_code"
},
{
"id": 0,
"type": "table",
"value": "iucr"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 2,
"type": "value",
"value": "I"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
6,126
|
student_loan
|
bird:train.json:4515
|
What is the average absent month for a unemployed male students?
|
SELECT AVG(T2.month) AS avg FROM unemployed AS T1 INNER JOIN longest_absense_from_school AS T2 ON T2.name = T1.name INNER JOIN male AS T3 ON T3.name = T2.name
|
[
"What",
"is",
"the",
"average",
"absent",
"month",
"for",
"a",
"unemployed",
"male",
"students",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 2,
"type": "table",
"value": "unemployed"
},
{
"id": 1,
"type": "column",
"value": "month"
},
{
"id": 0,
"type": "table",
"value": "male"
},
{
"id": 4,
"type": "column",
"value": "name"
}
] |
[
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]
},
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]
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},
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O"
] |
4,011
|
shakespeare
|
bird:train.json:3008
|
In "A Lover's Complaint", what is the description of Act 1, Scene 1?
|
SELECT T2.Description FROM works AS T1 INNER JOIN chapters AS T2 ON T1.id = T2.work_id WHERE T2.Act = 1 AND T2.Scene = 1 AND T1.Title = 'A Lover''s Complaint'
|
[
"In",
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"A",
"Lover",
"'s",
"Complaint",
"\"",
",",
"what",
"is",
"the",
"description",
"of",
"Act",
"1",
",",
"Scene",
"1",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "A Lover's Complaint"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "chapters"
},
{
"id": 4,
"type": "column",
"value": "work_id"
},
{
"id": 1,
"type": "table",
"value": "works"
},
{
"id": 7,
"type": "column",
"value": "scene"
},
{
"id": 8,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "column",
"value": "act"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
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{
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},
{
"entity_id": 19,
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}
] |
[
"O",
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"B-VALUE",
"I-VALUE",
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"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,925
|
retail_world
|
bird:train.json:6443
|
Which region does Hoffman Estates belong to?
|
SELECT T2.RegionDescription FROM Territories AS T1 INNER JOIN Region AS T2 ON T1.RegionID = T2.RegionID WHERE T1.TerritoryDescription = 'Hoffman Estates'
|
[
"Which",
"region",
"does",
"Hoffman",
"Estates",
"belong",
"to",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "territorydescription"
},
{
"id": 0,
"type": "column",
"value": "regiondescription"
},
{
"id": 4,
"type": "value",
"value": "Hoffman Estates"
},
{
"id": 1,
"type": "table",
"value": "territories"
},
{
"id": 5,
"type": "column",
"value": "regionid"
},
{
"id": 2,
"type": "table",
"value": "region"
}
] |
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{
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},
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1
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"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
10,318
|
legislator
|
bird:train.json:4758
|
How many legislators have an Instagram account?
|
SELECT COUNT(*) FROM `social-media` WHERE instagram IS NOT NULL AND instagram <> ''
|
[
"How",
"many",
"legislators",
"have",
"an",
"Instagram",
"account",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "social-media"
},
{
"id": 1,
"type": "column",
"value": "instagram"
}
] |
[
{
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"entity_id": 1,
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{
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},
{
"entity_id": 14,
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{
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},
{
"entity_id": 16,
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
5,180
|
synthea
|
bird:train.json:1377
|
State the prevalence rate of condition no. 368581000119106.
|
SELECT DISTINCT T1."PREVALENCE RATE" FROM all_prevalences AS T1 INNER JOIN conditions AS T2 ON lower(T1.ITEM) = lower(T2.DESCRIPTION) WHERE T2.code = '368581000119106'
|
[
"State",
"the",
"prevalence",
"rate",
"of",
"condition",
"no",
".",
"368581000119106",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "PREVALENCE RATE"
},
{
"id": 1,
"type": "table",
"value": "all_prevalences"
},
{
"id": 4,
"type": "value",
"value": "368581000119106"
},
{
"id": 6,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "conditions"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 5,
"type": "column",
"value": "item"
}
] |
[
{
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},
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},
{
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5
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{
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{
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{
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},
{
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{
"entity_id": 16,
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O",
"O"
] |
13,116
|
apartment_rentals
|
spider:train_spider.json:1218
|
Return the date of birth for all the guests with gender code "Male".
|
SELECT date_of_birth FROM Guests WHERE gender_code = "Male"
|
[
"Return",
"the",
"date",
"of",
"birth",
"for",
"all",
"the",
"guests",
"with",
"gender",
"code",
"\"",
"Male",
"\"",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "date_of_birth"
},
{
"id": 2,
"type": "column",
"value": "gender_code"
},
{
"id": 0,
"type": "table",
"value": "guests"
},
{
"id": 3,
"type": "column",
"value": "Male"
}
] |
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{
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{
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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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
2,184
|
toxicology
|
bird:dev.json:196
|
In the non-carcinogenic molecules, how many contain chlorine atoms?
|
SELECT COUNT(DISTINCT T1.molecule_id) FROM molecule AS T1 INNER JOIN atom AS T2 ON T1.molecule_id = T2.molecule_id WHERE T2.element = 'cl' AND T1.label = '-'
|
[
"In",
"the",
"non",
"-",
"carcinogenic",
"molecules",
",",
"how",
"many",
"contain",
"chlorine",
"atoms",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "molecule_id"
},
{
"id": 0,
"type": "table",
"value": "molecule"
},
{
"id": 3,
"type": "column",
"value": "element"
},
{
"id": 5,
"type": "column",
"value": "label"
},
{
"id": 1,
"type": "table",
"value": "atom"
},
{
"id": 4,
"type": "value",
"value": "cl"
},
{
"id": 6,
"type": "value",
"value": "-"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"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",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
15,622
|
wine_1
|
spider:train_spider.json:6544
|
Give the names and scores of wines made from white grapes.
|
SELECT T2.Name , T2.Score FROM GRAPES AS T1 JOIN WINE AS T2 ON T1.Grape = T2.Grape WHERE T1.Color = "White"
|
[
"Give",
"the",
"names",
"and",
"scores",
"of",
"wines",
"made",
"from",
"white",
"grapes",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "grapes"
},
{
"id": 1,
"type": "column",
"value": "score"
},
{
"id": 4,
"type": "column",
"value": "color"
},
{
"id": 5,
"type": "column",
"value": "White"
},
{
"id": 6,
"type": "column",
"value": "grape"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "table",
"value": "wine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
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10
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
12,818
|
beer_factory
|
bird:train.json:5310
|
What brand of beer has been the worst rated most times?
|
SELECT T1.BrandName FROM rootbeerbrand AS T1 INNER JOIN rootbeerreview AS T2 ON T2.BrandID = T1.BrandID WHERE T2.StarRating = 1 GROUP BY T1.BrandName ORDER BY COUNT(T1.BrandName) DESC LIMIT 1
|
[
"What",
"brand",
"of",
"beer",
"has",
"been",
"the",
"worst",
"rated",
"most",
"times",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "rootbeerreview"
},
{
"id": 1,
"type": "table",
"value": "rootbeerbrand"
},
{
"id": 3,
"type": "column",
"value": "starrating"
},
{
"id": 0,
"type": "column",
"value": "brandname"
},
{
"id": 5,
"type": "column",
"value": "brandid"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
1
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
441
|
csu_1
|
spider:train_spider.json:2384
|
How many undergraduates are there in "San Jose State University" in year 2004?
|
SELECT sum(t1.undergraduate) FROM discipline_enrollments AS t1 JOIN campuses AS t2 ON t1.campus = t2.id WHERE t1.year = 2004 AND t2.campus = "San Jose State University"
|
[
"How",
"many",
"undergraduates",
"are",
"there",
"in",
"\"",
"San",
"Jose",
"State",
"University",
"\"",
"in",
"year",
"2004",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "San Jose State University"
},
{
"id": 0,
"type": "table",
"value": "discipline_enrollments"
},
{
"id": 2,
"type": "column",
"value": "undergraduate"
},
{
"id": 1,
"type": "table",
"value": "campuses"
},
{
"id": 3,
"type": "column",
"value": "campus"
},
{
"id": 5,
"type": "column",
"value": "year"
},
{
"id": 6,
"type": "value",
"value": "2004"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
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11
]
},
{
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"token_idxs": [
7,
8
]
},
{
"entity_id": 2,
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2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
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14
]
},
{
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9,
10
]
},
{
"entity_id": 8,
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},
{
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},
{
"entity_id": 10,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
6,049
|
chicago_crime
|
bird:train.json:8650
|
List down the neighborhood areas of Douglas.
|
SELECT T2.neighborhood_name FROM Community_Area AS T1 INNER JOIN Neighborhood AS T2 ON T2.community_area_no = T1.community_area_no WHERE T1.community_area_name = 'Douglas'
|
[
"List",
"down",
"the",
"neighborhood",
"areas",
"of",
"Douglas",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "community_area_name"
},
{
"id": 0,
"type": "column",
"value": "neighborhood_name"
},
{
"id": 5,
"type": "column",
"value": "community_area_no"
},
{
"id": 1,
"type": "table",
"value": "community_area"
},
{
"id": 2,
"type": "table",
"value": "neighborhood"
},
{
"id": 4,
"type": "value",
"value": "Douglas"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
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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-TABLE",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
15,513
|
works_cycles
|
bird:train.json:7114
|
Please list the top three employees with the most unused sick leave along with their position titles.
|
SELECT JobTitle FROM Employee ORDER BY SickLeaveHours DESC LIMIT 3
|
[
"Please",
"list",
"the",
"top",
"three",
"employees",
"with",
"the",
"most",
"unused",
"sick",
"leave",
"along",
"with",
"their",
"position",
"titles",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "sickleavehours"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "column",
"value": "jobtitle"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,302
|
movie_platform
|
bird:train.json:165
|
What is the name of the movie that was rated recently by user 57756708?
|
SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T1.user_id = 57756708 ORDER BY T1.rating_timestamp_utc DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"movie",
"that",
"was",
"rated",
"recently",
"by",
"user",
"57756708",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "rating_timestamp_utc"
},
{
"id": 0,
"type": "column",
"value": "movie_title"
},
{
"id": 4,
"type": "value",
"value": "57756708"
},
{
"id": 6,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "ratings"
},
{
"id": 3,
"type": "column",
"value": "user_id"
},
{
"id": 2,
"type": "table",
"value": "movies"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
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11,
12
]
},
{
"entity_id": 8,
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14
]
},
{
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},
{
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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",
"B-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
8,935
|
video_games
|
bird:train.json:3367
|
List the region name where games reached 300000 sales and above.
|
SELECT DISTINCT T1.region_name FROM region AS T1 INNER JOIN region_sales AS T2 ON T1.id = T2.region_id WHERE T2.num_sales * 100000 > 300000
|
[
"List",
"the",
"region",
"name",
"where",
"games",
"reached",
"300000",
"sales",
"and",
"above",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "region_sales"
},
{
"id": 0,
"type": "column",
"value": "region_name"
},
{
"id": 5,
"type": "column",
"value": "region_id"
},
{
"id": 6,
"type": "column",
"value": "num_sales"
},
{
"id": 1,
"type": "table",
"value": "region"
},
{
"id": 3,
"type": "value",
"value": "300000"
},
{
"id": 7,
"type": "value",
"value": "100000"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
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"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
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},
{
"entity_id": 3,
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7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
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},
{
"entity_id": 6,
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8
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},
{
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},
{
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},
{
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},
{
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},
{
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},
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},
{
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
8,883
|
beer_factory
|
bird:train.json:5303
|
What is the difference in the average number of sales per day of root beer brands that contain honey and that don’t contain honey.
|
SELECT (CAST(SUM(CASE WHEN T1.Honey = 'TRUE' THEN 1 ELSE 0 END) AS REAL) / COUNT(DISTINCT T3.TransactionDate)) - (CAST(SUM(CASE WHEN T1.Honey <> 'TRUE' THEN 1 ELSE 0 END) AS REAL) / COUNT(DISTINCT T3.TransactionDate)) FROM rootbeerbrand AS T1 INNER JOIN rootbeer AS T2 ON T1.BrandID = T2.BrandID INNER JOIN `transaction` AS T3 ON T2.RootBeerID = T3.RootBeerID
|
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"."
] |
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{
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{
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"type": "table",
"value": "rootbeerbrand"
},
{
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"type": "table",
"value": "transaction"
},
{
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"type": "column",
"value": "rootbeerid"
},
{
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"type": "table",
"value": "rootbeer"
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{
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"type": "column",
"value": "brandid"
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{
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{
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"type": "value",
"value": "TRUE"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
}
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"O",
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"O",
"O",
"O",
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"B-TABLE",
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"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
8,689
|
authors
|
bird:train.json:3587
|
Please list the names of the authors of the paper "Hypermethylation of the <I>TPEF/HPP1</I> Gene in Primary and Metastatic Colorectal Cancers".
|
SELECT T2.Name FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Title = 'Hypermethylation of the <I>TPEF/HPP1</I> Gene in Primary and Metastatic Colorectal Cancers'
|
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"\"",
"."
] |
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},
{
"id": 2,
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"value": "paperauthor"
},
{
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"type": "column",
"value": "paperid"
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{
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"value": "paper"
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{
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"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
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] |
[
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"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
3,733
|
csu_1
|
spider:train_spider.json:2383
|
How many faculty members are at the university that gave the least number of degrees in 2001?
|
SELECT T2.faculty FROM campuses AS T1 JOIN faculty AS T2 ON T1.id = t2.campus JOIN degrees AS T3 ON T1.id = t3.campus AND t2.year = t3.year WHERE t2.year = 2001 ORDER BY t3.degrees LIMIT 1
|
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"?"
] |
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"value": "campuses"
},
{
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"value": "faculty"
},
{
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"type": "table",
"value": "degrees"
},
{
"id": 4,
"type": "column",
"value": "degrees"
},
{
"id": 6,
"type": "table",
"value": "faculty"
},
{
"id": 8,
"type": "column",
"value": "campus"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2001"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
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},
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}
] |
[
"O",
"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,895
|
retail_world
|
bird:train.json:6546
|
Describe the supplier companies, cities and products which total production amount is more than 120.
|
SELECT T2.CompanyName, T2.City, T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.UnitsInStock + UnitsOnOrder > 120
|
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"120",
"."
] |
[
{
"id": 7,
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"value": "unitsinstock"
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{
"id": 8,
"type": "column",
"value": "unitsonorder"
},
{
"id": 0,
"type": "column",
"value": "companyname"
},
{
"id": 2,
"type": "column",
"value": "productname"
},
{
"id": 6,
"type": "column",
"value": "supplierid"
},
{
"id": 4,
"type": "table",
"value": "suppliers"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "120"
}
] |
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[
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"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,489
|
bike_share_1
|
bird:train.json:9056
|
What was the mean humidity of a trip with id 4275?
|
SELECT T2.mean_humidity FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T1.id = 4275
|
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"d",
"4275",
"?"
] |
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{
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{
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"value": "zip_code"
},
{
"id": 2,
"type": "table",
"value": "weather"
},
{
"id": 1,
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"value": "trip"
},
{
"id": 4,
"type": "value",
"value": "4275"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
5,107
|
activity_1
|
spider:train_spider.json:6748
|
How many male and female assistant professors do we have?
|
SELECT sex , count(*) FROM Faculty WHERE rank = "AsstProf" GROUP BY sex
|
[
"How",
"many",
"male",
"and",
"female",
"assistant",
"professors",
"do",
"we",
"have",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "AsstProf"
},
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 2,
"type": "column",
"value": "rank"
},
{
"id": 1,
"type": "column",
"value": "sex"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
15,331
|
sales_in_weather
|
bird:train.json:8152
|
How many more units of item no.16 were sold on the day with the highest max temperature in 2012 in store no.5 than in store no.10?
|
SELECT ( SELECT SUM(units) FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr INNER JOIN weather AS T3 ON T2.station_nbr = T3.station_nbr WHERE T1.item_nbr = 16 AND T1.`date` LIKE '%2012%' AND T1.store_nbr = 5 GROUP BY tmax ORDER BY T3.tmax DESC LIMIT 1 ) - ( SELECT SUM(units) FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr INNER JOIN weather AS T3 ON T2.station_nbr = T3.station_nbr WHERE T1.item_nbr = 16 AND T1.`date` LIKE '%2012%' AND T1.store_nbr = 6 GROUP BY tmax ORDER BY T3.tmax DESC LIMIT 1 )
|
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{
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{
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{
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},
{
"id": 11,
"type": "value",
"value": "5"
},
{
"id": 12,
"type": "value",
"value": "6"
}
] |
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
11,851
|
movie_3
|
bird:train.json:9104
|
How many films have a rental duration of over 6 days?
|
SELECT COUNT(film_id) FROM film WHERE rental_duration > 6
|
[
"How",
"many",
"films",
"have",
"a",
"rental",
"duration",
"of",
"over",
"6",
"days",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "rental_duration"
},
{
"id": 3,
"type": "column",
"value": "film_id"
},
{
"id": 0,
"type": "table",
"value": "film"
},
{
"id": 2,
"type": "value",
"value": "6"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
4,349
|
bike_1
|
spider:train_spider.json:173
|
What are the name, latitude, and city of the station with the lowest latitude?
|
SELECT name , lat , city FROM station ORDER BY lat LIMIT 1
|
[
"What",
"are",
"the",
"name",
",",
"latitude",
",",
"and",
"city",
"of",
"the",
"station",
"with",
"the",
"lowest",
"latitude",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "station"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 2,
"type": "column",
"value": "lat"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"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-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,084
|
student_loan
|
bird:train.json:4517
|
Calculate the average duration of absense of disabled male students.
|
SELECT AVG(T1.month) FROM longest_absense_from_school AS T1 INNER JOIN disabled AS T2 ON T2.name = T1.name INNER JOIN male AS T3 ON T3.name = T2.name
|
[
"Calculate",
"the",
"average",
"duration",
"of",
"absense",
"of",
"disabled",
"male",
"students",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 3,
"type": "table",
"value": "disabled"
},
{
"id": 1,
"type": "column",
"value": "month"
},
{
"id": 0,
"type": "table",
"value": "male"
},
{
"id": 4,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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-TABLE",
"B-TABLE",
"O",
"O"
] |
14,586
|
e_government
|
spider:train_spider.json:6339
|
Count the number of different payment method codes used by parties.
|
SELECT count(DISTINCT payment_method_code) FROM parties
|
[
"Count",
"the",
"number",
"of",
"different",
"payment",
"method",
"codes",
"used",
"by",
"parties",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "payment_method_code"
},
{
"id": 0,
"type": "table",
"value": "parties"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"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": [
6,
7,
8,
9
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,396
|
beer_factory
|
bird:train.json:5238
|
How many transactions had Frank-Paul Santangelo made in July, 2014?
|
SELECT COUNT(T1.CustomerID) FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.First = 'Frank-Paul' AND T1.Last = 'Santangelo' AND STRFTIME('%Y-%m', T2.TransactionDate) = '2014-07'
|
[
"How",
"many",
"transactions",
"had",
"Frank",
"-",
"Paul",
"Santangelo",
"made",
"in",
"July",
",",
"2014",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "transactiondate"
},
{
"id": 1,
"type": "table",
"value": "transaction"
},
{
"id": 2,
"type": "column",
"value": "customerid"
},
{
"id": 4,
"type": "value",
"value": "Frank-Paul"
},
{
"id": 6,
"type": "value",
"value": "Santangelo"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 7,
"type": "value",
"value": "2014-07"
},
{
"id": 3,
"type": "column",
"value": "first"
},
{
"id": 8,
"type": "value",
"value": "%Y-%m"
},
{
"id": 5,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
10,
11,
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",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-VALUE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
15,802
|
video_games
|
bird:train.json:3444
|
List by name all the games released in the year 2010.
|
SELECT T1.game_name FROM game AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.game_id INNER JOIN game_platform AS T3 ON T2.id = T3.game_publisher_id WHERE T3.release_year = '2010'
|
[
"List",
"by",
"name",
"all",
"the",
"games",
"released",
"in",
"the",
"year",
"2010",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "game_publisher_id"
},
{
"id": 5,
"type": "table",
"value": "game_publisher"
},
{
"id": 1,
"type": "table",
"value": "game_platform"
},
{
"id": 2,
"type": "column",
"value": "release_year"
},
{
"id": 0,
"type": "column",
"value": "game_name"
},
{
"id": 8,
"type": "column",
"value": "game_id"
},
{
"id": 3,
"type": "value",
"value": "2010"
},
{
"id": 4,
"type": "table",
"value": "game"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
6,932
|
advertising_agencies
|
bird:test.json:2069
|
Show agency ids and details with at least 2 clients.
|
SELECT T1.agency_id , T1.agency_details FROM Agencies AS T1 JOIN Clients AS T2 ON T1.agency_id = T2.agency_id GROUP BY T1.agency_id HAVING count(*) >= 2
|
[
"Show",
"agency",
"ids",
"and",
"details",
"with",
"at",
"least",
"2",
"clients",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "agency_details"
},
{
"id": 0,
"type": "column",
"value": "agency_id"
},
{
"id": 2,
"type": "table",
"value": "agencies"
},
{
"id": 3,
"type": "table",
"value": "clients"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
9,333
|
car_retails
|
bird:train.json:1545
|
Which different vendor has the most amount of orders? Calculate the total estimated earnings.
|
SELECT DISTINCT T1.productVendor, T1.MSRP - T1.buyPrice FROM products AS T1 INNER JOIN orderdetails AS T2 ON T1.productCode = T2.productCode GROUP BY T1.productVendor, T1.MSRP, T1.buyPrice ORDER BY COUNT(T2.quantityOrdered) DESC LIMIT 1
|
[
"Which",
"different",
"vendor",
"has",
"the",
"most",
"amount",
"of",
"orders",
"?",
"Calculate",
"the",
"total",
"estimated",
"earnings",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "quantityordered"
},
{
"id": 0,
"type": "column",
"value": "productvendor"
},
{
"id": 4,
"type": "table",
"value": "orderdetails"
},
{
"id": 5,
"type": "column",
"value": "productcode"
},
{
"id": 2,
"type": "column",
"value": "buyprice"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 1,
"type": "column",
"value": "msrp"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
7,
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
8,890
|
computer_student
|
bird:train.json:997
|
Please list the IDs of the professors that teaches more than 3 courses.
|
SELECT T1.p_id FROM taughtBy AS T1 INNER JOIN person AS T2 ON T1.p_id = T2.p_id WHERE T2.professor = 1 GROUP BY T1.p_id HAVING COUNT(DISTINCT T1.course_id) > 3
|
[
"Please",
"list",
"the",
"IDs",
"of",
"the",
"professors",
"that",
"teaches",
"more",
"than",
"3",
"courses",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "professor"
},
{
"id": 6,
"type": "column",
"value": "course_id"
},
{
"id": 1,
"type": "table",
"value": "taughtby"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 0,
"type": "column",
"value": "p_id"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 5,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
10,726
|
music_2
|
spider:train_spider.json:5202
|
What are all the instruments used?
|
SELECT DISTINCT instrument FROM Instruments
|
[
"What",
"are",
"all",
"the",
"instruments",
"used",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "instruments"
},
{
"id": 1,
"type": "column",
"value": "instrument"
}
] |
[
{
"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"
] |
4,114
|
retails
|
bird:train.json:6820
|
List all the dates of the urgent orders.
|
SELECT o_orderdate FROM orders WHERE o_orderpriority = '1-URGENT'
|
[
"List",
"all",
"the",
"dates",
"of",
"the",
"urgent",
"orders",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "o_orderpriority"
},
{
"id": 1,
"type": "column",
"value": "o_orderdate"
},
{
"id": 3,
"type": "value",
"value": "1-URGENT"
},
{
"id": 0,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
12,977
|
e_commerce
|
bird:test.json:75
|
What are the invoice statuses for all orderes that have not been shipped out yet?
|
SELECT invoice_status_code FROM Invoices WHERE invoice_number NOT IN ( SELECT invoice_number FROM Shipments )
|
[
"What",
"are",
"the",
"invoice",
"statuses",
"for",
"all",
"orderes",
"that",
"have",
"not",
"been",
"shipped",
"out",
"yet",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "invoice_status_code"
},
{
"id": 2,
"type": "column",
"value": "invoice_number"
},
{
"id": 3,
"type": "table",
"value": "shipments"
},
{
"id": 0,
"type": "table",
"value": "invoices"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
722
|
chicago_crime
|
bird:train.json:8654
|
Provide the occurrence date and location of the deceptive practice due to the unlawful use of recorded sound.
|
SELECT T2.date, T2.latitude, T2.longitude FROM IUCR AS T1 INNER JOIN Crime AS T2 ON T2.iucr_no = T1.iucr_no WHERE T1.primary_description = 'DECEPTIVE PRACTICE' AND T1.secondary_description = 'UNLAWFUL USE OF RECORDED SOUND'
|
[
"Provide",
"the",
"occurrence",
"date",
"and",
"location",
"of",
"the",
"deceptive",
"practice",
"due",
"to",
"the",
"unlawful",
"use",
"of",
"recorded",
"sound",
"."
] |
[
{
"id": 9,
"type": "value",
"value": "UNLAWFUL USE OF RECORDED SOUND"
},
{
"id": 8,
"type": "column",
"value": "secondary_description"
},
{
"id": 6,
"type": "column",
"value": "primary_description"
},
{
"id": 7,
"type": "value",
"value": "DECEPTIVE PRACTICE"
},
{
"id": 2,
"type": "column",
"value": "longitude"
},
{
"id": 1,
"type": "column",
"value": "latitude"
},
{
"id": 5,
"type": "column",
"value": "iucr_no"
},
{
"id": 4,
"type": "table",
"value": "crime"
},
{
"id": 0,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "table",
"value": "iucr"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
8,
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
13,
14,
15,
16,
17
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
15,250
|
baseball_1
|
spider:train_spider.json:3632
|
Compute the average salary of the players in the team called 'Boston Red Stockings'.
|
SELECT avg(T1.salary) FROM salary AS T1 JOIN team AS T2 ON T1.team_id = T2.team_id_br WHERE T2.name = 'Boston Red Stockings'
|
[
"Compute",
"the",
"average",
"salary",
"of",
"the",
"players",
"in",
"the",
"team",
"called",
"'",
"Boston",
"Red",
"Stockings",
"'",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Boston Red Stockings"
},
{
"id": 6,
"type": "column",
"value": "team_id_br"
},
{
"id": 5,
"type": "column",
"value": "team_id"
},
{
"id": 0,
"type": "table",
"value": "salary"
},
{
"id": 4,
"type": "column",
"value": "salary"
},
{
"id": 1,
"type": "table",
"value": "team"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
3,566
|
school_bus
|
spider:train_spider.json:6352
|
Show all different home cities.
|
SELECT DISTINCT home_city FROM driver
|
[
"Show",
"all",
"different",
"home",
"cities",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "home_city"
},
{
"id": 0,
"type": "table",
"value": "driver"
}
] |
[
{
"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": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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"
] |
9,157
|
california_schools
|
bird:dev.json:8
|
What is the number of SAT test takers of the schools with the highest FRPM count for K-12 students?
|
SELECT NumTstTakr FROM satscores WHERE cds = ( SELECT CDSCode FROM frpm ORDER BY `FRPM Count (K-12)` DESC LIMIT 1 )
|
[
"What",
"is",
"the",
"number",
"of",
"SAT",
"test",
"takers",
"of",
"the",
"schools",
"with",
"the",
"highest",
"FRPM",
"count",
"for",
"K-12",
"students",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "FRPM Count (K-12)"
},
{
"id": 1,
"type": "column",
"value": "numtsttakr"
},
{
"id": 0,
"type": "table",
"value": "satscores"
},
{
"id": 4,
"type": "column",
"value": "cdscode"
},
{
"id": 3,
"type": "table",
"value": "frpm"
},
{
"id": 2,
"type": "column",
"value": "cds"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14,
15,
16,
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
11,087
|
movie_platform
|
bird:train.json:143
|
Among the lists with at least one follower, how many were created by user who was subscriber when created the list?
|
SELECT COUNT(T1.list_id) FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_followers >= 1 AND T1.user_subscriber = 1
|
[
"Among",
"the",
"lists",
"with",
"at",
"least",
"one",
"follower",
",",
"how",
"many",
"were",
"created",
"by",
"user",
"who",
"was",
"subscriber",
"when",
"created",
"the",
"list",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "user_subscriber"
},
{
"id": 3,
"type": "column",
"value": "list_followers"
},
{
"id": 0,
"type": "table",
"value": "lists_users"
},
{
"id": 2,
"type": "column",
"value": "list_id"
},
{
"id": 1,
"type": "table",
"value": "lists"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
21
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
14,496
|
sakila_1
|
spider:train_spider.json:2948
|
Which film has the highest rental rate? And what is the rate?
|
SELECT title , rental_rate FROM film ORDER BY rental_rate DESC LIMIT 1
|
[
"Which",
"film",
"has",
"the",
"highest",
"rental",
"rate",
"?",
"And",
"what",
"is",
"the",
"rate",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "rental_rate"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
9,489
|
flight_1
|
spider:train_spider.json:372
|
What is the average and largest salary of all employees?
|
SELECT avg(salary) , max(salary) FROM Employee
|
[
"What",
"is",
"the",
"average",
"and",
"largest",
"salary",
"of",
"all",
"employees",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "column",
"value": "salary"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
4,462
|
public_review_platform
|
bird:train.json:3837
|
How long does business number 12 in Scottsdale stay open on day number 3?
|
SELECT T2.closing_time - T2.opening_time AS "hour" FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T1.business_id = 12 AND T1.city LIKE 'Scottsdale' AND T2.day_id = 3
|
[
"How",
"long",
"does",
"business",
"number",
"12",
"in",
"Scottsdale",
"stay",
"open",
"on",
"day",
"number",
"3",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "business_hours"
},
{
"id": 2,
"type": "column",
"value": "closing_time"
},
{
"id": 3,
"type": "column",
"value": "opening_time"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 7,
"type": "value",
"value": "Scottsdale"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 8,
"type": "column",
"value": "day_id"
},
{
"id": 6,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "12"
},
{
"id": 9,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": [
11
]
},
{
"entity_id": 9,
"token_idxs": [
13
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
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