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744
|
voter_2
|
spider:train_spider.json:5464
|
What are the distinct secretary votes in the fall election cycle?
|
SELECT DISTINCT Secretary_Vote FROM VOTING_RECORD WHERE ELECTION_CYCLE = "Fall"
|
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"secretary",
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"in",
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"fall",
"election",
"cycle",
"?"
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{
"id": 1,
"type": "column",
"value": "secretary_vote"
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{
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"value": "election_cycle"
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{
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"type": "table",
"value": "voting_record"
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{
"id": 3,
"type": "column",
"value": "Fall"
}
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"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O"
] |
745
|
language_corpus
|
bird:train.json:5758
|
List out the title of Catalan language Wikipedia page that has wikipedia revision page id as 106601.
|
SELECT title FROM pages WHERE revision = 106601
|
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"."
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"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
746
|
mondial_geo
|
bird:train.json:8319
|
Which island is city Balikpapan located on? How big is the island?
|
SELECT T3.Name, T3.Area FROM city AS T1 INNER JOIN locatedOn AS T2 ON T1.Name = T2.City INNER JOIN island AS T3 ON T3.Name = T2.Island WHERE T1.Name = 'Balikpapan'
|
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"?"
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"id": 7,
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"value": "city"
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"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
747
|
driving_school
|
spider:train_spider.json:6644
|
Which country and state does staff with first name as Janessa and last name as Sawayn lived?
|
SELECT T1.country , T1.state_province_county FROM Addresses AS T1 JOIN Staff AS T2 ON T1.address_id = T2.staff_address_id WHERE T2.first_name = "Janessa" AND T2.last_name = "Sawayn";
|
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"?"
] |
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"id": 5,
"type": "column",
"value": "staff_address_id"
},
{
"id": 4,
"type": "column",
"value": "address_id"
},
{
"id": 6,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "table",
"value": "addresses"
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{
"id": 8,
"type": "column",
"value": "last_name"
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{
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"value": "country"
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{
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"type": "column",
"value": "Sawayn"
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{
"id": 3,
"type": "table",
"value": "staff"
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"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
748
|
talkingdata
|
bird:train.json:1053
|
What is the gender of the majority of Vivo phone users?
|
SELECT T.gender FROM ( SELECT T2.gender, COUNT(T2.gender) AS num FROM phone_brand_device_model2 AS T1 INNER JOIN gender_age AS T2 ON T2.device_id = T1.device_id WHERE T1.phone_brand = 'vivo' GROUP BY T2.gender ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"What",
"is",
"the",
"gender",
"of",
"the",
"majority",
"of",
"Vivo",
"phone",
"users",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 4,
"type": "column",
"value": "phone_brand"
},
{
"id": 3,
"type": "table",
"value": "gender_age"
},
{
"id": 6,
"type": "column",
"value": "device_id"
},
{
"id": 0,
"type": "column",
"value": "gender"
},
{
"id": 5,
"type": "value",
"value": "vivo"
},
{
"id": 1,
"type": "column",
"value": "num"
}
] |
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"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O"
] |
749
|
movie_3
|
bird:train.json:9198
|
What is the full name of the actor who has the highest number of restricted films?
|
SELECT T.first_name, T.last_name FROM ( SELECT T1.first_name, T1.last_name, COUNT(T2.film_id) AS num FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T2.film_id = T3.film_id WHERE T3.rating = 'R' GROUP BY T1.first_name, T1.last_name ) AS T ORDER BY T.num DESC LIMIT 1
|
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{
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"value": "film_id"
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{
"id": 4,
"type": "column",
"value": "rating"
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{
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"value": "film"
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{
"id": 2,
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"value": "num"
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{
"id": 5,
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"value": "R"
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751
|
bakery_1
|
bird:test.json:1533
|
On which date did some customer buy a good that costs more than 15 dollars?
|
SELECT DISTINCT T1.date FROM receipts AS T1 JOIN items AS T2 ON T1.ReceiptNumber = T2.receipt JOIN goods AS T3 ON T2.item = T3.id WHERE T3.price > 15
|
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{
"id": 8,
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{
"id": 9,
"type": "column",
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{
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"O",
"O"
] |
752
|
assets_maintenance
|
spider:train_spider.json:3144
|
Which kind of part has the least number of faults? List the part name.
|
SELECT T1.part_name FROM Parts AS T1 JOIN Part_Faults AS T2 ON T1.part_id = T2.part_id GROUP BY T1.part_name ORDER BY count(*) ASC LIMIT 1
|
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"type": "column",
"value": "part_id"
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{
"id": 1,
"type": "table",
"value": "parts"
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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-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
753
|
customers_and_orders
|
bird:test.json:296
|
Give the id, name, phone, and email corresponding to the customer who made the most orders.
|
SELECT T1.customer_id , T2.customer_name , T2.customer_phone , T2.customer_email FROM Customer_orders AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id ORDER BY count(*) DESC LIMIT 1
|
[
"Give",
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"i",
"d",
",",
"name",
",",
"phone",
",",
"and",
"email",
"corresponding",
"to",
"the",
"customer",
"who",
"made",
"the",
"most",
"orders",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "customer_orders"
},
{
"id": 2,
"type": "column",
"value": "customer_phone"
},
{
"id": 3,
"type": "column",
"value": "customer_email"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "column",
"value": "customer_id"
},
{
"id": 5,
"type": "table",
"value": "customers"
}
] |
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{
"entity_id": 0,
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"entity_id": 1,
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{
"entity_id": 2,
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15
]
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"token_idxs": []
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"entity_id": 4,
"token_idxs": []
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"entity_id": 5,
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14
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"entity_id": 8,
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"entity_id": 9,
"token_idxs": []
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},
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"entity_id": 13,
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},
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"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
754
|
coinmarketcap
|
bird:train.json:6293
|
When is the highest price of Terracoin?
|
SELECT T2.date FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'Terracoin' ORDER BY T2.price DESC LIMIT 1
|
[
"When",
"is",
"the",
"highest",
"price",
"of",
"Terracoin",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 4,
"type": "value",
"value": "Terracoin"
},
{
"id": 7,
"type": "column",
"value": "coin_id"
},
{
"id": 1,
"type": "table",
"value": "coins"
},
{
"id": 5,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
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"entity_id": 11,
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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-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
755
|
books
|
bird:train.json:6087
|
What is the title of the first book that was written by A.J. Ayer?
|
SELECT T1.title FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T3.author_name = 'A.J. Ayer' ORDER BY T1.publication_date ASC LIMIT 1
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"first",
"book",
"that",
"was",
"written",
"by",
"A.J.",
"Ayer",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "publication_date"
},
{
"id": 2,
"type": "column",
"value": "author_name"
},
{
"id": 6,
"type": "table",
"value": "book_author"
},
{
"id": 3,
"type": "value",
"value": "A.J. Ayer"
},
{
"id": 7,
"type": "column",
"value": "author_id"
},
{
"id": 8,
"type": "column",
"value": "book_id"
},
{
"id": 1,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "table",
"value": "book"
}
] |
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"entity_id": 0,
"token_idxs": [
3
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{
"entity_id": 1,
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{
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},
{
"entity_id": 3,
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13
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{
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"entity_id": 5,
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{
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{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
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},
{
"entity_id": 13,
"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
756
|
professional_basketball
|
bird:train.json:2807
|
What is the percentage of player who won "All-Defensive First Team" from 1980 - 2000 is from 'NY'.
|
SELECT COUNT(DISTINCT T1.playerID) FROM players AS T1 INNER JOIN awards_players AS T2 ON T1.playerID = T2.playerID WHERE T1.birthState = 'NY' AND T2.award = 'All-Defensive First Team' AND T2.year BETWEEN 1980 AND 2000
|
[
"What",
"is",
"the",
"percentage",
"of",
"player",
"who",
"won",
"\"",
"All",
"-",
"Defensive",
"First",
"Team",
"\"",
"from",
"1980",
"-",
"2000",
"is",
"from",
"'",
"NY",
"'",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "All-Defensive First Team"
},
{
"id": 1,
"type": "table",
"value": "awards_players"
},
{
"id": 3,
"type": "column",
"value": "birthstate"
},
{
"id": 2,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "players"
},
{
"id": 5,
"type": "column",
"value": "award"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "1980"
},
{
"id": 9,
"type": "value",
"value": "2000"
},
{
"id": 4,
"type": "value",
"value": "NY"
}
] |
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{
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},
{
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},
{
"entity_id": 3,
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12,
13
]
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{
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22
]
},
{
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},
{
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9,
10,
11
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},
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5
]
},
{
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16
]
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18
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},
{
"entity_id": 12,
"token_idxs": []
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"entity_id": 13,
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{
"entity_id": 14,
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"entity_id": 15,
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{
"entity_id": 16,
"token_idxs": []
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{
"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",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
758
|
hockey
|
bird:train.json:7726
|
Which country produced the most number of hockey players? Identify which year was most of the hockey players are born.
|
SELECT DISTINCT birthCountry, birthYear FROM Master GROUP BY birthCountry, birthYear ORDER BY COUNT(birthCountry) DESC LIMIT 1
|
[
"Which",
"country",
"produced",
"the",
"most",
"number",
"of",
"hockey",
"players",
"?",
"Identify",
"which",
"year",
"was",
"most",
"of",
"the",
"hockey",
"players",
"are",
"born",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "birthcountry"
},
{
"id": 2,
"type": "column",
"value": "birthyear"
},
{
"id": 0,
"type": "table",
"value": "master"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
11,
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,
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
759
|
storm_record
|
spider:train_spider.json:2691
|
Count the number of regions.
|
SELECT count(*) FROM region
|
[
"Count",
"the",
"number",
"of",
"regions",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "region"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
760
|
retail_complains
|
bird:train.json:304
|
What is the name of the state in which there have been the largest number of complaints with priority 0?
|
SELECT T2.state FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN district AS T3 ON T2.district_id = T3.district_id INNER JOIN state AS T4 ON T3.state_abbrev = T4.StateCode WHERE T1.priority = 0 GROUP BY T2.state ORDER BY COUNT(T2.state) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"state",
"in",
"which",
"there",
"have",
"been",
"the",
"largest",
"number",
"of",
"complaints",
"with",
"priority",
"0",
"?"
] |
[
{
"id": 7,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 5,
"type": "column",
"value": "state_abbrev"
},
{
"id": 9,
"type": "column",
"value": "district_id"
},
{
"id": 10,
"type": "column",
"value": "rand client"
},
{
"id": 6,
"type": "column",
"value": "statecode"
},
{
"id": 11,
"type": "column",
"value": "client_id"
},
{
"id": 2,
"type": "column",
"value": "priority"
},
{
"id": 4,
"type": "table",
"value": "district"
},
{
"id": 8,
"type": "table",
"value": "client"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 1,
"type": "table",
"value": "state"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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{
"entity_id": 9,
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{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
761
|
thrombosis_prediction
|
bird:dev.json:1217
|
For all patient born in 1982, state if their albumin is within normal range.
|
SELECT CASE WHEN T2.ALB >= 3.5 AND T2.ALB <= 5.5 THEN 'normal' ELSE 'abnormal' END FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE STRFTIME('%Y', T1.Birthday) = '1982'
|
[
"For",
"all",
"patient",
"born",
"in",
"1982",
",",
"state",
"if",
"their",
"albumin",
"is",
"within",
"normal",
"range",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 3,
"type": "value",
"value": "abnormal"
},
{
"id": 6,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 7,
"type": "value",
"value": "normal"
},
{
"id": 2,
"type": "value",
"value": "1982"
},
{
"id": 8,
"type": "column",
"value": "alb"
},
{
"id": 9,
"type": "value",
"value": "3.5"
},
{
"id": 10,
"type": "value",
"value": "5.5"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
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},
{
"entity_id": 2,
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5
]
},
{
"entity_id": 3,
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},
{
"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": [
1
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
762
|
beer_factory
|
bird:train.json:5348
|
What is the percentage difference of River City sale compare to Frostie?
|
SELECT CAST((SUM(CASE WHEN T3.BrandName = 'River City' THEN T2.PurchasePrice ELSE 0 END) - SUM(CASE WHEN T3.BrandName = 'Frostie' THEN T2.PurchasePrice ELSE 0 END)) AS REAL) * 100 / SUM(CASE WHEN T3.BrandName = 'Frostie' THEN T2.PurchasePrice ELSE 0 END) FROM rootbeer AS T1 INNER JOIN `transaction` AS T2 ON T1.RootBeerID = T2.RootBeerID INNER JOIN rootbeerbrand AS T3 ON T1.BrandID = T3.BrandID
|
[
"What",
"is",
"the",
"percentage",
"difference",
"of",
"River",
"City",
"sale",
"compare",
"to",
"Frostie",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "rootbeerbrand"
},
{
"id": 7,
"type": "column",
"value": "purchaseprice"
},
{
"id": 2,
"type": "table",
"value": "transaction"
},
{
"id": 5,
"type": "column",
"value": "rootbeerid"
},
{
"id": 10,
"type": "value",
"value": "River City"
},
{
"id": 8,
"type": "column",
"value": "brandname"
},
{
"id": 1,
"type": "table",
"value": "rootbeer"
},
{
"id": 3,
"type": "column",
"value": "brandid"
},
{
"id": 9,
"type": "value",
"value": "Frostie"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": [
6,
7
]
},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
763
|
manufactory_1
|
spider:train_spider.json:5274
|
Where is the headquarter of the company founded by James?
|
SELECT headquarter FROM manufacturers WHERE founder = 'James'
|
[
"Where",
"is",
"the",
"headquarter",
"of",
"the",
"company",
"founded",
"by",
"James",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "manufacturers"
},
{
"id": 1,
"type": "column",
"value": "headquarter"
},
{
"id": 2,
"type": "column",
"value": "founder"
},
{
"id": 3,
"type": "value",
"value": "James"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
764
|
olympics
|
bird:train.json:4982
|
Which summer Olympic have the highest and lowest number of participants?
|
SELECT ( SELECT T1.games_name FROM games AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.games_id WHERE T1.season = 'Summer' GROUP BY T1.games_year ORDER BY COUNT(T2.person_id) DESC LIMIT 1 ) AS HIGHEST , ( SELECT T1.games_name FROM games AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.games_id WHERE T1.season = 'Summer' GROUP BY T1.games_year ORDER BY COUNT(T2.person_id) LIMIT 1 ) AS LOWEST
|
[
"Which",
"summer",
"Olympic",
"have",
"the",
"highest",
"and",
"lowest",
"number",
"of",
"participants",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "games_competitor"
},
{
"id": 0,
"type": "column",
"value": "games_year"
},
{
"id": 1,
"type": "column",
"value": "games_name"
},
{
"id": 8,
"type": "column",
"value": "person_id"
},
{
"id": 7,
"type": "column",
"value": "games_id"
},
{
"id": 4,
"type": "column",
"value": "season"
},
{
"id": 5,
"type": "value",
"value": "Summer"
},
{
"id": 2,
"type": "table",
"value": "games"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
1
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
765
|
dorm_1
|
spider:train_spider.json:5685
|
How many students exist?
|
SELECT count(*) FROM student
|
[
"How",
"many",
"students",
"exist",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "student"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O"
] |
766
|
party_people
|
spider:train_spider.json:2056
|
What are the names of members and their corresponding parties?
|
SELECT T1.member_name , T2.party_name FROM Member AS T1 JOIN party AS T2 ON T1.party_id = T2.party_id
|
[
"What",
"are",
"the",
"names",
"of",
"members",
"and",
"their",
"corresponding",
"parties",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "member_name"
},
{
"id": 1,
"type": "column",
"value": "party_name"
},
{
"id": 4,
"type": "column",
"value": "party_id"
},
{
"id": 2,
"type": "table",
"value": "member"
},
{
"id": 3,
"type": "table",
"value": "party"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1,
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
767
|
theme_gallery
|
spider:train_spider.json:1671
|
Show names for artists without any exhibition.
|
SELECT name FROM artist WHERE artist_id NOT IN (SELECT artist_id FROM exhibition)
|
[
"Show",
"names",
"for",
"artists",
"without",
"any",
"exhibition",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "exhibition"
},
{
"id": 2,
"type": "column",
"value": "artist_id"
},
{
"id": 0,
"type": "table",
"value": "artist"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O"
] |
768
|
retail_complains
|
bird:train.json:252
|
Among the clients who did receive a timely response for their complaint, how many of them are from New York?
|
SELECT COUNT(T1.city) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Timely response?` = 'No' AND T1.city = 'New York City'
|
[
"Among",
"the",
"clients",
"who",
"did",
"receive",
"a",
"timely",
"response",
"for",
"their",
"complaint",
",",
"how",
"many",
"of",
"them",
"are",
"from",
"New",
"York",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "Timely response?"
},
{
"id": 6,
"type": "value",
"value": "New York City"
},
{
"id": 3,
"type": "column",
"value": "client_id"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "table",
"value": "events"
},
{
"id": 2,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "No"
}
] |
[
{
"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": [
7,
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
19,
20
]
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
769
|
movies_4
|
bird:train.json:511
|
Are there any post-production movies in Nederlands?
|
SELECT DISTINCT CASE WHEN T1.movie_status = 'Post Production' THEN 'YES' ELSE 'NO' END AS YORN FROM movie AS T1 INNER JOIN movie_languages AS T2 ON T1.movie_id = T2.movie_id INNER JOIN language AS T3 ON T2.language_id = T3.language_id WHERE T3.language_name = 'Nederlands'
|
[
"Are",
"there",
"any",
"post",
"-",
"production",
"movies",
"in",
"Nederlands",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "movie_languages"
},
{
"id": 10,
"type": "value",
"value": "Post Production"
},
{
"id": 1,
"type": "column",
"value": "language_name"
},
{
"id": 9,
"type": "column",
"value": "movie_status"
},
{
"id": 6,
"type": "column",
"value": "language_id"
},
{
"id": 2,
"type": "value",
"value": "Nederlands"
},
{
"id": 0,
"type": "table",
"value": "language"
},
{
"id": 8,
"type": "column",
"value": "movie_id"
},
{
"id": 4,
"type": "table",
"value": "movie"
},
{
"id": 7,
"type": "value",
"value": "YES"
},
{
"id": 3,
"type": "value",
"value": "NO"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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8
]
},
{
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},
{
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6
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},
{
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},
{
"entity_id": 6,
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},
{
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},
{
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7
]
},
{
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},
{
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3,
4,
5
]
},
{
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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,
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},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
770
|
gas_company
|
spider:train_spider.json:2026
|
What are the main industries of the companies without gas stations and what are the companies?
|
SELECT company , main_industry FROM company WHERE company_id NOT IN (SELECT company_id FROM station_company)
|
[
"What",
"are",
"the",
"main",
"industries",
"of",
"the",
"companies",
"without",
"gas",
"stations",
"and",
"what",
"are",
"the",
"companies",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "station_company"
},
{
"id": 2,
"type": "column",
"value": "main_industry"
},
{
"id": 3,
"type": "column",
"value": "company_id"
},
{
"id": 0,
"type": "table",
"value": "company"
},
{
"id": 1,
"type": "column",
"value": "company"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": [
3,
4
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
10,
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
772
|
tracking_software_problems
|
spider:train_spider.json:5392
|
Find the top 3 products which have the largest number of problems?
|
SELECT T2.product_name FROM problems AS T1 JOIN product AS T2 ON T1.product_id = T2.product_id GROUP BY T2.product_name ORDER BY count(*) DESC LIMIT 3
|
[
"Find",
"the",
"top",
"3",
"products",
"which",
"have",
"the",
"largest",
"number",
"of",
"problems",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "product_name"
},
{
"id": 3,
"type": "column",
"value": "product_id"
},
{
"id": 1,
"type": "table",
"value": "problems"
},
{
"id": 2,
"type": "table",
"value": "product"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"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-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
773
|
books
|
bird:train.json:6013
|
What are the city addresses of the customers located in the United States of America?
|
SELECT DISTINCT T2.city FROM country AS T1 INNER JOIN address AS T2 ON T1.country_id = T2.country_id WHERE T1.country_name = 'United States of America'
|
[
"What",
"are",
"the",
"city",
"addresses",
"of",
"the",
"customers",
"located",
"in",
"the",
"United",
"States",
"of",
"America",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "United States of America"
},
{
"id": 3,
"type": "column",
"value": "country_name"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "address"
},
{
"id": 0,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12,
13,
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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
774
|
cre_Doc_and_collections
|
bird:test.json:666
|
What are the document subset names?
|
SELECT Document_Subset_Name FROM Document_Subsets;
|
[
"What",
"are",
"the",
"document",
"subset",
"names",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "document_subset_name"
},
{
"id": 0,
"type": "table",
"value": "document_subsets"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O"
] |
775
|
california_schools
|
bird:dev.json:38
|
What are the webpages for the Los Angeles County school that has between 2,000 and 3,000 test takers?
|
SELECT T2.Website FROM satscores AS T1 INNER JOIN schools AS T2 ON T1.cds = T2.CDSCode WHERE T1.NumTstTakr BETWEEN 2000 AND 3000 AND T2.County = 'Los Angeles'
|
[
"What",
"are",
"the",
"webpages",
"for",
"the",
"Los",
"Angeles",
"County",
"school",
"that",
"has",
"between",
"2,000",
"and",
"3,000",
"test",
"takers",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "Los Angeles"
},
{
"id": 5,
"type": "column",
"value": "numtsttakr"
},
{
"id": 1,
"type": "table",
"value": "satscores"
},
{
"id": 0,
"type": "column",
"value": "website"
},
{
"id": 2,
"type": "table",
"value": "schools"
},
{
"id": 4,
"type": "column",
"value": "cdscode"
},
{
"id": 8,
"type": "column",
"value": "county"
},
{
"id": 6,
"type": "value",
"value": "2000"
},
{
"id": 7,
"type": "value",
"value": "3000"
},
{
"id": 3,
"type": "column",
"value": "cds"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16,
17
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": [
6,
7
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
776
|
mondial_geo
|
bird:train.json:8253
|
How many lakes in the Canary Islands cover an area of over 1000000?
|
SELECT COUNT(T2.Name) FROM located AS T1 INNER JOIN lake AS T2 ON T1.Lake = T2.Name WHERE T1.Province = 'Canary Islands' AND T2.Area > 1000000
|
[
"How",
"many",
"lakes",
"in",
"the",
"Canary",
"Islands",
"cover",
"an",
"area",
"of",
"over",
"1000000",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Canary Islands"
},
{
"id": 4,
"type": "column",
"value": "province"
},
{
"id": 0,
"type": "table",
"value": "located"
},
{
"id": 7,
"type": "value",
"value": "1000000"
},
{
"id": 1,
"type": "table",
"value": "lake"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "lake"
},
{
"id": 6,
"type": "column",
"value": "area"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5,
6
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
777
|
insurance_fnol
|
spider:train_spider.json:918
|
Count the total number of available services.
|
SELECT count(*) FROM services
|
[
"Count",
"the",
"total",
"number",
"of",
"available",
"services",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "services"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
778
|
movie
|
bird:train.json:750
|
When is the birthday of the actor who played "Sully"?
|
SELECT T2.`Date of Birth` FROM characters AS T1 INNER JOIN actor AS T2 ON T1.ActorID = T2.ActorID WHERE T1.`Character Name` = 'Sully'
|
[
"When",
"is",
"the",
"birthday",
"of",
"the",
"actor",
"who",
"played",
"\"",
"Sully",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Character Name"
},
{
"id": 0,
"type": "column",
"value": "Date of Birth"
},
{
"id": 1,
"type": "table",
"value": "characters"
},
{
"id": 5,
"type": "column",
"value": "actorid"
},
{
"id": 2,
"type": "table",
"value": "actor"
},
{
"id": 4,
"type": "value",
"value": "Sully"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
779
|
music_2
|
spider:train_spider.json:5172
|
How many bands are there?
|
SELECT count(*) FROM Band
|
[
"How",
"many",
"bands",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "band"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
780
|
codebase_community
|
bird:dev.json:646
|
Describe the post title which got positive comments and display names of the users who posted those comments.
|
SELECT T1.Title, T2.UserDisplayName FROM posts AS T1 INNER JOIN comments AS T2 ON T2.PostId = T2.Id WHERE T1.Score > 60
|
[
"Describe",
"the",
"post",
"title",
"which",
"got",
"positive",
"comments",
"and",
"display",
"names",
"of",
"the",
"users",
"who",
"posted",
"those",
"comments",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "userdisplayname"
},
{
"id": 3,
"type": "table",
"value": "comments"
},
{
"id": 6,
"type": "column",
"value": "postid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "posts"
},
{
"id": 4,
"type": "column",
"value": "score"
},
{
"id": 5,
"type": "value",
"value": "60"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
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3
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},
{
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{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
781
|
movie
|
bird:train.json:742
|
What is the average rating of all the movies starring Tom Cruise?
|
SELECT AVG(T1.Rating) FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE T3.Name = 'Tom Cruise'
|
[
"What",
"is",
"the",
"average",
"rating",
"of",
"all",
"the",
"movies",
"starring",
"Tom",
"Cruise",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "Tom Cruise"
},
{
"id": 5,
"type": "table",
"value": "characters"
},
{
"id": 6,
"type": "column",
"value": "actorid"
},
{
"id": 7,
"type": "column",
"value": "movieid"
},
{
"id": 3,
"type": "column",
"value": "rating"
},
{
"id": 0,
"type": "table",
"value": "actor"
},
{
"id": 4,
"type": "table",
"value": "movie"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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{
"entity_id": 0,
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{
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{
"entity_id": 14,
"token_idxs": []
},
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
782
|
bakery_1
|
bird:test.json:1510
|
What are the average, minimum and maximum prices for each food?
|
SELECT food , avg(price) , max(price) , min(price) FROM goods GROUP BY food
|
[
"What",
"are",
"the",
"average",
",",
"minimum",
"and",
"maximum",
"prices",
"for",
"each",
"food",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "column",
"value": "food"
}
] |
[
{
"entity_id": 0,
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11
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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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"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",
"B-COLUMN",
"O"
] |
783
|
book_publishing_company
|
bird:train.json:176
|
List all titles with sales of quantity more than 20 and store located in the CA state.
|
SELECT T1.title, T2.qty FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id INNER JOIN stores AS T3 ON T2.stor_id = T3.stor_id WHERE T2.qty > 20 AND T3.state = 'CA'
|
[
"List",
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"with",
"sales",
"of",
"quantity",
"more",
"than",
"20",
"and",
"store",
"located",
"in",
"the",
"CA",
"state",
"."
] |
[
{
"id": 9,
"type": "column",
"value": "title_id"
},
{
"id": 5,
"type": "column",
"value": "stor_id"
},
{
"id": 2,
"type": "table",
"value": "stores"
},
{
"id": 3,
"type": "table",
"value": "titles"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "table",
"value": "sales"
},
{
"id": 7,
"type": "column",
"value": "state"
},
{
"id": 1,
"type": "column",
"value": "qty"
},
{
"id": 6,
"type": "value",
"value": "20"
},
{
"id": 8,
"type": "value",
"value": "CA"
}
] |
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},
{
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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",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
784
|
flight_1
|
spider:train_spider.json:368
|
What is the number of employees that have a salary between 100000 and 200000?
|
SELECT count(*) FROM Employee WHERE salary BETWEEN 100000 AND 200000
|
[
"What",
"is",
"the",
"number",
"of",
"employees",
"that",
"have",
"a",
"salary",
"between",
"100000",
"and",
"200000",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "column",
"value": "salary"
},
{
"id": 2,
"type": "value",
"value": "100000"
},
{
"id": 3,
"type": "value",
"value": "200000"
}
] |
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{
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{
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},
{
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},
{
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},
{
"entity_id": 16,
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},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
785
|
college_3
|
spider:train_spider.json:4659
|
List all information about courses sorted by credits in the ascending order.
|
SELECT * FROM COURSE ORDER BY Credits
|
[
"List",
"all",
"information",
"about",
"courses",
"sorted",
"by",
"credits",
"in",
"the",
"ascending",
"order",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "credits"
},
{
"id": 0,
"type": "table",
"value": "course"
}
] |
[
{
"entity_id": 0,
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4
]
},
{
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7
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 13,
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
786
|
products_gen_characteristics
|
spider:train_spider.json:5551
|
What are the names of products with 'white' as their color description?
|
SELECT t1.product_name FROM products AS t1 JOIN ref_colors AS t2 ON t1.color_code = t2.color_code WHERE t2.color_description = "white"
|
[
"What",
"are",
"the",
"names",
"of",
"products",
"with",
"'",
"white",
"'",
"as",
"their",
"color",
"description",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "color_description"
},
{
"id": 0,
"type": "column",
"value": "product_name"
},
{
"id": 2,
"type": "table",
"value": "ref_colors"
},
{
"id": 5,
"type": "column",
"value": "color_code"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 4,
"type": "column",
"value": "white"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
788
|
tracking_grants_for_research
|
spider:train_spider.json:4363
|
For each staff id, what is the description of the role that is involved with the most number of projects?
|
SELECT T1.role_description , T2.staff_id FROM Staff_Roles AS T1 JOIN Project_Staff AS T2 ON T1.role_code = T2.role_code JOIN Project_outcomes AS T3 ON T2.project_id = T3.project_id GROUP BY T2.staff_id ORDER BY count(*) DESC LIMIT 1
|
[
"For",
"each",
"staff",
"i",
"d",
",",
"what",
"is",
"the",
"description",
"of",
"the",
"role",
"that",
"is",
"involved",
"with",
"the",
"most",
"number",
"of",
"projects",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "role_description"
},
{
"id": 2,
"type": "table",
"value": "project_outcomes"
},
{
"id": 4,
"type": "table",
"value": "project_staff"
},
{
"id": 3,
"type": "table",
"value": "staff_roles"
},
{
"id": 5,
"type": "column",
"value": "project_id"
},
{
"id": 6,
"type": "column",
"value": "role_code"
},
{
"id": 0,
"type": "column",
"value": "staff_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
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9
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},
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{
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{
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},
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
789
|
toxicology
|
bird:dev.json:260
|
Calculate the total atoms with triple-bond molecules containing the element phosphorus or bromine.
|
SELECT COUNT(T1.atom_id) FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id INNER JOIN bond AS T3 ON T2.molecule_id = T3.molecule_id WHERE T3.bond_type = '#' AND T1.element IN ('p', 'br')
|
[
"Calculate",
"the",
"total",
"atoms",
"with",
"triple",
"-",
"bond",
"molecules",
"containing",
"the",
"element",
"phosphorus",
"or",
"bromine",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "molecule_id"
},
{
"id": 5,
"type": "column",
"value": "bond_type"
},
{
"id": 3,
"type": "table",
"value": "molecule"
},
{
"id": 1,
"type": "column",
"value": "atom_id"
},
{
"id": 7,
"type": "column",
"value": "element"
},
{
"id": 0,
"type": "table",
"value": "bond"
},
{
"id": 2,
"type": "table",
"value": "atom"
},
{
"id": 9,
"type": "value",
"value": "br"
},
{
"id": 6,
"type": "value",
"value": "#"
},
{
"id": 8,
"type": "value",
"value": "p"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
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"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
790
|
mondial_geo
|
bird:train.json:8241
|
How much is her GDP in agriculture for the country with the least area?
|
SELECT T2.GDP * T2.Agriculture FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country ORDER BY T1.Area ASC LIMIT 1
|
[
"How",
"much",
"is",
"her",
"GDP",
"in",
"agriculture",
"for",
"the",
"country",
"with",
"the",
"least",
"area",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "agriculture"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "economy"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "area"
},
{
"id": 5,
"type": "column",
"value": "code"
},
{
"id": 3,
"type": "column",
"value": "gdp"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
791
|
legislator
|
bird:train.json:4807
|
State the number of female legislators in the list.
|
SELECT COUNT(*) FROM current WHERE gender_bio = 'F'
|
[
"State",
"the",
"number",
"of",
"female",
"legislators",
"in",
"the",
"list",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "gender_bio"
},
{
"id": 0,
"type": "table",
"value": "current"
},
{
"id": 2,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
792
|
university
|
bird:train.json:8122
|
List down all universities that scored below 50.
|
SELECT DISTINCT T2.university_name FROM university_ranking_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T1.score < 50
|
[
"List",
"down",
"all",
"universities",
"that",
"scored",
"below",
"50",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 5,
"type": "column",
"value": "university_id"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 3,
"type": "column",
"value": "score"
},
{
"id": 4,
"type": "value",
"value": "50"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
793
|
superstore
|
bird:train.json:2390
|
Who is the customer from the West region that received the highest discount?
|
SELECT T2.`Customer Name` FROM west_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T1.Region = 'West' ORDER BY T1.Discount DESC LIMIT 1
|
[
"Who",
"is",
"the",
"customer",
"from",
"the",
"West",
"region",
"that",
"received",
"the",
"highest",
"discount",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "west_superstore"
},
{
"id": 0,
"type": "column",
"value": "Customer Name"
},
{
"id": 6,
"type": "column",
"value": "Customer ID"
},
{
"id": 5,
"type": "column",
"value": "discount"
},
{
"id": 2,
"type": "table",
"value": "people"
},
{
"id": 3,
"type": "column",
"value": "region"
},
{
"id": 4,
"type": "value",
"value": "West"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
794
|
wine_1
|
spider:train_spider.json:6548
|
Find the white grape used to produce wines with scores above 90.
|
SELECT DISTINCT T1.Grape FROM GRAPES AS T1 JOIN WINE AS T2 ON T1.Grape = T2.Grape WHERE T1.Color = "White" AND T2.score > 90
|
[
"Find",
"the",
"white",
"grape",
"used",
"to",
"produce",
"wines",
"with",
"scores",
"above",
"90",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "grapes"
},
{
"id": 0,
"type": "column",
"value": "grape"
},
{
"id": 3,
"type": "column",
"value": "color"
},
{
"id": 4,
"type": "column",
"value": "White"
},
{
"id": 5,
"type": "column",
"value": "score"
},
{
"id": 2,
"type": "table",
"value": "wine"
},
{
"id": 6,
"type": "value",
"value": "90"
}
] |
[
{
"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": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
795
|
aan_1
|
bird:test.json:1001
|
How many papers cite paper with id A00-1002?
|
SELECT count(*) FROM Citation WHERE cited_paper_id = "A00-1002"
|
[
"How",
"many",
"papers",
"cite",
"paper",
"with",
"i",
"d",
"A00",
"-",
"1002",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "cited_paper_id"
},
{
"id": 0,
"type": "table",
"value": "citation"
},
{
"id": 2,
"type": "column",
"value": "A00-1002"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
796
|
retail_complains
|
bird:train.json:381
|
Which city in the Midwest region has the least number of clients?
|
SELECT T2.city FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN state AS T3 ON T2.state_abbrev = T3.StateCode WHERE T3.Region = 'Midwest' GROUP BY T2.city ORDER BY COUNT(T2.city) LIMIT 1
|
[
"Which",
"city",
"in",
"the",
"Midwest",
"region",
"has",
"the",
"least",
"number",
"of",
"clients",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "state_abbrev"
},
{
"id": 8,
"type": "column",
"value": "district_id"
},
{
"id": 7,
"type": "column",
"value": "statecode"
},
{
"id": 5,
"type": "table",
"value": "district"
},
{
"id": 3,
"type": "value",
"value": "Midwest"
},
{
"id": 2,
"type": "column",
"value": "region"
},
{
"id": 4,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "table",
"value": "state"
},
{
"id": 0,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
797
|
hospital_1
|
spider:train_spider.json:3950
|
Find the names of all patients who have an undergoing treatment and are staying in room 111.
|
SELECT DISTINCT T2.name FROM undergoes AS T1 JOIN patient AS T2 ON T1.patient = T2.SSN JOIN stay AS T3 ON T1.Stay = T3.StayID WHERE T3.room = 111
|
[
"Find",
"the",
"names",
"of",
"all",
"patients",
"who",
"have",
"an",
"undergoing",
"treatment",
"and",
"are",
"staying",
"in",
"room",
"111",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "undergoes"
},
{
"id": 5,
"type": "table",
"value": "patient"
},
{
"id": 8,
"type": "column",
"value": "patient"
},
{
"id": 7,
"type": "column",
"value": "stayid"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "stay"
},
{
"id": 2,
"type": "column",
"value": "room"
},
{
"id": 6,
"type": "column",
"value": "stay"
},
{
"id": 3,
"type": "value",
"value": "111"
},
{
"id": 9,
"type": "column",
"value": "ssn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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13
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
5
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
798
|
movie_3
|
bird:train.json:9162
|
Give the address location of Heather Morris.
|
SELECT T1.address FROM address AS T1 INNER JOIN customer AS T2 ON T1.address_id = T2.address_id WHERE T2.first_name = 'HEATHER' AND T2.last_name = 'MORRIS'
|
[
"Give",
"the",
"address",
"location",
"of",
"Heather",
"Morris",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "address_id"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "address"
},
{
"id": 1,
"type": "table",
"value": "address"
},
{
"id": 5,
"type": "value",
"value": "HEATHER"
},
{
"id": 7,
"type": "value",
"value": "MORRIS"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"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",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
799
|
food_inspection_2
|
bird:train.json:6202
|
State the name of dbas with verified quality.
|
SELECT DISTINCT T1.dba_name FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no WHERE T2.results LIKE '%Pass%'
|
[
"State",
"the",
"name",
"of",
"dbas",
"with",
"verified",
"quality",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "establishment"
},
{
"id": 2,
"type": "table",
"value": "inspection"
},
{
"id": 5,
"type": "column",
"value": "license_no"
},
{
"id": 0,
"type": "column",
"value": "dba_name"
},
{
"id": 3,
"type": "column",
"value": "results"
},
{
"id": 4,
"type": "value",
"value": "%Pass%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
800
|
sales
|
bird:train.json:5418
|
List the first names of customers who have purchased products from sale person id 1.
|
SELECT T1.FirstName FROM Customers AS T1 INNER JOIN Sales AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.SalesPersonID = 1
|
[
"List",
"the",
"first",
"names",
"of",
"customers",
"who",
"have",
"purchased",
"products",
"from",
"sale",
"person",
"i",
"d",
"1",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "salespersonid"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "sales"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13,
14
]
},
{
"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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
801
|
music_platform_2
|
bird:train.json:7947
|
What is the percentage of reviews added each year of the total reviews added?
|
SELECT CAST((SUM(CASE WHEN run_at LIKE '2022-%' THEN reviews_added ELSE 0 END) - SUM(CASE WHEN run_at LIKE '2021-%' THEN reviews_added ELSE 0 END)) AS REAL) * 100 / SUM(reviews_added) OR '%' "percentage" FROM runs
|
[
"What",
"is",
"the",
"percentage",
"of",
"reviews",
"added",
"each",
"year",
"of",
"the",
"total",
"reviews",
"added",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "reviews_added"
},
{
"id": 5,
"type": "column",
"value": "run_at"
},
{
"id": 6,
"type": "value",
"value": "2022-%"
},
{
"id": 7,
"type": "value",
"value": "2021-%"
},
{
"id": 0,
"type": "table",
"value": "runs"
},
{
"id": 2,
"type": "value",
"value": "100"
},
{
"id": 1,
"type": "value",
"value": "%"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
802
|
department_store
|
spider:train_spider.json:4740
|
What are the ids and names of department stores with both marketing and managing departments?
|
SELECT T2.dept_store_id , T2.store_name FROM departments AS T1 JOIN department_stores AS T2 ON T1.dept_store_id = T2.dept_store_id WHERE T1.department_name = "marketing" INTERSECT SELECT T2.dept_store_id , T2.store_name FROM departments AS T1 JOIN department_stores AS T2 ON T1.dept_store_id = T2.dept_store_id WHERE T1.department_name = "managing"
|
[
"What",
"are",
"the",
"ids",
"and",
"names",
"of",
"department",
"stores",
"with",
"both",
"marketing",
"and",
"managing",
"departments",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "department_stores"
},
{
"id": 4,
"type": "column",
"value": "department_name"
},
{
"id": 0,
"type": "column",
"value": "dept_store_id"
},
{
"id": 2,
"type": "table",
"value": "departments"
},
{
"id": 1,
"type": "column",
"value": "store_name"
},
{
"id": 5,
"type": "column",
"value": "marketing"
},
{
"id": 6,
"type": "column",
"value": "managing"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
803
|
art_1
|
bird:test.json:1283
|
What are the locations that have works painted before 1885 and after 1930?
|
SELECT DISTINCT LOCATION FROM paintings WHERE YEAR < 1885 INTERSECT SELECT DISTINCT LOCATION FROM paintings WHERE YEAR > 1930
|
[
"What",
"are",
"the",
"locations",
"that",
"have",
"works",
"painted",
"before",
"1885",
"and",
"after",
"1930",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "1885"
},
{
"id": 4,
"type": "value",
"value": "1930"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
804
|
art_1
|
bird:test.json:1307
|
Order all of the oil paintings by date of creation and list their ids, locations, and titles.
|
SELECT paintingID , title , LOCATION FROM paintings WHERE medium = "oil" ORDER BY YEAR
|
[
"Order",
"all",
"of",
"the",
"oil",
"paintings",
"by",
"date",
"of",
"creation",
"and",
"list",
"their",
"ids",
",",
"locations",
",",
"and",
"titles",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "paintingid"
},
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 3,
"type": "column",
"value": "location"
},
{
"id": 4,
"type": "column",
"value": "medium"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "column",
"value": "oil"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
805
|
hockey
|
bird:train.json:7683
|
Which team did player Id "roypa01" play in 1992? Give the team id.
|
SELECT tmID FROM Goalies WHERE playerID = 'roypa01' AND year = 1992
|
[
"Which",
"team",
"did",
"player",
"I",
"d",
"\"",
"roypa01",
"\"",
"play",
"in",
"1992",
"?",
"Give",
"the",
"team",
"i",
"d."
] |
[
{
"id": 2,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "goalies"
},
{
"id": 3,
"type": "value",
"value": "roypa01"
},
{
"id": 1,
"type": "column",
"value": "tmid"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "1992"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
15,
16,
17
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN"
] |
806
|
movie_3
|
bird:train.json:9264
|
To which country does the address '1386 Nakhon Sawan Boulevard' belong?
|
SELECT T1.country FROM country AS T1 INNER JOIN city AS T2 ON T1.country_id = T2.country_id INNER JOIN address AS T3 ON T2.city_id = T3.city_id WHERE T3.address = '1386 Nakhon Sawan Boulevard'
|
[
"To",
"which",
"country",
"does",
"the",
"address",
"'",
"1386",
"Nakhon",
"Sawan",
"Boulevard",
"'",
"belong",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "1386 Nakhon Sawan Boulevard"
},
{
"id": 7,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "address"
},
{
"id": 2,
"type": "column",
"value": "address"
},
{
"id": 4,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "city_id"
},
{
"id": 5,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
807
|
soccer_2
|
spider:train_spider.json:5012
|
Find the average hours for the students whose tryout decision is no.
|
SELECT avg(T1.HS) FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T2.decision = 'no'
|
[
"Find",
"the",
"average",
"hours",
"for",
"the",
"students",
"whose",
"tryout",
"decision",
"is",
"no",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "decision"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 1,
"type": "table",
"value": "tryout"
},
{
"id": 5,
"type": "column",
"value": "pid"
},
{
"id": 3,
"type": "value",
"value": "no"
},
{
"id": 4,
"type": "column",
"value": "hs"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
808
|
card_games
|
bird:dev.json:463
|
How many translations are there for the set of cards with "Angel of Mercy" in it?
|
SELECT COUNT(DISTINCT translation) FROM set_translations WHERE setCode IN ( SELECT setCode FROM cards WHERE name = 'Angel of Mercy' ) AND translation IS NOT NULL
|
[
"How",
"many",
"translations",
"are",
"there",
"for",
"the",
"set",
"of",
"cards",
"with",
"\"",
"Angel",
"of",
"Mercy",
"\"",
"in",
"it",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "set_translations"
},
{
"id": 5,
"type": "value",
"value": "Angel of Mercy"
},
{
"id": 1,
"type": "column",
"value": "translation"
},
{
"id": 2,
"type": "column",
"value": "setcode"
},
{
"id": 3,
"type": "table",
"value": "cards"
},
{
"id": 4,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12,
13,
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",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
809
|
legislator
|
bird:train.json:4842
|
Provide the type and end date of the term of the legislator named John Vining.
|
SELECT T2.type, T2.end FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.first_name = 'John' AND T1.last_name = 'Vining'
|
[
"Provide",
"the",
"type",
"and",
"end",
"date",
"of",
"the",
"term",
"of",
"the",
"legislator",
"named",
"John",
"Vining",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "historical-terms"
},
{
"id": 4,
"type": "column",
"value": "bioguide_id"
},
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 6,
"type": "column",
"value": "first_name"
},
{
"id": 8,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "bioguide"
},
{
"id": 9,
"type": "value",
"value": "Vining"
},
{
"id": 0,
"type": "column",
"value": "type"
},
{
"id": 7,
"type": "value",
"value": "John"
},
{
"id": 1,
"type": "column",
"value": "end"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
14
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
810
|
cre_Theme_park
|
spider:train_spider.json:5946
|
Which transportation method is used the most often to get to tourist attractions?
|
SELECT How_to_Get_There FROM Tourist_Attractions GROUP BY How_to_Get_There ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Which",
"transportation",
"method",
"is",
"used",
"the",
"most",
"often",
"to",
"get",
"to",
"tourist",
"attractions",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "tourist_attractions"
},
{
"id": 1,
"type": "column",
"value": "how_to_get_there"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11,
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
811
|
computer_student
|
bird:train.json:984
|
How many people teaches course no.11?
|
SELECT COUNT(*) FROM taughtBy WHERE course_id = 11
|
[
"How",
"many",
"people",
"teaches",
"course",
"no.11",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "course_id"
},
{
"id": 0,
"type": "table",
"value": "taughtby"
},
{
"id": 2,
"type": "value",
"value": "11"
}
] |
[
{
"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",
"O"
] |
812
|
movies_4
|
bird:train.json:439
|
When was the first movie released?
|
SELECT MIN(release_date) FROM movie WHERE movie_status = 'Released'
|
[
"When",
"was",
"the",
"first",
"movie",
"released",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "movie_status"
},
{
"id": 3,
"type": "column",
"value": "release_date"
},
{
"id": 2,
"type": "value",
"value": "Released"
},
{
"id": 0,
"type": "table",
"value": "movie"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
813
|
mondial_geo
|
bird:train.json:8496
|
What is the name of the country with the smallest population, and what is its gross domestic product?
|
SELECT T1.Name, T2.GDP FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country ORDER BY T1.Population ASC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"country",
"with",
"the",
"smallest",
"population",
",",
"and",
"what",
"is",
"its",
"gross",
"domestic",
"product",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "population"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "table",
"value": "economy"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
},
{
"id": 1,
"type": "column",
"value": "gdp"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
814
|
public_review_platform
|
bird:train.json:3781
|
Which closed/not running Yelp business in "Sun City" has got the most reviews? Give the business id.
|
SELECT T1.business_id FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.city LIKE 'Sun City' AND T1.active LIKE 'FALSE' GROUP BY T1.business_id ORDER BY COUNT(T2.review_length) DESC LIMIT 1
|
[
"Which",
"closed",
"/",
"not",
"running",
"Yelp",
"business",
"in",
"\"",
"Sun",
"City",
"\"",
"has",
"got",
"the",
"most",
"reviews",
"?",
"Give",
"the",
"business",
"i",
"d."
] |
[
{
"id": 7,
"type": "column",
"value": "review_length"
},
{
"id": 0,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "business"
},
{
"id": 4,
"type": "value",
"value": "Sun City"
},
{
"id": 2,
"type": "table",
"value": "reviews"
},
{
"id": 5,
"type": "column",
"value": "active"
},
{
"id": 6,
"type": "value",
"value": "FALSE"
},
{
"id": 3,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20,
21,
22
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
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"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": [
17,
19
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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},
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"entity_id": 10,
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},
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN"
] |
815
|
address
|
bird:train.json:5168
|
Provide the zip code, city, and congress representative's full names of the area which has highest population in 2020.
|
SELECT T1.zip_code, T1.city, T3.first_name, T3.last_name FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id GROUP BY T2.district ORDER BY T1.population_2020 DESC LIMIT 1
|
[
"Provide",
"the",
"zip",
"code",
",",
"city",
",",
"and",
"congress",
"representative",
"'s",
"full",
"names",
"of",
"the",
"area",
"which",
"has",
"highest",
"population",
"in",
"2020",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "population_2020"
},
{
"id": 9,
"type": "column",
"value": "cognress_rep_id"
},
{
"id": 8,
"type": "table",
"value": "zip_congress"
},
{
"id": 3,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "column",
"value": "district"
},
{
"id": 1,
"type": "column",
"value": "zip_code"
},
{
"id": 5,
"type": "table",
"value": "congress"
},
{
"id": 7,
"type": "table",
"value": "zip_data"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
19,
20,
21
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
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"entity_id": 10,
"token_idxs": []
},
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
816
|
flight_4
|
spider:train_spider.json:6851
|
Return the cities with more than 3 airports in the United States.
|
SELECT city FROM airports WHERE country = 'United States' GROUP BY city HAVING count(*) > 3
|
[
"Return",
"the",
"cities",
"with",
"more",
"than",
"3",
"airports",
"in",
"the",
"United",
"States",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "United States"
},
{
"id": 0,
"type": "table",
"value": "airports"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
817
|
sakila_1
|
spider:train_spider.json:2970
|
How many languages are in these films?
|
SELECT count(DISTINCT language_id) FROM film
|
[
"How",
"many",
"languages",
"are",
"in",
"these",
"films",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "language_id"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
818
|
shipping
|
bird:train.json:5601
|
What is the area of the destination city of shipment No.1346?
|
SELECT T2.area FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T1.ship_id = '1346'
|
[
"What",
"is",
"the",
"area",
"of",
"the",
"destination",
"city",
"of",
"shipment",
"No.1346",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "column",
"value": "ship_id"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 0,
"type": "column",
"value": "area"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "1346"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
819
|
voter_2
|
spider:train_spider.json:5503
|
Which advisors have more than two students?
|
SELECT Advisor FROM STUDENT GROUP BY Advisor HAVING COUNT(*) > 2
|
[
"Which",
"advisors",
"have",
"more",
"than",
"two",
"students",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "advisor"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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",
"B-TABLE",
"O"
] |
820
|
olympics
|
bird:train.json:4949
|
Which region do most of the athletes are from?
|
SELECT T2.region_name FROM person_region AS T1 INNER JOIN noc_region AS T2 ON T1.region_id = T2.id GROUP BY T2.region_name ORDER BY COUNT(T1.person_id) DESC LIMIT 1
|
[
"Which",
"region",
"do",
"most",
"of",
"the",
"athletes",
"are",
"from",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "person_region"
},
{
"id": 0,
"type": "column",
"value": "region_name"
},
{
"id": 2,
"type": "table",
"value": "noc_region"
},
{
"id": 3,
"type": "column",
"value": "region_id"
},
{
"id": 5,
"type": "column",
"value": "person_id"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
824
|
retails
|
bird:train.json:6813
|
Which region has the lowest number of countries?
|
SELECT T.r_name FROM ( SELECT T1.r_name, COUNT(T2.n_name) AS num FROM region AS T1 INNER JOIN nation AS T2 ON T1.r_regionkey = T2.n_regionkey GROUP BY T1.r_name ) AS T ORDER BY T.num LIMIT 1
|
[
"Which",
"region",
"has",
"the",
"lowest",
"number",
"of",
"countries",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "r_regionkey"
},
{
"id": 6,
"type": "column",
"value": "n_regionkey"
},
{
"id": 0,
"type": "column",
"value": "r_name"
},
{
"id": 2,
"type": "table",
"value": "region"
},
{
"id": 3,
"type": "table",
"value": "nation"
},
{
"id": 4,
"type": "column",
"value": "n_name"
},
{
"id": 1,
"type": "column",
"value": "num"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
825
|
talkingdata
|
bird:train.json:1226
|
Which behavior category does user number 5902120154267990000 belong to?
|
SELECT T1.category FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T2.app_id = 5902120154267990000
|
[
"Which",
"behavior",
"category",
"does",
"user",
"number",
"5902120154267990000",
"belong",
"to",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "5902120154267990000"
},
{
"id": 1,
"type": "table",
"value": "label_categories"
},
{
"id": 2,
"type": "table",
"value": "app_labels"
},
{
"id": 0,
"type": "column",
"value": "category"
},
{
"id": 5,
"type": "column",
"value": "label_id"
},
{
"id": 3,
"type": "column",
"value": "app_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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6
]
},
{
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},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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},
{
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},
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"token_idxs": []
},
{
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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",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
826
|
insurance_fnol
|
spider:train_spider.json:898
|
Find the phone numbers of customers using the most common policy type among the available policies.
|
SELECT customer_phone FROM available_policies WHERE policy_type_code = (SELECT policy_type_code FROM available_policies GROUP BY policy_type_code ORDER BY count(*) DESC LIMIT 1)
|
[
"Find",
"the",
"phone",
"numbers",
"of",
"customers",
"using",
"the",
"most",
"common",
"policy",
"type",
"among",
"the",
"available",
"policies",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "available_policies"
},
{
"id": 2,
"type": "column",
"value": "policy_type_code"
},
{
"id": 1,
"type": "column",
"value": "customer_phone"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14,
15
]
},
{
"entity_id": 1,
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5
]
},
{
"entity_id": 2,
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10,
11
]
},
{
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},
{
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},
{
"entity_id": 5,
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},
{
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
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},
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"entity_id": 12,
"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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
827
|
formula_1
|
bird:dev.json:940
|
Among the drivers that finished the race in the 2008 Chinese Grand Prix, how many of them have participated in Formula_1 races?
|
SELECT COUNT(*) FROM ( SELECT T1.driverId FROM results AS T1 INNER JOIN races AS T2 on T1.raceId = T2.raceId WHERE T2.name = 'Chinese Grand Prix' AND T2.year = 2008 AND T1.time IS NOT NULL GROUP BY T1.driverId HAVING COUNT(T2.raceId) > 0 )
|
[
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",",
"how",
"many",
"of",
"them",
"have",
"participated",
"in",
"Formula_1",
"races",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Chinese Grand Prix"
},
{
"id": 0,
"type": "column",
"value": "driverid"
},
{
"id": 1,
"type": "table",
"value": "results"
},
{
"id": 4,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "2008"
},
{
"id": 9,
"type": "column",
"value": "time"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
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{
"entity_id": 0,
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2
]
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"entity_id": 1,
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{
"entity_id": 2,
"token_idxs": [
22
]
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{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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6
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{
"entity_id": 5,
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{
"entity_id": 6,
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10,
11,
12
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9
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"entity_id": 12,
"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": []
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
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"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
829
|
e_commerce
|
bird:test.json:91
|
What is the number of products that have not been ordered yet?
|
SELECT count(*) FROM Products WHERE product_id NOT IN ( SELECT product_id FROM Order_items )
|
[
"What",
"is",
"the",
"number",
"of",
"products",
"that",
"have",
"not",
"been",
"ordered",
"yet",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "order_items"
},
{
"id": 1,
"type": "column",
"value": "product_id"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
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5
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},
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},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
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},
{
"entity_id": 4,
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},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
830
|
cs_semester
|
bird:train.json:903
|
What is the average number of students who registered for the courses with a difficulty of 4?
|
SELECT CAST(COUNT(T1.student_id) AS REAL) / COUNT(DISTINCT T2.course_id) FROM registration AS T1 INNER JOIN course AS T2 ON T1.course_id = T2.course_id WHERE T2.diff = 4
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"students",
"who",
"registered",
"for",
"the",
"courses",
"with",
"a",
"difficulty",
"of",
"4",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "registration"
},
{
"id": 5,
"type": "column",
"value": "student_id"
},
{
"id": 4,
"type": "column",
"value": "course_id"
},
{
"id": 1,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "column",
"value": "diff"
},
{
"id": 3,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
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11
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},
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16
]
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{
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6
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{
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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",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
831
|
codebase_community
|
bird:dev.json:542
|
What is the total number of comments of all the posts owned by csgillespie?
|
SELECT SUM(T1.CommentCount) FROM posts AS T1 INNER JOIN users AS T2 ON T1.OwnerUserId = T2.Id WHERE T2.DisplayName = 'csgillespie'
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"comments",
"of",
"all",
"the",
"posts",
"owned",
"by",
"csgillespie",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "commentcount"
},
{
"id": 2,
"type": "column",
"value": "displayname"
},
{
"id": 3,
"type": "value",
"value": "csgillespie"
},
{
"id": 5,
"type": "column",
"value": "owneruserid"
},
{
"id": 0,
"type": "table",
"value": "posts"
},
{
"id": 1,
"type": "table",
"value": "users"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
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},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
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11
]
},
{
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{
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{
"entity_id": 9,
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{
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},
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
833
|
hospital_1
|
spider:train_spider.json:3959
|
Find the physician who prescribed the highest dose. What is his or her name?
|
SELECT T1.name FROM physician AS T1 JOIN prescribes AS T2 ON T1.employeeid = T2.physician ORDER BY T2.dose DESC LIMIT 1
|
[
"Find",
"the",
"physician",
"who",
"prescribed",
"the",
"highest",
"dose",
".",
"What",
"is",
"his",
"or",
"her",
"name",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "prescribes"
},
{
"id": 4,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "physician"
},
{
"id": 5,
"type": "column",
"value": "physician"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "dose"
}
] |
[
{
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},
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},
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4
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2
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
834
|
legislator
|
bird:train.json:4881
|
What is the party of the oldest legislator?
|
SELECT T1.party FROM `historical-terms` AS T1 INNER JOIN historical AS T2 ON T2.bioguide_id = T1.bioguide ORDER BY T2.birthday_bio LIMIT 1
|
[
"What",
"is",
"the",
"party",
"of",
"the",
"oldest",
"legislator",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "historical-terms"
},
{
"id": 3,
"type": "column",
"value": "birthday_bio"
},
{
"id": 4,
"type": "column",
"value": "bioguide_id"
},
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 5,
"type": "column",
"value": "bioguide"
},
{
"id": 0,
"type": "column",
"value": "party"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
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},
{
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},
{
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},
{
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{
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{
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},
{
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},
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},
{
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},
{
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
835
|
thrombosis_prediction
|
bird:dev.json:1281
|
Among the patients who have an abnormal level of glutamic oxaloacetic transaminase, when was the youngest of them born?
|
SELECT T1.Birthday FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.GOT >= 60 ORDER BY T1.Birthday DESC LIMIT 1
|
[
"Among",
"the",
"patients",
"who",
"have",
"an",
"abnormal",
"level",
"of",
"glutamic",
"oxaloacetic",
"transaminase",
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"when",
"was",
"the",
"youngest",
"of",
"them",
"born",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "column",
"value": "birthday"
},
{
"id": 1,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "got"
},
{
"id": 4,
"type": "value",
"value": "60"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
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{
"entity_id": 1,
"token_idxs": [
2
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},
{
"entity_id": 14,
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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-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
836
|
bakery_1
|
bird:test.json:1531
|
List distinct receipt numbers for which someone bought a good that costs more than 13 dollars.
|
SELECT DISTINCT T1.ReceiptNumber FROM receipts AS T1 JOIN items AS T2 ON T1.ReceiptNumber = T2.receipt JOIN goods AS T3 ON T2.item = T3.id WHERE T3.price > 13
|
[
"List",
"distinct",
"receipt",
"numbers",
"for",
"which",
"someone",
"bought",
"a",
"good",
"that",
"costs",
"more",
"than",
"13",
"dollars",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "receiptnumber"
},
{
"id": 4,
"type": "table",
"value": "receipts"
},
{
"id": 8,
"type": "column",
"value": "receipt"
},
{
"id": 1,
"type": "table",
"value": "goods"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 5,
"type": "table",
"value": "items"
},
{
"id": 6,
"type": "column",
"value": "item"
},
{
"id": 3,
"type": "value",
"value": "13"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
2
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
837
|
retail_complains
|
bird:train.json:366
|
Between 1/1/2017 and 4/1/2017, what is the average server time of calls under the server DARMON?
|
SELECT AVG(CAST(SUBSTR(ser_time, 4, 2) AS REAL)) FROM callcenterlogs WHERE `Date received` BETWEEN '2017-01-01' AND '2017-04-01'
|
[
"Between",
"1/1/2017",
"and",
"4/1/2017",
",",
"what",
"is",
"the",
"average",
"server",
"time",
"of",
"calls",
"under",
"the",
"server",
"DARMON",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 1,
"type": "column",
"value": "Date received"
},
{
"id": 2,
"type": "value",
"value": "2017-01-01"
},
{
"id": 3,
"type": "value",
"value": "2017-04-01"
},
{
"id": 4,
"type": "column",
"value": "ser_time"
},
{
"id": 5,
"type": "value",
"value": "4"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"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": [
9,
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
838
|
party_host
|
spider:train_spider.json:2671
|
Which party had the most hosts? Give me the party location.
|
SELECT LOCATION FROM party ORDER BY Number_of_hosts DESC LIMIT 1
|
[
"Which",
"party",
"had",
"the",
"most",
"hosts",
"?",
"Give",
"me",
"the",
"party",
"location",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "number_of_hosts"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "party"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"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-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
839
|
cars
|
bird:train.json:3079
|
What are the miles per gallon of the most expensive car?
|
SELECT T1.mpg FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID ORDER BY T2.price DESC LIMIT 1
|
[
"What",
"are",
"the",
"miles",
"per",
"gallon",
"of",
"the",
"most",
"expensive",
"car",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "price"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "data"
},
{
"id": 0,
"type": "column",
"value": "mpg"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
840
|
advertising_agencies
|
bird:test.json:2143
|
What are the id, sic code and agency id of the client who has attended 1 meeting and has any invoice.
|
SELECT T1.client_id , T1.sic_code , T1.agency_id FROM clients AS T1 JOIN meetings AS T2 ON T1.client_id = T2.client_id GROUP BY T1.client_id HAVING count(*) = 1 INTERSECT SELECT T1.client_id , T1.sic_code , T1.agency_id FROM clients AS T1 JOIN invoices AS T2 ON T1.client_id = T2.client_id
|
[
"What",
"are",
"the",
"i",
"d",
",",
"sic",
"code",
"and",
"agency",
"i",
"d",
"of",
"the",
"client",
"who",
"has",
"attended",
"1",
"meeting",
"and",
"has",
"any",
"invoice",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "client_id"
},
{
"id": 2,
"type": "column",
"value": "agency_id"
},
{
"id": 1,
"type": "column",
"value": "sic_code"
},
{
"id": 4,
"type": "table",
"value": "meetings"
},
{
"id": 6,
"type": "table",
"value": "invoices"
},
{
"id": 3,
"type": "table",
"value": "clients"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
19
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": [
23
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
841
|
shakespeare
|
bird:train.json:3016
|
List the character names and descriptions of chapter ID 18710.
|
SELECT DISTINCT T1.CharName, T1.Description FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T2.Chapter_id = 18710
|
[
"List",
"the",
"character",
"names",
"and",
"descriptions",
"of",
"chapter",
"ID",
"18710",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "character_id"
},
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "characters"
},
{
"id": 3,
"type": "table",
"value": "paragraphs"
},
{
"id": 4,
"type": "column",
"value": "chapter_id"
},
{
"id": 0,
"type": "column",
"value": "charname"
},
{
"id": 5,
"type": "value",
"value": "18710"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O"
] |
842
|
bike_share_1
|
bird:train.json:9066
|
What is the location coordinates of the bike station from which the bike for the trip that last the longest was borrowed?
|
SELECT T2.lat, T2.long FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.duration = ( SELECT MAX(T1.duration) FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name )
|
[
"What",
"is",
"the",
"location",
"coordinates",
"of",
"the",
"bike",
"station",
"from",
"which",
"the",
"bike",
"for",
"the",
"trip",
"that",
"last",
"the",
"longest",
"was",
"borrowed",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "start_station_name"
},
{
"id": 4,
"type": "column",
"value": "duration"
},
{
"id": 3,
"type": "table",
"value": "station"
},
{
"id": 1,
"type": "column",
"value": "long"
},
{
"id": 2,
"type": "table",
"value": "trip"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "lat"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17
]
},
{
"entity_id": 1,
"token_idxs": [
19
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
843
|
shipping
|
bird:train.json:5671
|
Where does the driver of ship ID 1127 live?
|
SELECT T2.address FROM shipment AS T1 INNER JOIN driver AS T2 ON T1.driver_id = T2.driver_id WHERE T1.ship_id = '1127'
|
[
"Where",
"does",
"the",
"driver",
"of",
"ship",
"ID",
"1127",
"live",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "driver_id"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 0,
"type": "column",
"value": "address"
},
{
"id": 3,
"type": "column",
"value": "ship_id"
},
{
"id": 2,
"type": "table",
"value": "driver"
},
{
"id": 4,
"type": "value",
"value": "1127"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
5,
6
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O"
] |
844
|
student_club
|
bird:dev.json:1440
|
List emails of people who paid more than 20 dollars from 9/10/2019 to 11/19/2019.
|
SELECT DISTINCT T1.email FROM member AS T1 INNER JOIN expense AS T2 ON T1.member_id = T2.link_to_member WHERE date(SUBSTR(T2.expense_date, 1, 10)) BETWEEN '2019-09-10' AND '2019-11-19' AND T2.cost > 20
|
[
"List",
"emails",
"of",
"people",
"who",
"paid",
"more",
"than",
"20",
"dollars",
"from",
"9/10/2019",
"to",
"11/19/2019",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "link_to_member"
},
{
"id": 9,
"type": "column",
"value": "expense_date"
},
{
"id": 5,
"type": "value",
"value": "2019-09-10"
},
{
"id": 6,
"type": "value",
"value": "2019-11-19"
},
{
"id": 3,
"type": "column",
"value": "member_id"
},
{
"id": 2,
"type": "table",
"value": "expense"
},
{
"id": 1,
"type": "table",
"value": "member"
},
{
"id": 0,
"type": "column",
"value": "email"
},
{
"id": 7,
"type": "column",
"value": "cost"
},
{
"id": 8,
"type": "value",
"value": "20"
},
{
"id": 11,
"type": "value",
"value": "10"
},
{
"id": 10,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
845
|
car_retails
|
bird:train.json:1653
|
Please list the top three product names with the highest unit price.
|
SELECT t1.productName FROM products AS t1 INNER JOIN orderdetails AS t2 ON t1.productCode = t2.productCode ORDER BY t2.priceEach DESC LIMIT 3
|
[
"Please",
"list",
"the",
"top",
"three",
"product",
"names",
"with",
"the",
"highest",
"unit",
"price",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "orderdetails"
},
{
"id": 0,
"type": "column",
"value": "productname"
},
{
"id": 4,
"type": "column",
"value": "productcode"
},
{
"id": 3,
"type": "column",
"value": "priceeach"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
846
|
medicine_enzyme_interaction
|
spider:train_spider.json:971
|
How many distinct FDA approval statuses are there for the medicines?
|
SELECT count(DISTINCT FDA_approved) FROM medicine
|
[
"How",
"many",
"distinct",
"FDA",
"approval",
"statuses",
"are",
"there",
"for",
"the",
"medicines",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "fda_approved"
},
{
"id": 0,
"type": "table",
"value": "medicine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
847
|
video_games
|
bird:train.json:3422
|
How many times did other regions make positive sales in DS platform?
|
SELECT COUNT(DISTINCT T2.id) FROM platform AS T1 INNER JOIN game_platform AS T2 ON T1.id = T2.platform_id INNER JOIN region_sales AS T3 ON T1.id = T3.game_platform_id INNER JOIN region AS T4 ON T3.region_id = T4.id WHERE T1.platform_name = 'DS' AND T4.region_name = 'Other' AND T3.num_sales > 0
|
[
"How",
"many",
"times",
"did",
"other",
"regions",
"make",
"positive",
"sales",
"in",
"DS",
"platform",
"?"
] |
[
{
"id": 12,
"type": "column",
"value": "game_platform_id"
},
{
"id": 4,
"type": "column",
"value": "platform_name"
},
{
"id": 11,
"type": "table",
"value": "game_platform"
},
{
"id": 2,
"type": "table",
"value": "region_sales"
},
{
"id": 6,
"type": "column",
"value": "region_name"
},
{
"id": 13,
"type": "column",
"value": "platform_id"
},
{
"id": 3,
"type": "column",
"value": "region_id"
},
{
"id": 8,
"type": "column",
"value": "num_sales"
},
{
"id": 10,
"type": "table",
"value": "platform"
},
{
"id": 0,
"type": "table",
"value": "region"
},
{
"id": 7,
"type": "value",
"value": "Other"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "DS"
},
{
"id": 9,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
11
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
848
|
movie_1
|
spider:train_spider.json:2491
|
What are the names of all directors who made one movie?
|
SELECT director FROM Movie GROUP BY director HAVING count(*) = 1
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"directors",
"who",
"made",
"one",
"movie",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "director"
},
{
"id": 0,
"type": "table",
"value": "movie"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"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",
"O",
"B-TABLE",
"O"
] |
849
|
menu
|
bird:train.json:5549
|
Provide the menu page ids of all the menu that includes mashed potatoes.
|
SELECT T2.menu_page_id FROM Dish AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.dish_id WHERE T1.name = 'Mashed potatoes'
|
[
"Provide",
"the",
"menu",
"page",
"ids",
"of",
"all",
"the",
"menu",
"that",
"includes",
"mashed",
"potatoes",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Mashed potatoes"
},
{
"id": 0,
"type": "column",
"value": "menu_page_id"
},
{
"id": 2,
"type": "table",
"value": "menuitem"
},
{
"id": 6,
"type": "column",
"value": "dish_id"
},
{
"id": 1,
"type": "table",
"value": "dish"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"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",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
850
|
driving_school
|
spider:train_spider.json:6655
|
In which city do the most employees live and how many of them live there?
|
SELECT T1.city , count(*) FROM Addresses AS T1 JOIN Staff AS T2 ON T1.address_id = T2.staff_address_id GROUP BY T1.city ORDER BY count(*) DESC LIMIT 1;
|
[
"In",
"which",
"city",
"do",
"the",
"most",
"employees",
"live",
"and",
"how",
"many",
"of",
"them",
"live",
"there",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "staff_address_id"
},
{
"id": 3,
"type": "column",
"value": "address_id"
},
{
"id": 1,
"type": "table",
"value": "addresses"
},
{
"id": 2,
"type": "table",
"value": "staff"
},
{
"id": 0,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
851
|
student_club
|
bird:dev.json:1363
|
List all of the College of Humanities and Social Sciences' departments.
|
SELECT department FROM major WHERE college = 'College of Humanities and Social Sciences'
|
[
"List",
"all",
"of",
"the",
"College",
"of",
"Humanities",
"and",
"Social",
"Sciences",
"'",
"departments",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "College of Humanities and Social Sciences"
},
{
"id": 1,
"type": "column",
"value": "department"
},
{
"id": 2,
"type": "column",
"value": "college"
},
{
"id": 0,
"type": "table",
"value": "major"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
5,
6,
7,
8,
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O"
] |
852
|
talkingdata
|
bird:train.json:1206
|
Identify by their id all the apps that belong to the game-stress reliever category.
|
SELECT T2.app_id FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T1.category = 'game-stress reliever'
|
[
"Identify",
"by",
"their",
"i",
"d",
"all",
"the",
"apps",
"that",
"belong",
"to",
"the",
"game",
"-",
"stress",
"reliever",
"category",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "game-stress reliever"
},
{
"id": 1,
"type": "table",
"value": "label_categories"
},
{
"id": 2,
"type": "table",
"value": "app_labels"
},
{
"id": 3,
"type": "column",
"value": "category"
},
{
"id": 5,
"type": "column",
"value": "label_id"
},
{
"id": 0,
"type": "column",
"value": "app_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
12,
13,
14,
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
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