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15,205
|
california_schools
|
bird:dev.json:82
|
What is the grade span offered in the school with the highest longitude?
|
SELECT GSoffered FROM schools ORDER BY ABS(longitude) DESC LIMIT 1
|
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"?"
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"B-COLUMN",
"O"
] |
15,206
|
european_football_2
|
bird:dev.json:1107
|
When was the first time did Kevin Constant have his highest crossing score? Give the date.
|
SELECT `date` FROM ( SELECT t2.crossing, t2.`date` FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_fifa_api_id = t2.player_fifa_api_id WHERE t1.player_name = 'Kevin Constant' ORDER BY t2.crossing DESC) ORDER BY date DESC LIMIT 1
|
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"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,207
|
book_1
|
bird:test.json:558
|
What are the names of clients who have never made an order?
|
SELECT name FROM Client EXCEPT SELECT T1.name FROM Client AS T1 JOIN Orders AS T2 ON T1.idClient = T2.idClient
|
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"value": "name"
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"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,208
|
scientist_1
|
spider:train_spider.json:6487
|
Find the total hours of the projects that scientists named Michael Rogers or Carol Smith are assigned to.
|
SELECT sum(T2.hours) FROM assignedto AS T1 JOIN projects AS T2 ON T1.project = T2.code JOIN scientists AS T3 ON T1.scientist = T3.SSN WHERE T3.name = 'Michael Rogers' OR T3.name = 'Carol Smith'
|
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"."
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"type": "column",
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"value": "ssn"
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"O",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
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15,209
|
behavior_monitoring
|
spider:train_spider.json:3098
|
Find the maximum and minimum monthly rental for all student addresses.
|
SELECT max(monthly_rental) , min(monthly_rental) FROM Student_Addresses
|
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"."
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{
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"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
15,210
|
game_1
|
spider:train_spider.json:6022
|
What are the ids of all students who don't play sports?
|
SELECT StuID FROM Student EXCEPT SELECT StuID FROM Sportsinfo
|
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"?"
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{
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"type": "table",
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{
"id": 2,
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"value": "stuid"
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"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,211
|
image_and_language
|
bird:train.json:7577
|
Based on image 5, what is the percentage of images that belong windows object class?
|
SELECT CAST(COUNT(T1.OBJ_SAMPLE_ID) AS REAL) * 100 / COUNT(CASE WHEN T1.IMG_ID = 5 THEN 1 ELSE 0 END) FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T2.OBJ_CLASS = 'windows'
|
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"O",
"O",
"B-VALUE",
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"I-COLUMN",
"O"
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15,212
|
movie_platform
|
bird:train.json:77
|
Among the users who are trailists when rating the movie "When Will I Be Loved", how many of them have rated "1" on the movie?
|
SELECT COUNT(T1.user_id) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_title = 'When Will I Be Loved' AND T1.rating_score = 1 AND T1.user_trialist = 1
|
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{
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{
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"type": "table",
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{
"id": 7,
"type": "value",
"value": "1"
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"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,213
|
company_office
|
spider:train_spider.json:4562
|
For each company, return the company name and the name of the building its office is located in.
|
SELECT T3.name , T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id
|
[
"For",
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"company",
",",
"return",
"the",
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"name",
"and",
"the",
"name",
"of",
"the",
"building",
"its",
"office",
"is",
"located",
"in",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "office_locations"
},
{
"id": 6,
"type": "column",
"value": "building_id"
},
{
"id": 4,
"type": "column",
"value": "company_id"
},
{
"id": 1,
"type": "table",
"value": "companies"
},
{
"id": 3,
"type": "table",
"value": "buildings"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
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7
]
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6
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15,
16,
17,
18
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"entity_id": 3,
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13
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2
]
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{
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{
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{
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"token_idxs": []
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"token_idxs": []
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"entity_id": 13,
"token_idxs": []
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"entity_id": 14,
"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"O"
] |
15,214
|
bike_share_1
|
bird:train.json:9064
|
Please list the starting stations of the bike trips made on a day with a max humidity over 80 in 2013 in the area where the zip code is 94107.
|
SELECT DISTINCT T1.start_station_name FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE SUBSTR(CAST(T2.date AS TEXT), -4) = '2013' AND T2.zip_code = 94107 AND T2.max_temperature_f > 80
|
[
"Please",
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"bike",
"trips",
"made",
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"80",
"in",
"2013",
"in",
"the",
"area",
"where",
"the",
"zip",
"code",
"is",
"94107",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "start_station_name"
},
{
"id": 6,
"type": "column",
"value": "max_temperature_f"
},
{
"id": 3,
"type": "column",
"value": "zip_code"
},
{
"id": 2,
"type": "table",
"value": "weather"
},
{
"id": 5,
"type": "value",
"value": "94107"
},
{
"id": 1,
"type": "table",
"value": "trip"
},
{
"id": 4,
"type": "value",
"value": "2013"
},
{
"id": 9,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "value",
"value": "80"
},
{
"id": 8,
"type": "value",
"value": "-4"
}
] |
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{
"entity_id": 0,
"token_idxs": [
3,
4
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},
{
"entity_id": 1,
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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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"entity_id": 8,
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"token_idxs": []
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"token_idxs": []
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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",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,215
|
university
|
bird:train.json:8007
|
What is the university ID of the university with the largest student staff ratio?
|
SELECT university_id FROM university_year ORDER BY student_staff_ratio DESC LIMIT 1
|
[
"What",
"is",
"the",
"university",
"ID",
"of",
"the",
"university",
"with",
"the",
"largest",
"student",
"staff",
"ratio",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "student_staff_ratio"
},
{
"id": 0,
"type": "table",
"value": "university_year"
},
{
"id": 1,
"type": "column",
"value": "university_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
11,
12,
13
]
},
{
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"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
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},
{
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
15,216
|
books
|
bird:train.json:5951
|
How many orders were delivered in 2021?
|
SELECT COUNT(*) FROM order_status AS T1 INNER JOIN order_history AS T2 ON T1.status_id = T2.status_id WHERE T1.status_value = 'Delivered' AND STRFTIME('%Y', T2.status_date) = '2021'
|
[
"How",
"many",
"orders",
"were",
"delivered",
"in",
"2021",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "order_history"
},
{
"id": 0,
"type": "table",
"value": "order_status"
},
{
"id": 3,
"type": "column",
"value": "status_value"
},
{
"id": 7,
"type": "column",
"value": "status_date"
},
{
"id": 2,
"type": "column",
"value": "status_id"
},
{
"id": 4,
"type": "value",
"value": "Delivered"
},
{
"id": 5,
"type": "value",
"value": "2021"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
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6
]
},
{
"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,
"token_idxs": []
},
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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",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
15,217
|
bike_1
|
spider:train_spider.json:195
|
Find all the zip codes in which the max dew point have never reached 70.
|
SELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70
|
[
"Find",
"all",
"the",
"zip",
"codes",
"in",
"which",
"the",
"max",
"dew",
"point",
"have",
"never",
"reached",
"70",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "max_dew_point_f"
},
{
"id": 1,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 3,
"type": "value",
"value": "70"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,218
|
video_games
|
bird:train.json:3391
|
Mention the genre of the 2Xtreme.
|
SELECT T2.id FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T1.game_name = '2Xtreme'
|
[
"Mention",
"the",
"genre",
"of",
"the",
"2Xtreme",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "game_name"
},
{
"id": 5,
"type": "column",
"value": "genre_id"
},
{
"id": 4,
"type": "value",
"value": "2Xtreme"
},
{
"id": 2,
"type": "table",
"value": "genre"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
15,220
|
aan_1
|
bird:test.json:982
|
What are the titles and paper ids for papers which were affiliated with both Stanford and Columbia University?
|
SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T3.name LIKE "Stanford University" INTERSECT SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T3.name LIKE "Columbia University"
|
[
"What",
"are",
"the",
"titles",
"and",
"paper",
"ids",
"for",
"papers",
"which",
"were",
"affiliated",
"with",
"both",
"Stanford",
"and",
"Columbia",
"University",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "Stanford University"
},
{
"id": 5,
"type": "column",
"value": "Columbia University"
},
{
"id": 8,
"type": "column",
"value": "affiliation_id"
},
{
"id": 2,
"type": "table",
"value": "affiliation"
},
{
"id": 7,
"type": "table",
"value": "author_list"
},
{
"id": 1,
"type": "column",
"value": "paper_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
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11
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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14,
15
]
},
{
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"token_idxs": [
16,
17
]
},
{
"entity_id": 6,
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5
]
},
{
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"token_idxs": []
},
{
"entity_id": 8,
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},
{
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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",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,223
|
beer_factory
|
bird:train.json:5256
|
Which city does the customer who finished transaction no.103545 live in?
|
SELECT T1.City FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.TransactionID = 103545
|
[
"Which",
"city",
"does",
"the",
"customer",
"who",
"finished",
"transaction",
"no.103545",
"live",
"in",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "transactionid"
},
{
"id": 2,
"type": "table",
"value": "transaction"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "value",
"value": "103545"
},
{
"id": 0,
"type": "column",
"value": "city"
}
] |
[
{
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"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
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"token_idxs": [
7
]
},
{
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},
{
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8
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},
{
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},
{
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},
{
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},
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O",
"O",
"O"
] |
15,224
|
authors
|
bird:train.json:3530
|
In year 1999, list the titles and conference's short name of paper authored by someone named "Philip".
|
SELECT T1.Title, T3.ShortName FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId INNER JOIN Conference AS T3 ON T1.ConferenceId = T3.Id WHERE T1.Year = 1999 AND T2.Name LIKE 'Philip%'
|
[
"In",
"year",
"1999",
",",
"list",
"the",
"titles",
"and",
"conference",
"'s",
"short",
"name",
"of",
"paper",
"authored",
"by",
"someone",
"named",
"\"",
"Philip",
"\"",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "conferenceid"
},
{
"id": 4,
"type": "table",
"value": "paperauthor"
},
{
"id": 2,
"type": "table",
"value": "conference"
},
{
"id": 1,
"type": "column",
"value": "shortname"
},
{
"id": 10,
"type": "value",
"value": "Philip%"
},
{
"id": 11,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "paper"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "1999"
},
{
"id": 9,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
1
]
},
{
"entity_id": 8,
"token_idxs": [
2
]
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": [
19
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,225
|
software_company
|
bird:train.json:8567
|
List the level of education and income of customers ages from 30 to 55 with a true response.
|
SELECT T1.EDUCATIONNUM, T3.INCOME_K 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 T1.age >= 30 AND T1.age <= 55 AND T2.RESPONSE = 'true'
|
[
"List",
"the",
"level",
"of",
"education",
"and",
"income",
"of",
"customers",
"ages",
"from",
"30",
"to",
"55",
"with",
"a",
"true",
"response",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "educationnum"
},
{
"id": 4,
"type": "table",
"value": "mailings1_2"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "income_k"
},
{
"id": 9,
"type": "column",
"value": "response"
},
{
"id": 2,
"type": "table",
"value": "demog"
},
{
"id": 5,
"type": "column",
"value": "geoid"
},
{
"id": 12,
"type": "column",
"value": "refid"
},
{
"id": 10,
"type": "value",
"value": "true"
},
{
"id": 6,
"type": "column",
"value": "age"
},
{
"id": 7,
"type": "value",
"value": "30"
},
{
"id": 8,
"type": "value",
"value": "55"
},
{
"id": 11,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": [
17
]
},
{
"entity_id": 10,
"token_idxs": [
16
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,227
|
real_estate_rentals
|
bird:test.json:1442
|
List the first name, middle name and last name, and log in name of all the seller users, whose seller value is 1.
|
SELECT first_name , middle_name , last_name , login_name FROM Users WHERE is_seller = 1;
|
[
"List",
"the",
"first",
"name",
",",
"middle",
"name",
"and",
"last",
"name",
",",
"and",
"log",
"in",
"name",
"of",
"all",
"the",
"seller",
"users",
",",
"whose",
"seller",
"value",
"is",
"1",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "middle_name"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "login_name"
},
{
"id": 3,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "is_seller"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": [
25
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,228
|
book_publishing_company
|
bird:train.json:235
|
Find the difference between the average royalty of titles published by US and non US publishers?
|
SELECT (CAST(SUM(CASE WHEN T2.country = 'USA' THEN T1.royalty ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.country = 'USA' THEN 1 ELSE 0 END)) - (CAST(SUM(CASE WHEN T2.country != 'USA' THEN T1.royalty ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.country != 'USA' THEN 1 ELSE 0 END)) FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN roysched AS T3 ON T1.title_id = T3.title_id
|
[
"Find",
"the",
"difference",
"between",
"the",
"average",
"royalty",
"of",
"titles",
"published",
"by",
"US",
"and",
"non",
"US",
"publishers",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "publishers"
},
{
"id": 0,
"type": "table",
"value": "roysched"
},
{
"id": 3,
"type": "column",
"value": "title_id"
},
{
"id": 7,
"type": "column",
"value": "royalty"
},
{
"id": 8,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "titles"
},
{
"id": 4,
"type": "column",
"value": "pub_id"
},
{
"id": 9,
"type": "value",
"value": "USA"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,229
|
apartment_rentals
|
spider:train_spider.json:1257
|
What are the top three apartment types in terms of the average room count? Give me the
|
SELECT apt_type_code FROM Apartments GROUP BY apt_type_code ORDER BY avg(room_count) DESC LIMIT 3
|
[
"What",
"are",
"the",
"top",
"three",
"apartment",
"types",
"in",
"terms",
"of",
"the",
"average",
"room",
"count",
"?",
"Give",
"me",
"the"
] |
[
{
"id": 1,
"type": "column",
"value": "apt_type_code"
},
{
"id": 0,
"type": "table",
"value": "apartments"
},
{
"id": 2,
"type": "column",
"value": "room_count"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12,
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
15,230
|
soccer_3
|
bird:test.json:26
|
Please show the most common manufacturer of clubs.
|
SELECT Manufacturer FROM club GROUP BY Manufacturer ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Please",
"show",
"the",
"most",
"common",
"manufacturer",
"of",
"clubs",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "manufacturer"
},
{
"id": 0,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
15,231
|
music_platform_2
|
bird:train.json:7984
|
Please list the titles of the podcasts for which the author whose ID is F7E5A318989779D has written a review.
|
SELECT T2.title FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T2.author_id = 'F7E5A318989779D'
|
[
"Please",
"list",
"the",
"titles",
"of",
"the",
"podcasts",
"for",
"which",
"the",
"author",
"whose",
"ID",
"is",
"F7E5A318989779D",
"has",
"written",
"a",
"review",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "F7E5A318989779D"
},
{
"id": 5,
"type": "column",
"value": "podcast_id"
},
{
"id": 3,
"type": "column",
"value": "author_id"
},
{
"id": 1,
"type": "table",
"value": "podcasts"
},
{
"id": 2,
"type": "table",
"value": "reviews"
},
{
"id": 0,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,232
|
movie_3
|
bird:train.json:9310
|
Who is the manager of the store with the largest collection of films?
|
SELECT T.first_name, T.last_name FROM ( SELECT T3.first_name, T3.last_name, COUNT(T1.film_id) AS num FROM inventory AS T1 INNER JOIN store AS T2 ON T1.store_id = T2.store_id INNER JOIN staff AS T3 ON T2.manager_staff_id = T3.staff_id GROUP BY T3.first_name, T3.last_name ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"Who",
"is",
"the",
"manager",
"of",
"the",
"store",
"with",
"the",
"largest",
"collection",
"of",
"films",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "manager_staff_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "table",
"value": "inventory"
},
{
"id": 8,
"type": "column",
"value": "staff_id"
},
{
"id": 9,
"type": "column",
"value": "store_id"
},
{
"id": 4,
"type": "column",
"value": "film_id"
},
{
"id": 3,
"type": "table",
"value": "staff"
},
{
"id": 6,
"type": "table",
"value": "store"
},
{
"id": 2,
"type": "column",
"value": "num"
}
] |
[
{
"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": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": [
3,
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,233
|
video_games
|
bird:train.json:3490
|
What is the name of the company that produced the game titled Adventure Time: Explore the Dungeon Because I Don't Know!?
|
SELECT T3.publisher_name FROM game AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.game_id INNER JOIN publisher AS T3 ON T2.publisher_id = T3.id WHERE T1.game_name = 'Adventure Time: Explore the Dungeon Because I Don''t Know!'
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"company",
"that",
"produced",
"the",
"game",
"titled",
"Adventure",
"Time",
":",
"Explore",
"the",
"Dungeon",
"Because",
"I",
"Do",
"n't",
"Know",
"!",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Adventure Time: Explore the Dungeon Because I Don't Know!"
},
{
"id": 0,
"type": "column",
"value": "publisher_name"
},
{
"id": 5,
"type": "table",
"value": "game_publisher"
},
{
"id": 6,
"type": "column",
"value": "publisher_id"
},
{
"id": 1,
"type": "table",
"value": "publisher"
},
{
"id": 2,
"type": "column",
"value": "game_name"
},
{
"id": 8,
"type": "column",
"value": "game_id"
},
{
"id": 4,
"type": "table",
"value": "game"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13,
14,
15,
16,
17,
18,
20,
21,
22,
23
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
19
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
15,234
|
college_1
|
spider:train_spider.json:3269
|
What is the name of department where has the smallest number of professors?
|
SELECT T2.dept_name FROM professor AS T1 JOIN department AS T2 ON T1.dept_code = T2.dept_code GROUP BY T1.dept_code ORDER BY count(*) LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"department",
"where",
"has",
"the",
"smallest",
"number",
"of",
"professors",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "dept_code"
},
{
"id": 1,
"type": "column",
"value": "dept_name"
},
{
"id": 2,
"type": "table",
"value": "professor"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,236
|
art_1
|
bird:test.json:1246
|
What are the average height of paintings for different medium types?
|
SELECT avg(height_mm) , medium FROM paintings GROUP BY medium
|
[
"What",
"are",
"the",
"average",
"height",
"of",
"paintings",
"for",
"different",
"medium",
"types",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 2,
"type": "column",
"value": "height_mm"
},
{
"id": 1,
"type": "column",
"value": "medium"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,237
|
real_estate_rentals
|
bird:test.json:1468
|
List the last names and ids of users who have at least 2 properties and searched at most twice.
|
SELECT T1.last_name , T1.user_id FROM Users AS T1 JOIN User_Searches AS T2 ON T1.user_id = T2.user_id GROUP BY T1.user_id HAVING count(*) <= 2 INTERSECT SELECT T3.last_name , T3.user_id FROM Users AS T3 JOIN Properties AS T4 ON T3.user_id = T4.owner_user_id GROUP BY T3.user_id HAVING count(*) >= 2;
|
[
"List",
"the",
"last",
"names",
"and",
"ids",
"of",
"users",
"who",
"have",
"at",
"least",
"2",
"properties",
"and",
"searched",
"at",
"most",
"twice",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "user_searches"
},
{
"id": 6,
"type": "column",
"value": "owner_user_id"
},
{
"id": 5,
"type": "table",
"value": "properties"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 2,
"type": "table",
"value": "users"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
15,238
|
european_football_2
|
bird:dev.json:1140
|
What are Alexis Blin's sprint speed, agility, and acceleration scores?
|
SELECT sprint_speed, agility, acceleration FROM Player_Attributes WHERE player_api_id IN ( SELECT player_api_id FROM Player WHERE player_name = 'Alexis Blin' )
|
[
"What",
"are",
"Alexis",
"Blin",
"'s",
"sprint",
"speed",
",",
"agility",
",",
"and",
"acceleration",
"scores",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "player_attributes"
},
{
"id": 4,
"type": "column",
"value": "player_api_id"
},
{
"id": 1,
"type": "column",
"value": "sprint_speed"
},
{
"id": 3,
"type": "column",
"value": "acceleration"
},
{
"id": 6,
"type": "column",
"value": "player_name"
},
{
"id": 7,
"type": "value",
"value": "Alexis Blin"
},
{
"id": 2,
"type": "column",
"value": "agility"
},
{
"id": 5,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
2,
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,239
|
law_episode
|
bird:train.json:1342
|
What is the episode that has mafia keyword?
|
SELECT T1.episode FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T2.Keyword = 'mafia'
|
[
"What",
"is",
"the",
"episode",
"that",
"has",
"mafia",
"keyword",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "episode_id"
},
{
"id": 0,
"type": "column",
"value": "episode"
},
{
"id": 1,
"type": "table",
"value": "episode"
},
{
"id": 2,
"type": "table",
"value": "keyword"
},
{
"id": 3,
"type": "column",
"value": "keyword"
},
{
"id": 4,
"type": "value",
"value": "mafia"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"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-VALUE",
"B-COLUMN",
"O"
] |
15,240
|
software_company
|
bird:train.json:8512
|
Please list the occupations of the customers with an education level of 11.
|
SELECT DISTINCT OCCUPATION FROM Customers WHERE EDUCATIONNUM = 11
|
[
"Please",
"list",
"the",
"occupations",
"of",
"the",
"customers",
"with",
"an",
"education",
"level",
"of",
"11",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "educationnum"
},
{
"id": 1,
"type": "column",
"value": "occupation"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "value",
"value": "11"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"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-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
15,241
|
car_retails
|
bird:train.json:1619
|
If Dragon Souveniers, Ltd. aren't satisfied with their order and want to send a complain e-mail, which e-mail address should they send to?
|
SELECT t2.email FROM customers AS t1 INNER JOIN employees AS t2 ON t1.salesRepEmployeeNumber = t2.employeeNumber WHERE t1.customerName = 'Dragon Souveniers, Ltd.'
|
[
"If",
"Dragon",
"Souveniers",
",",
"Ltd.",
"are",
"n't",
"satisfied",
"with",
"their",
"order",
"and",
"want",
"to",
"send",
"a",
"complain",
"e",
"-",
"mail",
",",
"which",
"e",
"-",
"mail",
"address",
"should",
"they",
"send",
"to",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Dragon Souveniers, Ltd."
},
{
"id": 5,
"type": "column",
"value": "salesrepemployeenumber"
},
{
"id": 6,
"type": "column",
"value": "employeenumber"
},
{
"id": 3,
"type": "column",
"value": "customername"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "employees"
},
{
"id": 0,
"type": "column",
"value": "email"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17,
18,
19
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
1,
2,
3,
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,242
|
beer_factory
|
bird:train.json:5287
|
Among the root beer purchased in 2014, what percentage were sold in cans?
|
SELECT CAST(COUNT(CASE WHEN ContainerType = 'Can' THEN RootBeerID ELSE NULL END) AS REAL) * 100 / COUNT(RootBeerID) FROM rootbeer WHERE PurchaseDate LIKE '2014%'
|
[
"Among",
"the",
"root",
"beer",
"purchased",
"in",
"2014",
",",
"what",
"percentage",
"were",
"sold",
"in",
"cans",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "containertype"
},
{
"id": 1,
"type": "column",
"value": "purchasedate"
},
{
"id": 4,
"type": "column",
"value": "rootbeerid"
},
{
"id": 0,
"type": "table",
"value": "rootbeer"
},
{
"id": 2,
"type": "value",
"value": "2014%"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "Can"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,243
|
cre_Students_Information_Systems
|
bird:test.json:482
|
What are the pairs of teachers and students who are in the same class? Give me the pairs of their details.
|
SELECT T1.teacher_details , T3.student_details FROM Teachers AS T1 JOIN Classes AS T2 ON T1.teacher_id = T2.teacher_id JOIN Students AS T3 ON T2.student_id = T3.student_id
|
[
"What",
"are",
"the",
"pairs",
"of",
"teachers",
"and",
"students",
"who",
"are",
"in",
"the",
"same",
"class",
"?",
"Give",
"me",
"the",
"pairs",
"of",
"their",
"details",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "teacher_details"
},
{
"id": 1,
"type": "column",
"value": "student_details"
},
{
"id": 5,
"type": "column",
"value": "student_id"
},
{
"id": 6,
"type": "column",
"value": "teacher_id"
},
{
"id": 2,
"type": "table",
"value": "students"
},
{
"id": 3,
"type": "table",
"value": "teachers"
},
{
"id": 4,
"type": "table",
"value": "classes"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20,
21
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,244
|
works_cycles
|
bird:train.json:7041
|
Which job title has the lowest pay?
|
SELECT T1.JobTitle FROM Employee AS T1 INNER JOIN EmployeePayHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID ORDER BY T2.Rate ASC LIMIT 1
|
[
"Which",
"job",
"title",
"has",
"the",
"lowest",
"pay",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "employeepayhistory"
},
{
"id": 4,
"type": "column",
"value": "businessentityid"
},
{
"id": 0,
"type": "column",
"value": "jobtitle"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 3,
"type": "column",
"value": "rate"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
15,245
|
world_development_indicators
|
bird:train.json:2219
|
What is the name of the country with the highest percentage of rural population in the overall total population? Indicate the rural population percentage of total population.
|
SELECT countryname, MAX(value) FROM indicators WHERE indicatorname = 'Rural population (% of total population)'
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"country",
"with",
"the",
"highest",
"percentage",
"of",
"rural",
"population",
"in",
"the",
"overall",
"total",
"population",
"?",
"Indicate",
"the",
"rural",
"population",
"percentage",
"of",
"total",
"population",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Rural population (% of total population)"
},
{
"id": 2,
"type": "column",
"value": "indicatorname"
},
{
"id": 1,
"type": "column",
"value": "countryname"
},
{
"id": 0,
"type": "table",
"value": "indicators"
},
{
"id": 4,
"type": "column",
"value": "value"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
22,
23,
24,
25,
26,
27
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
15,246
|
card_games
|
bird:dev.json:437
|
Among black card borders, which card has full artwork?
|
SELECT id FROM cards WHERE borderColor = 'black' AND isFullArt = 1
|
[
"Among",
"black",
"card",
"borders",
",",
"which",
"card",
"has",
"full",
"artwork",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "bordercolor"
},
{
"id": 4,
"type": "column",
"value": "isfullart"
},
{
"id": 0,
"type": "table",
"value": "cards"
},
{
"id": 3,
"type": "value",
"value": "black"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": [
8,
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,247
|
dorm_1
|
spider:train_spider.json:5682
|
Find the total capacity of all dorms.
|
SELECT sum(student_capacity) FROM dorm
|
[
"Find",
"the",
"total",
"capacity",
"of",
"all",
"dorms",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "student_capacity"
},
{
"id": 0,
"type": "table",
"value": "dorm"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
15,248
|
bakery_1
|
bird:test.json:1545
|
Find all receipts which has the latest date. Also tell me that date.
|
SELECT ReceiptNumber , date FROM receipts WHERE date = (SELECT date FROM receipts ORDER BY date DESC LIMIT 1)
|
[
"Find",
"all",
"receipts",
"which",
"has",
"the",
"latest",
"date",
".",
"Also",
"tell",
"me",
"that",
"date",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "receiptnumber"
},
{
"id": 0,
"type": "table",
"value": "receipts"
},
{
"id": 2,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,249
|
gas_company
|
spider:train_spider.json:2015
|
How many gas station are opened between 2000 and 2005?
|
SELECT count(*) FROM gas_station WHERE open_year BETWEEN 2000 AND 2005
|
[
"How",
"many",
"gas",
"station",
"are",
"opened",
"between",
"2000",
"and",
"2005",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "gas_station"
},
{
"id": 1,
"type": "column",
"value": "open_year"
},
{
"id": 2,
"type": "value",
"value": "2000"
},
{
"id": 3,
"type": "value",
"value": "2005"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"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-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
15,251
|
cre_Students_Information_Systems
|
bird:test.json:448
|
List the amount and date of loan for the students who have two or more achievements.
|
SELECT amount_of_loan , date_of_loan FROM Student_Loans WHERE student_id IN ( SELECT student_id FROM Achievements GROUP BY student_id HAVING count(*) >= 2 )
|
[
"List",
"the",
"amount",
"and",
"date",
"of",
"loan",
"for",
"the",
"students",
"who",
"have",
"two",
"or",
"more",
"achievements",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "amount_of_loan"
},
{
"id": 0,
"type": "table",
"value": "student_loans"
},
{
"id": 2,
"type": "column",
"value": "date_of_loan"
},
{
"id": 4,
"type": "table",
"value": "achievements"
},
{
"id": 3,
"type": "column",
"value": "student_id"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,252
|
ice_hockey_draft
|
bird:train.json:6988
|
What team did Niklas Eckerblom play in the 1997-1998 season?
|
SELECT T2.TEAM FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T2.SEASON = '1997-1998' AND T1.PlayerName = 'Niko Kapanen'
|
[
"What",
"team",
"did",
"Niklas",
"Eckerblom",
"play",
"in",
"the",
"1997",
"-",
"1998",
"season",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "seasonstatus"
},
{
"id": 7,
"type": "value",
"value": "Niko Kapanen"
},
{
"id": 1,
"type": "table",
"value": "playerinfo"
},
{
"id": 6,
"type": "column",
"value": "playername"
},
{
"id": 5,
"type": "value",
"value": "1997-1998"
},
{
"id": 3,
"type": "column",
"value": "eliteid"
},
{
"id": 4,
"type": "column",
"value": "season"
},
{
"id": 0,
"type": "column",
"value": "team"
}
] |
[
{
"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": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 6,
"token_idxs": [
5,
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
15,253
|
soccer_2016
|
bird:train.json:1917
|
In what year did SP Narine win the Orange Cap?
|
SELECT T4.Season_Year, T4.Orange_Cap FROM Player AS T1 INNER JOIN Player_Match AS T2 ON T1.Player_Id = T2.Player_Id INNER JOIN Match AS T3 ON T2.Match_Id = T3.Match_Id INNER JOIN Season AS T4 ON T3.Season_Id = T4.Season_Id WHERE T1.Player_Name = 'SP Narine' GROUP BY T4.Season_Year, T4.Orange_Cap
|
[
"In",
"what",
"year",
"did",
"SP",
"Narine",
"win",
"the",
"Orange",
"Cap",
"?"
] |
[
{
"id": 8,
"type": "table",
"value": "player_match"
},
{
"id": 0,
"type": "column",
"value": "season_year"
},
{
"id": 3,
"type": "column",
"value": "player_name"
},
{
"id": 1,
"type": "column",
"value": "orange_cap"
},
{
"id": 4,
"type": "value",
"value": "SP Narine"
},
{
"id": 6,
"type": "column",
"value": "season_id"
},
{
"id": 10,
"type": "column",
"value": "player_id"
},
{
"id": 9,
"type": "column",
"value": "match_id"
},
{
"id": 2,
"type": "table",
"value": "season"
},
{
"id": 7,
"type": "table",
"value": "player"
},
{
"id": 5,
"type": "table",
"value": "match"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4,
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
2
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
3
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,254
|
soccer_2016
|
bird:train.json:1828
|
In which country do the majority of the players are from?
|
SELECT T1.Country_Name FROM Country AS T1 INNER JOIN Player AS T2 ON T1.Country_Id = T2.Country_Name GROUP BY T2.Country_Name ORDER BY COUNT(T2.Country_Name) DESC LIMIT 1
|
[
"In",
"which",
"country",
"do",
"the",
"majority",
"of",
"the",
"players",
"are",
"from",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "country_name"
},
{
"id": 3,
"type": "column",
"value": "country_id"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
15,255
|
toxicology
|
bird:dev.json:337
|
List the element and bond type included in the molecule with molecule ID of TR002.
|
SELECT DISTINCT T1.element, T2.bond_type FROM atom AS T1 INNER JOIN bond AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.molecule_id = 'TR002'
|
[
"List",
"the",
"element",
"and",
"bond",
"type",
"included",
"in",
"the",
"molecule",
"with",
"molecule",
"ID",
"of",
"TR002",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "molecule_id"
},
{
"id": 1,
"type": "column",
"value": "bond_type"
},
{
"id": 0,
"type": "column",
"value": "element"
},
{
"id": 5,
"type": "value",
"value": "TR002"
},
{
"id": 2,
"type": "table",
"value": "atom"
},
{
"id": 3,
"type": "table",
"value": "bond"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,256
|
wedding
|
spider:train_spider.json:1645
|
How many weddings are there in year 2016?
|
SELECT count(*) FROM wedding WHERE YEAR = 2016
|
[
"How",
"many",
"weddings",
"are",
"there",
"in",
"year",
"2016",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "wedding"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "2016"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
15,257
|
phone_market
|
spider:train_spider.json:1979
|
List the names of phones in ascending order of price.
|
SELECT Name FROM phone ORDER BY Price ASC
|
[
"List",
"the",
"names",
"of",
"phones",
"in",
"ascending",
"order",
"of",
"price",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "phone"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"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-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,258
|
food_inspection_2
|
bird:train.json:6233
|
How many restaurants failed the inspection in April 2010?
|
SELECT COUNT(DISTINCT T1.license_no) FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no WHERE strftime('%Y-%m', T2.inspection_date) = '2010-04' AND T1.facility_type = 'Restaurant' AND T2.results = 'Fail'
|
[
"How",
"many",
"restaurants",
"failed",
"the",
"inspection",
"in",
"April",
"2010",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "inspection_date"
},
{
"id": 0,
"type": "table",
"value": "establishment"
},
{
"id": 4,
"type": "column",
"value": "facility_type"
},
{
"id": 1,
"type": "table",
"value": "inspection"
},
{
"id": 2,
"type": "column",
"value": "license_no"
},
{
"id": 5,
"type": "value",
"value": "Restaurant"
},
{
"id": 3,
"type": "value",
"value": "2010-04"
},
{
"id": 6,
"type": "column",
"value": "results"
},
{
"id": 8,
"type": "value",
"value": "%Y-%m"
},
{
"id": 7,
"type": "value",
"value": "Fail"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
15,259
|
bakery_1
|
bird:test.json:1513
|
Find all the receipt numbers in which customer with last name LOGAN purchased Croissant.
|
SELECT T1.ReceiptNumber FROM receipts AS T1 JOIN items AS T2 ON T1.ReceiptNumber = T2.receipt JOIN goods AS T3 ON T2.item = T3.id JOIN customers AS T4 ON T4.Id = T1.CustomerId WHERE T3.food = "Croissant" AND T4.LastName = 'LOGAN'
|
[
"Find",
"all",
"the",
"receipt",
"numbers",
"in",
"which",
"customer",
"with",
"last",
"name",
"LOGAN",
"purchased",
"Croissant",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "receiptnumber"
},
{
"id": 4,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "Croissant"
},
{
"id": 7,
"type": "column",
"value": "lastname"
},
{
"id": 9,
"type": "table",
"value": "receipts"
},
{
"id": 12,
"type": "column",
"value": "receipt"
},
{
"id": 2,
"type": "table",
"value": "goods"
},
{
"id": 8,
"type": "value",
"value": "LOGAN"
},
{
"id": 10,
"type": "table",
"value": "items"
},
{
"id": 5,
"type": "column",
"value": "food"
},
{
"id": 11,
"type": "column",
"value": "item"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
0
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": [
9,
10
]
},
{
"entity_id": 8,
"token_idxs": [
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
3
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"O"
] |
15,260
|
coinmarketcap
|
bird:train.json:6283
|
What is the name of the coin with the highest price?
|
SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.price = ( SELECT MAX(price) FROM historical )
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"coin",
"with",
"the",
"highest",
"price",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 5,
"type": "column",
"value": "coin_id"
},
{
"id": 1,
"type": "table",
"value": "coins"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,261
|
simpson_episodes
|
bird:train.json:4208
|
What is the birth place of the cast or crew member who won the Best Voice-Over Performance in Online Film & Television Association in 2009?
|
SELECT T1.birth_place FROM Person AS T1 INNER JOIN Award AS T2 ON T1.name = T2.person WHERE T2.award = 'Best Voice-Over Performance' AND T2.organization = 'Online Film & Television Association' AND T2.year = 2009;
|
[
"What",
"is",
"the",
"birth",
"place",
"of",
"the",
"cast",
"or",
"crew",
"member",
"who",
"won",
"the",
"Best",
"Voice",
"-",
"Over",
"Performance",
"in",
"Online",
"Film",
"&",
"Television",
"Association",
"in",
"2009",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Online Film & Television Association"
},
{
"id": 6,
"type": "value",
"value": "Best Voice-Over Performance"
},
{
"id": 7,
"type": "column",
"value": "organization"
},
{
"id": 0,
"type": "column",
"value": "birth_place"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 4,
"type": "column",
"value": "person"
},
{
"id": 2,
"type": "table",
"value": "award"
},
{
"id": 5,
"type": "column",
"value": "award"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 9,
"type": "column",
"value": "year"
},
{
"id": 10,
"type": "value",
"value": "2009"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
14,
15,
16,
17
]
},
{
"entity_id": 7,
"token_idxs": [
24
]
},
{
"entity_id": 8,
"token_idxs": [
20,
21,
22,
23
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
26
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,262
|
wrestler
|
spider:train_spider.json:1857
|
Give the names of wrestlers and their elimination moves.
|
SELECT T2.Name , T1.Elimination_Move FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID
|
[
"Give",
"the",
"names",
"of",
"wrestlers",
"and",
"their",
"elimination",
"moves",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "elimination_move"
},
{
"id": 2,
"type": "table",
"value": "elimination"
},
{
"id": 4,
"type": "column",
"value": "wrestler_id"
},
{
"id": 3,
"type": "table",
"value": "wrestler"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,263
|
railway
|
spider:train_spider.json:5646
|
Show different locations of railways along with the corresponding number of railways at each location.
|
SELECT LOCATION , COUNT(*) FROM railway GROUP BY LOCATION
|
[
"Show",
"different",
"locations",
"of",
"railways",
"along",
"with",
"the",
"corresponding",
"number",
"of",
"railways",
"at",
"each",
"location",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "railway"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,264
|
movie_3
|
bird:train.json:9333
|
Which movie title has the lowest movie rental in the horror category?
|
SELECT T1.title FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T2.category_id = T3.category_id WHERE T3.`name` = 'Horror' ORDER BY T1.rental_rate LIMIT 1
|
[
"Which",
"movie",
"title",
"has",
"the",
"lowest",
"movie",
"rental",
"in",
"the",
"horror",
"category",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "film_category"
},
{
"id": 4,
"type": "column",
"value": "rental_rate"
},
{
"id": 7,
"type": "column",
"value": "category_id"
},
{
"id": 1,
"type": "table",
"value": "category"
},
{
"id": 8,
"type": "column",
"value": "film_id"
},
{
"id": 3,
"type": "value",
"value": "Horror"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
15,266
|
election
|
spider:train_spider.json:2784
|
Show the 3 counties with the smallest population.
|
SELECT County_name FROM county ORDER BY Population ASC LIMIT 3
|
[
"Show",
"the",
"3",
"counties",
"with",
"the",
"smallest",
"population",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "county_name"
},
{
"id": 2,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "county"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,267
|
network_2
|
spider:train_spider.json:4423
|
How old is the average person for each job?
|
SELECT avg(age) , job FROM Person GROUP BY job
|
[
"How",
"old",
"is",
"the",
"average",
"person",
"for",
"each",
"job",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "job"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
15,268
|
election
|
spider:train_spider.json:2741
|
What are the maximum and minimum population of the counties?
|
SELECT max(Population) , min(Population) FROM county
|
[
"What",
"are",
"the",
"maximum",
"and",
"minimum",
"population",
"of",
"the",
"counties",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "county"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
15,269
|
debit_card_specializing
|
bird:dev.json:1526
|
For the customer who paid 634.8 in 2012/8/25, what was the consumption decrease rate from Year 2012 to 2013?
|
SELECT CAST(SUM(IIF(SUBSTR(Date, 1, 4) = '2012', Consumption, 0)) - SUM(IIF(SUBSTR(Date, 1, 4) = '2013', Consumption, 0)) AS FLOAT) / SUM(IIF(SUBSTR(Date, 1, 4) = '2012', Consumption, 0)) FROM yearmonth WHERE CustomerID = ( SELECT T1.CustomerID FROM transactions_1k AS T1 INNER JOIN gasstations AS T2 ON T1.GasStationID = T2.GasStationID WHERE T1.Date = '2012-08-25' AND T1.Price = 634.8 )
|
[
"For",
"the",
"customer",
"who",
"paid",
"634.8",
"in",
"2012/8/25",
",",
"what",
"was",
"the",
"consumption",
"decrease",
"rate",
"from",
"Year",
"2012",
"to",
"2013",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "transactions_1k"
},
{
"id": 7,
"type": "column",
"value": "gasstationid"
},
{
"id": 2,
"type": "column",
"value": "consumption"
},
{
"id": 5,
"type": "table",
"value": "gasstations"
},
{
"id": 1,
"type": "column",
"value": "customerid"
},
{
"id": 9,
"type": "value",
"value": "2012-08-25"
},
{
"id": 0,
"type": "table",
"value": "yearmonth"
},
{
"id": 10,
"type": "column",
"value": "price"
},
{
"id": 11,
"type": "value",
"value": "634.8"
},
{
"id": 6,
"type": "value",
"value": "2012"
},
{
"id": 8,
"type": "column",
"value": "date"
},
{
"id": 14,
"type": "value",
"value": "2013"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 12,
"type": "value",
"value": "1"
},
{
"id": 13,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
14
]
},
{
"entity_id": 9,
"token_idxs": [
7
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
5
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": [
19
]
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
15,270
|
social_media
|
bird:train.json:846
|
From which city was the tweet with the most number of retweets posted?
|
SELECT T2.City FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID ORDER BY T1.RetweetCount DESC LIMIT 1
|
[
"From",
"which",
"city",
"was",
"the",
"tweet",
"with",
"the",
"most",
"number",
"of",
"retweets",
"posted",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "retweetcount"
},
{
"id": 4,
"type": "column",
"value": "locationid"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 1,
"type": "table",
"value": "twitter"
},
{
"id": 0,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6,
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,271
|
menu
|
bird:train.json:5560
|
Among the menus with over 10 pages, how many of them have over 20 dishes?
|
SELECT COUNT(*) FROM Menu WHERE page_count > 10 AND dish_count > 20
|
[
"Among",
"the",
"menus",
"with",
"over",
"10",
"pages",
",",
"how",
"many",
"of",
"them",
"have",
"over",
"20",
"dishes",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "page_count"
},
{
"id": 3,
"type": "column",
"value": "dish_count"
},
{
"id": 0,
"type": "table",
"value": "menu"
},
{
"id": 2,
"type": "value",
"value": "10"
},
{
"id": 4,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,272
|
entrepreneur
|
spider:train_spider.json:2272
|
Return the names of people, ordered by weight ascending.
|
SELECT Name FROM People ORDER BY Weight ASC
|
[
"Return",
"the",
"names",
"of",
"people",
",",
"ordered",
"by",
"weight",
"ascending",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "people"
},
{
"id": 2,
"type": "column",
"value": "weight"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,273
|
sports_competition
|
spider:train_spider.json:3347
|
What are the maximum and minimum number of silver medals for clubs.
|
SELECT max(Silver) , min(Silver) FROM club_rank
|
[
"What",
"are",
"the",
"maximum",
"and",
"minimum",
"number",
"of",
"silver",
"medals",
"for",
"clubs",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "club_rank"
},
{
"id": 1,
"type": "column",
"value": "silver"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,274
|
aan_1
|
bird:test.json:973
|
List names and addresses for all affiliations.
|
SELECT DISTINCT name , address FROM Affiliation
|
[
"List",
"names",
"and",
"addresses",
"for",
"all",
"affiliations",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "affiliation"
},
{
"id": 2,
"type": "column",
"value": "address"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
15,275
|
sakila_1
|
spider:train_spider.json:2955
|
What are the full names of actors who had roles in more than 30 films?
|
SELECT T2.first_name , T2.last_name FROM film_actor AS T1 JOIN actor AS T2 ON T1.actor_id = T2.actor_id GROUP BY T2.actor_id HAVING count(*) > 30
|
[
"What",
"are",
"the",
"full",
"names",
"of",
"actors",
"who",
"had",
"roles",
"in",
"more",
"than",
"30",
"films",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "table",
"value": "film_actor"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "column",
"value": "actor_id"
},
{
"id": 4,
"type": "table",
"value": "actor"
},
{
"id": 5,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,276
|
movie_platform
|
bird:train.json:117
|
Give the number of followers for the user who posted the most lists.
|
SELECT SUM(T1.list_followers) FROM lists AS T1 INNER JOIN lists_users AS T2 ON T1.list_id = T2.list_id GROUP BY T1.user_id ORDER BY COUNT(T1.list_id) DESC LIMIT 1
|
[
"Give",
"the",
"number",
"of",
"followers",
"for",
"the",
"user",
"who",
"posted",
"the",
"most",
"lists",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "list_followers"
},
{
"id": 2,
"type": "table",
"value": "lists_users"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 4,
"type": "column",
"value": "list_id"
},
{
"id": 1,
"type": "table",
"value": "lists"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,277
|
food_inspection
|
bird:train.json:8837
|
List the names and business certificates of the eateries which got inspection score under 50.
|
SELECT T2.name, T2.business_id FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.score < 50
|
[
"List",
"the",
"names",
"and",
"business",
"certificates",
"of",
"the",
"eateries",
"which",
"got",
"inspection",
"score",
"under",
"50",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 2,
"type": "table",
"value": "inspections"
},
{
"id": 3,
"type": "table",
"value": "businesses"
},
{
"id": 4,
"type": "column",
"value": "score"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "value",
"value": "50"
}
] |
[
{
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2
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]
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,278
|
loan_1
|
spider:train_spider.json:3081
|
What is the total amount of money loaned by banks in New York state?
|
SELECT sum(T2.amount) FROM bank AS T1 JOIN loan AS T2 ON T1.branch_id = T2.branch_id WHERE T1.state = 'New York'
|
[
"What",
"is",
"the",
"total",
"amount",
"of",
"money",
"loaned",
"by",
"banks",
"in",
"New",
"York",
"state",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "branch_id"
},
{
"id": 3,
"type": "value",
"value": "New York"
},
{
"id": 4,
"type": "column",
"value": "amount"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "table",
"value": "bank"
},
{
"id": 1,
"type": "table",
"value": "loan"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
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7
]
},
{
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13
]
},
{
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11,
12
]
},
{
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4
]
},
{
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},
{
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},
{
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},
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},
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},
{
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
15,279
|
chicago_crime
|
bird:train.json:8659
|
How many crimes are commited on January 1, 2018?
|
SELECT COUNT(*) FROM Crime WHERE date LIKE '1/1/2018%'
|
[
"How",
"many",
"crimes",
"are",
"commited",
"on",
"January",
"1",
",",
"2018",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "1/1/2018%"
},
{
"id": 0,
"type": "table",
"value": "crime"
},
{
"id": 1,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
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"token_idxs": [
7,
8,
9
]
},
{
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},
{
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{
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},
{
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},
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},
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"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
15,280
|
shop_membership
|
spider:train_spider.json:5427
|
What are the names and cities of the branches that do not have any registered members?
|
SELECT name , city FROM branch WHERE branch_id NOT IN (SELECT branch_id FROM membership_register_branch)
|
[
"What",
"are",
"the",
"names",
"and",
"cities",
"of",
"the",
"branches",
"that",
"do",
"not",
"have",
"any",
"registered",
"members",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "membership_register_branch"
},
{
"id": 3,
"type": "column",
"value": "branch_id"
},
{
"id": 0,
"type": "table",
"value": "branch"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
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3
]
},
{
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5
]
},
{
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},
{
"entity_id": 4,
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},
{
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},
{
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},
{
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},
{
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},
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},
{
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},
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,281
|
beer_factory
|
bird:train.json:5342
|
What is the amount difference between the bottles of root beer sold from Louisiana and Missouri?
|
SELECT ( SELECT COUNT(T1.BrandID) FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID WHERE T2.State = 'LA' AND T1.ContainerType = 'Bottle' ) - ( SELECT COUNT(T3.BrandID) FROM rootbeer AS T3 INNER JOIN rootbeerbrand AS T4 ON T3.BrandID = T4.BrandID WHERE T4.State = 'MO' AND T3.ContainerType = 'Bottle' ) AS DIFFERENCE
|
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"is",
"the",
"amount",
"difference",
"between",
"the",
"bottles",
"of",
"root",
"beer",
"sold",
"from",
"Louisiana",
"and",
"Missouri",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "rootbeerbrand"
},
{
"id": 5,
"type": "column",
"value": "containertype"
},
{
"id": 0,
"type": "table",
"value": "rootbeer"
},
{
"id": 2,
"type": "column",
"value": "brandid"
},
{
"id": 6,
"type": "value",
"value": "Bottle"
},
{
"id": 3,
"type": "column",
"value": "state"
},
{
"id": 4,
"type": "value",
"value": "LA"
},
{
"id": 7,
"type": "value",
"value": "MO"
}
] |
[
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"entity_id": 0,
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9,
10
]
},
{
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{
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},
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
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},
{
"entity_id": 16,
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,282
|
movie_3
|
bird:train.json:9111
|
What is the email address of the staff Jon Stephens?
|
SELECT email FROM staff WHERE first_name = 'Jon' AND last_name = 'Stephens'
|
[
"What",
"is",
"the",
"email",
"address",
"of",
"the",
"staff",
"Jon",
"Stephens",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "value",
"value": "Stephens"
},
{
"id": 0,
"type": "table",
"value": "staff"
},
{
"id": 1,
"type": "column",
"value": "email"
},
{
"id": 3,
"type": "value",
"value": "Jon"
}
] |
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"entity_id": 0,
"token_idxs": [
7
]
},
{
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3
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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8
]
},
{
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},
{
"entity_id": 5,
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9
]
},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
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},
{
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},
{
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"B-VALUE",
"O"
] |
15,283
|
student_club
|
bird:dev.json:1359
|
How many times was the budget in Advertisement for "Yearly Kickoff" meeting more than "October Meeting"?
|
SELECT CAST(SUM(CASE WHEN T2.event_name = 'Yearly Kickoff' THEN T1.amount ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.event_name = 'October Meeting' THEN T1.amount ELSE 0 END) FROM budget AS T1 INNER JOIN event AS T2 ON T1.link_to_event = T2.event_id WHERE T1.category = 'Advertisement' AND T2.type = 'Meeting'
|
[
"How",
"many",
"times",
"was",
"the",
"budget",
"in",
"Advertisement",
"for",
"\"",
"Yearly",
"Kickoff",
"\"",
"meeting",
"more",
"than",
"\"",
"October",
"Meeting",
"\"",
"?"
] |
[
{
"id": 11,
"type": "value",
"value": "October Meeting"
},
{
"id": 12,
"type": "value",
"value": "Yearly Kickoff"
},
{
"id": 2,
"type": "column",
"value": "link_to_event"
},
{
"id": 5,
"type": "value",
"value": "Advertisement"
},
{
"id": 10,
"type": "column",
"value": "event_name"
},
{
"id": 3,
"type": "column",
"value": "event_id"
},
{
"id": 4,
"type": "column",
"value": "category"
},
{
"id": 7,
"type": "value",
"value": "Meeting"
},
{
"id": 0,
"type": "table",
"value": "budget"
},
{
"id": 9,
"type": "column",
"value": "amount"
},
{
"id": 1,
"type": "table",
"value": "event"
},
{
"id": 6,
"type": "column",
"value": "type"
},
{
"id": 8,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
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{
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},
{
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},
{
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{
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10,
11
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
15,284
|
simpson_episodes
|
bird:train.json:4324
|
Write down all the keywords for winner of "WGA Award (TV)" award.
|
SELECT T2.keyword FROM Award AS T1 INNER JOIN Keyword AS T2 ON T2.episode_id = T1.episode_id WHERE T1.award_category = 'WGA Award (TV)';
|
[
"Write",
"down",
"all",
"the",
"keywords",
"for",
"winner",
"of",
"\"",
"WGA",
"Award",
"(",
"TV",
")",
"\"",
"award",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "award_category"
},
{
"id": 4,
"type": "value",
"value": "WGA Award (TV)"
},
{
"id": 5,
"type": "column",
"value": "episode_id"
},
{
"id": 0,
"type": "column",
"value": "keyword"
},
{
"id": 2,
"type": "table",
"value": "keyword"
},
{
"id": 1,
"type": "table",
"value": "award"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
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15
]
},
{
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4
]
},
{
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},
{
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9,
10,
11,
12,
13
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},
{
"entity_id": 5,
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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
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"token_idxs": []
},
{
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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",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
15,285
|
scientist_1
|
spider:train_spider.json:6485
|
Find the name of the project for which a scientist whose name contains ‘Smith’ is assigned to.
|
SELECT T2.name FROM assignedto AS T1 JOIN projects AS T2 ON T1.project = T2.code JOIN scientists AS T3 ON T1.scientist = T3.SSN WHERE T3.name LIKE '%Smith%'
|
[
"Find",
"the",
"name",
"of",
"the",
"project",
"for",
"which",
"a",
"scientist",
"whose",
"name",
"contains",
"‘",
"Smith",
"’",
"is",
"assigned",
"to",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "scientists"
},
{
"id": 3,
"type": "table",
"value": "assignedto"
},
{
"id": 5,
"type": "column",
"value": "scientist"
},
{
"id": 4,
"type": "table",
"value": "projects"
},
{
"id": 2,
"type": "value",
"value": "%Smith%"
},
{
"id": 7,
"type": "column",
"value": "project"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "column",
"value": "ssn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
17,
18
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
15,286
|
regional_sales
|
bird:train.json:2590
|
List down the customer IDs and names that start with alphabet "W".
|
SELECT DISTINCT CustomerID, `Customer Names` FROM Customers WHERE `Customer Names` LIKE 'W%' ORDER BY `Customer Names` DESC
|
[
"List",
"down",
"the",
"customer",
"IDs",
"and",
"names",
"that",
"start",
"with",
"alphabet",
"\"",
"W",
"\"",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "Customer Names"
},
{
"id": 1,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "value",
"value": "W%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,288
|
sakila_1
|
spider:train_spider.json:2956
|
Which store owns most items?
|
SELECT store_id FROM inventory GROUP BY store_id ORDER BY count(*) DESC LIMIT 1
|
[
"Which",
"store",
"owns",
"most",
"items",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "inventory"
},
{
"id": 1,
"type": "column",
"value": "store_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,289
|
thrombosis_prediction
|
bird:dev.json:1161
|
For in-patient age 50 and above, what is their average anti-cardiolipin antibody (IgG) concentration?
|
SELECT AVG(T2.`aCL IgG`) FROM Patient AS T1 INNER JOIN Examination AS T2 ON T1.ID = T2.ID WHERE STRFTIME('%Y', CURRENT_TIMESTAMP) - STRFTIME('%Y', T1.Birthday) >= 50 AND T1.Admission = '+'
|
[
"For",
"in",
"-",
"patient",
"age",
"50",
"and",
"above",
",",
"what",
"is",
"their",
"average",
"anti",
"-",
"cardiolipin",
"antibody",
"(",
"IgG",
")",
"concentration",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "examination"
},
{
"id": 5,
"type": "column",
"value": "admission"
},
{
"id": 8,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 2,
"type": "column",
"value": "aCL IgG"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "50"
},
{
"id": 7,
"type": "value",
"value": "%Y"
},
{
"id": 6,
"type": "value",
"value": "+"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
15,291
|
retails
|
bird:train.json:6767
|
How many customers who are not in debt ordered an urgent order?
|
SELECT COUNT(T2.c_custkey) FROM orders AS T1 INNER JOIN customer AS T2 ON T1.o_custkey = T2.c_custkey WHERE T2.c_acctbal > 0 AND T1.o_orderpriority = '1-URGENT'
|
[
"How",
"many",
"customers",
"who",
"are",
"not",
"in",
"debt",
"ordered",
"an",
"urgent",
"order",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "o_orderpriority"
},
{
"id": 2,
"type": "column",
"value": "c_custkey"
},
{
"id": 3,
"type": "column",
"value": "o_custkey"
},
{
"id": 4,
"type": "column",
"value": "c_acctbal"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 7,
"type": "value",
"value": "1-URGENT"
},
{
"id": 0,
"type": "table",
"value": "orders"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
15,292
|
shipping
|
bird:train.json:5622
|
Where was shipment no. 1002 headed?
|
SELECT T2.city_name FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T1.ship_id = '1002'
|
[
"Where",
"was",
"shipment",
"no",
".",
"1002",
"headed",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "city_name"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "column",
"value": "ship_id"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "1002"
}
] |
[
{
"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": [
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-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,293
|
car_retails
|
bird:train.json:1605
|
What is the full address of the office where 4 people work and one of them is Sales Representation?
|
SELECT T1.addressLine1, T1.addressLine2 FROM customers AS T1 INNER JOIN employees AS T2 ON T1.salesRepEmployeeNumber = T2.employeeNumber WHERE T2.jobTitle = 'Sales Rep'
|
[
"What",
"is",
"the",
"full",
"address",
"of",
"the",
"office",
"where",
"4",
"people",
"work",
"and",
"one",
"of",
"them",
"is",
"Sales",
"Representation",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "salesrepemployeenumber"
},
{
"id": 7,
"type": "column",
"value": "employeenumber"
},
{
"id": 0,
"type": "column",
"value": "addressline1"
},
{
"id": 1,
"type": "column",
"value": "addressline2"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "table",
"value": "employees"
},
{
"id": 5,
"type": "value",
"value": "Sales Rep"
},
{
"id": 4,
"type": "column",
"value": "jobtitle"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,294
|
vehicle_driver
|
bird:test.json:155
|
How many vehicles has a driver driven at most, and what is the driver id of the driver who has driven this many vehicles?
|
SELECT count(*) , driver_id FROM vehicle_driver GROUP BY driver_id ORDER BY count(*) DESC LIMIT 1
|
[
"How",
"many",
"vehicles",
"has",
"a",
"driver",
"driven",
"at",
"most",
",",
"and",
"what",
"is",
"the",
"driver",
"i",
"d",
"of",
"the",
"driver",
"who",
"has",
"driven",
"this",
"many",
"vehicles",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "vehicle_driver"
},
{
"id": 1,
"type": "column",
"value": "driver_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
14,
15,
16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,295
|
bakery_1
|
bird:test.json:1520
|
Count the number of goods for each food type.
|
SELECT count(*) , food FROM goods GROUP BY food
|
[
"Count",
"the",
"number",
"of",
"goods",
"for",
"each",
"food",
"type",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 1,
"type": "column",
"value": "food"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,296
|
public_review_platform
|
bird:train.json:3812
|
How many active businesses are there in Phoenix?
|
SELECT COUNT(business_id) FROM Business WHERE city LIKE 'Phoenix' AND active LIKE 'TRUE'
|
[
"How",
"many",
"active",
"businesses",
"are",
"there",
"in",
"Phoenix",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 3,
"type": "value",
"value": "Phoenix"
},
{
"id": 4,
"type": "column",
"value": "active"
},
{
"id": 2,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "TRUE"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
15,297
|
college_1
|
spider:train_spider.json:3315
|
Find the first names and offices of all instructors who have taught some course and the course description and the department name.
|
SELECT T2.emp_fname , T4.prof_office , T3.crs_description , T5.dept_name FROM CLASS AS T1 JOIN employee AS T2 ON T1.prof_num = T2.emp_num JOIN course AS T3 ON T1.crs_code = T3.crs_code JOIN professor AS T4 ON T2.emp_num = T4.emp_num JOIN department AS T5 ON T4.dept_code = T5.dept_code
|
[
"Find",
"the",
"first",
"names",
"and",
"offices",
"of",
"all",
"instructors",
"who",
"have",
"taught",
"some",
"course",
"and",
"the",
"course",
"description",
"and",
"the",
"department",
"name",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "crs_description"
},
{
"id": 1,
"type": "column",
"value": "prof_office"
},
{
"id": 4,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "emp_fname"
},
{
"id": 3,
"type": "column",
"value": "dept_name"
},
{
"id": 5,
"type": "table",
"value": "professor"
},
{
"id": 6,
"type": "column",
"value": "dept_code"
},
{
"id": 10,
"type": "table",
"value": "employee"
},
{
"id": 11,
"type": "column",
"value": "crs_code"
},
{
"id": 12,
"type": "column",
"value": "prof_num"
},
{
"id": 8,
"type": "column",
"value": "emp_num"
},
{
"id": 7,
"type": "table",
"value": "course"
},
{
"id": 9,
"type": "table",
"value": "class"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
16,
17
]
},
{
"entity_id": 3,
"token_idxs": [
20,
21
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,298
|
city_record
|
spider:train_spider.json:6298
|
Please give me a list of cities whose regional population is over 8000000 or under 5000000.
|
SELECT city FROM city WHERE regional_population > 10000000 UNION SELECT city FROM city WHERE regional_population < 5000000
|
[
"Please",
"give",
"me",
"a",
"list",
"of",
"cities",
"whose",
"regional",
"population",
"is",
"over",
"8000000",
"or",
"under",
"5000000",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "regional_population"
},
{
"id": 3,
"type": "value",
"value": "10000000"
},
{
"id": 4,
"type": "value",
"value": "5000000"
},
{
"id": 0,
"type": "table",
"value": "city"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,299
|
european_football_2
|
bird:dev.json:1126
|
State the name of players who came from Belgium.
|
SELECT t3.player_name FROM Country AS t1 INNER JOIN Match AS t2 ON t1.id = t2.country_id INNER JOIN Player AS t3 ON t2.home_player_1 = t3.player_api_id WHERE t1.name = 'Belgium'
|
[
"State",
"the",
"name",
"of",
"players",
"who",
"came",
"from",
"Belgium",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "home_player_1"
},
{
"id": 7,
"type": "column",
"value": "player_api_id"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 9,
"type": "column",
"value": "country_id"
},
{
"id": 3,
"type": "value",
"value": "Belgium"
},
{
"id": 4,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "player"
},
{
"id": 5,
"type": "table",
"value": "match"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,300
|
superhero
|
bird:dev.json:739
|
What are the names of the superheroes with the power of death touch?
|
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN hero_power AS T2 ON T1.id = T2.hero_id INNER JOIN superpower AS T3 ON T2.power_id = T3.id WHERE T3.power_name = 'Death Touch'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"superheroes",
"with",
"the",
"power",
"of",
"death",
"touch",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "superhero_name"
},
{
"id": 3,
"type": "value",
"value": "Death Touch"
},
{
"id": 1,
"type": "table",
"value": "superpower"
},
{
"id": 2,
"type": "column",
"value": "power_name"
},
{
"id": 5,
"type": "table",
"value": "hero_power"
},
{
"id": 4,
"type": "table",
"value": "superhero"
},
{
"id": 6,
"type": "column",
"value": "power_id"
},
{
"id": 8,
"type": "column",
"value": "hero_id"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
15,301
|
restaurant
|
bird:train.json:1761
|
Among all indian restaurants in Castro St., Mountainview, how many of them is about cookhouse in their label?
|
SELECT COUNT(T1.id_restaurant) FROM location AS T1 INNER JOIN generalinfo AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T1.street_name = 'castro st' AND T1.city = 'mountain view' AND T2.food_type = 'indian' AND T2.label LIKE '%cookhouse%'
|
[
"Among",
"all",
"indian",
"restaurants",
"in",
"Castro",
"St.",
",",
"Mountainview",
",",
"how",
"many",
"of",
"them",
"is",
"about",
"cookhouse",
"in",
"their",
"label",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "id_restaurant"
},
{
"id": 6,
"type": "value",
"value": "mountain view"
},
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 3,
"type": "column",
"value": "street_name"
},
{
"id": 10,
"type": "value",
"value": "%cookhouse%"
},
{
"id": 4,
"type": "value",
"value": "castro st"
},
{
"id": 7,
"type": "column",
"value": "food_type"
},
{
"id": 0,
"type": "table",
"value": "location"
},
{
"id": 8,
"type": "value",
"value": "indian"
},
{
"id": 9,
"type": "column",
"value": "label"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
2
]
},
{
"entity_id": 9,
"token_idxs": [
19
]
},
{
"entity_id": 10,
"token_idxs": [
16
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
15,302
|
department_store
|
spider:train_spider.json:4717
|
What are the staff ids and genders of all staffs whose job title is Department Manager?
|
SELECT T1.staff_id , T1.staff_gender FROM staff AS T1 JOIN staff_department_assignments AS T2 ON T1.staff_id = T2.staff_id WHERE T2.job_title_code = "Department Manager"
|
[
"What",
"are",
"the",
"staff",
"ids",
"and",
"genders",
"of",
"all",
"staffs",
"whose",
"job",
"title",
"is",
"Department",
"Manager",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "staff_department_assignments"
},
{
"id": 5,
"type": "column",
"value": "Department Manager"
},
{
"id": 4,
"type": "column",
"value": "job_title_code"
},
{
"id": 1,
"type": "column",
"value": "staff_gender"
},
{
"id": 0,
"type": "column",
"value": "staff_id"
},
{
"id": 2,
"type": "table",
"value": "staff"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
14,
15
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,303
|
pilot_1
|
bird:test.json:1161
|
Find the max age for each group of pilots with the same name.
|
SELECT max(age) , pilot_name FROM pilotskills GROUP BY pilot_name
|
[
"Find",
"the",
"max",
"age",
"for",
"each",
"group",
"of",
"pilots",
"with",
"the",
"same",
"name",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 1,
"type": "column",
"value": "pilot_name"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
15,304
|
shooting
|
bird:train.json:2472
|
From the cases where the subject were deceased, list the subject's last name, gender, race and case number.
|
SELECT T2.last_name, T2.gender, T2.race, T2.case_number FROM incidents AS T1 INNER JOIN subjects AS T2 ON T1.case_number = T2.case_number WHERE T1.subject_statuses = 'Deceased'
|
[
"From",
"the",
"cases",
"where",
"the",
"subject",
"were",
"deceased",
",",
"list",
"the",
"subject",
"'s",
"last",
"name",
",",
"gender",
",",
"race",
"and",
"case",
"number",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "subject_statuses"
},
{
"id": 3,
"type": "column",
"value": "case_number"
},
{
"id": 0,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "table",
"value": "incidents"
},
{
"id": 5,
"type": "table",
"value": "subjects"
},
{
"id": 7,
"type": "value",
"value": "Deceased"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 2,
"type": "column",
"value": "race"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13,
14
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
20,
21
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11,
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,305
|
soccer_2
|
spider:train_spider.json:4951
|
How many different players trained for more than 1000 hours?
|
SELECT count(*) FROM Player WHERE HS > 1000
|
[
"How",
"many",
"different",
"players",
"trained",
"for",
"more",
"than",
"1000",
"hours",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 2,
"type": "value",
"value": "1000"
},
{
"id": 1,
"type": "column",
"value": "hs"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,306
|
retails
|
bird:train.json:6738
|
List the suppliers' names which supplied smoke red pale saddle plum.
|
SELECT T3.s_name FROM part AS T1 INNER JOIN partsupp AS T2 ON T1.p_partkey = T2.ps_partkey INNER JOIN supplier AS T3 ON T2.ps_suppkey = T3.s_suppkey WHERE T1.p_name = 'smoke red pale saddle plum'
|
[
"List",
"the",
"suppliers",
"'",
"names",
"which",
"supplied",
"smoke",
"red",
"pale",
"saddle",
"plum",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "smoke red pale saddle plum"
},
{
"id": 6,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 9,
"type": "column",
"value": "ps_partkey"
},
{
"id": 7,
"type": "column",
"value": "s_suppkey"
},
{
"id": 8,
"type": "column",
"value": "p_partkey"
},
{
"id": 1,
"type": "table",
"value": "supplier"
},
{
"id": 5,
"type": "table",
"value": "partsupp"
},
{
"id": 0,
"type": "column",
"value": "s_name"
},
{
"id": 2,
"type": "column",
"value": "p_name"
},
{
"id": 4,
"type": "table",
"value": "part"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
15,307
|
department_store
|
spider:train_spider.json:4766
|
Return the phone numbers for all customers and suppliers.
|
SELECT customer_phone FROM customers UNION SELECT supplier_phone FROM suppliers
|
[
"Return",
"the",
"phone",
"numbers",
"for",
"all",
"customers",
"and",
"suppliers",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "customer_phone"
},
{
"id": 3,
"type": "column",
"value": "supplier_phone"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "table",
"value": "suppliers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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",
"B-TABLE",
"O"
] |
15,308
|
apartment_rentals
|
spider:train_spider.json:1237
|
Which guests have apartment bookings with status code "Confirmed"? Return their first names and last names.
|
SELECT T2.guest_first_name , T2.guest_last_name FROM Apartment_Bookings AS T1 JOIN Guests AS T2 ON T1.guest_id = T2.guest_id WHERE T1.booking_status_code = "Confirmed"
|
[
"Which",
"guests",
"have",
"apartment",
"bookings",
"with",
"status",
"code",
"\"",
"Confirmed",
"\"",
"?",
"Return",
"their",
"first",
"names",
"and",
"last",
"names",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "booking_status_code"
},
{
"id": 2,
"type": "table",
"value": "apartment_bookings"
},
{
"id": 0,
"type": "column",
"value": "guest_first_name"
},
{
"id": 1,
"type": "column",
"value": "guest_last_name"
},
{
"id": 5,
"type": "column",
"value": "Confirmed"
},
{
"id": 6,
"type": "column",
"value": "guest_id"
},
{
"id": 3,
"type": "table",
"value": "guests"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14,
15
]
},
{
"entity_id": 1,
"token_idxs": [
17,
18
]
},
{
"entity_id": 2,
"token_idxs": [
3,
4
]
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,309
|
music_platform_2
|
bird:train.json:7943
|
How many total reviews runned at in June 2022 were added to the podcasts?
|
SELECT SUM(reviews_added) FROM runs WHERE run_at LIKE '2022-06-%'
|
[
"How",
"many",
"total",
"reviews",
"runned",
"at",
"in",
"June",
"2022",
"were",
"added",
"to",
"the",
"podcasts",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "reviews_added"
},
{
"id": 2,
"type": "value",
"value": "2022-06-%"
},
{
"id": 1,
"type": "column",
"value": "run_at"
},
{
"id": 0,
"type": "table",
"value": "runs"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,310
|
cinema
|
spider:train_spider.json:1948
|
Who are all the directors?
|
SELECT DISTINCT directed_by FROM film
|
[
"Who",
"are",
"all",
"the",
"directors",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "directed_by"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,311
|
hr_1
|
spider:train_spider.json:3407
|
List the full name (first and last name), and salary for those employees who earn below 6000.
|
SELECT first_name , last_name , salary FROM employees WHERE salary < 6000
|
[
"List",
"the",
"full",
"name",
"(",
"first",
"and",
"last",
"name",
")",
",",
"and",
"salary",
"for",
"those",
"employees",
"who",
"earn",
"below",
"6000",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "salary"
},
{
"id": 4,
"type": "value",
"value": "6000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
19
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,312
|
retail_world
|
bird:train.json:6371
|
What is the name of the supplier that supplies the most products to the company?
|
SELECT T1.SupplierID FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID GROUP BY T1.SupplierID ORDER BY COUNT(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"supplier",
"that",
"supplies",
"the",
"most",
"products",
"to",
"the",
"company",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
15,313
|
customers_and_products_contacts
|
spider:train_spider.json:5654
|
Show all distinct cities in the address record.
|
SELECT DISTINCT city FROM addresses
|
[
"Show",
"all",
"distinct",
"cities",
"in",
"the",
"address",
"record",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "addresses"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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"
] |
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